All tags
Topic: "model-performance"
Execuhires Round 2: Scale-Meta, Lamini-AMD, and Instacart-OpenAI
o3-pro o3 o1-pro gpt-4o gpt-4.1 gpt-4.1-mini gpt-4.1-nano meta-ai-fair scale-ai lamini amd openai gemini google anthropic model-release benchmarking reasoning fine-tuning pricing model-performance direct-preference-optimization complex-problem-solving alexandr_wang sharon_zhou fidji_simo sama jack_rae markchen90 kevinweil gdb gregkamradt lechmazur wesrothmoney paul_cal imjaredz cto_junior johnowhitaker polynoamial scaling01
Meta hires Scale AI's Alexandr Wang to lead its new "Superintelligence" division following a $15 billion investment for a 49% stake in Scale. Lamini's Sharon Zhou joins AMD as VP of AI under Lisa Su, while Instacart's Fidji Simo becomes CEO of Apps at OpenAI under Sama. Meta offers over $10 million/year compensation packages to top researchers, successfully recruiting Jack Rae from Gemini. OpenAI releases o3-pro model to ChatGPT Pro users and API, outperforming o3 and setting new benchmarks like Extended NYT Connections and SnakeBench. Despite being slower than o1-pro, o3-pro excels in reasoning and complex problem-solving. OpenAI cuts o3 pricing by 80%, making it cheaper than GPT-4o and pressuring competitors like Google and Anthropic to lower prices. Users can now fine-tune the GPT-4.1 family using direct preference optimization (DPO) for subjective tasks.
not much happened today
dots-llm1 qwen3-235b xiaohongshu rednote-hilab deepseek huggingface mixture-of-experts open-source model-benchmarking fine-tuning inference context-windows training-data model-architecture model-performance model-optimization
China's Xiaohongshu (Rednote) released dots.llm1, a 142B parameter open-source Mixture-of-Experts (MoE) language model with 14B active parameters and a 32K context window, pretrained on 11.2 trillion high-quality, non-synthetic tokens. The model supports efficient inference frameworks like Docker, HuggingFace, and vLLM, and provides intermediate checkpoints every 1 trillion tokens, enabling flexible fine-tuning. Benchmarking claims it slightly surpasses Qwen3 235B on MMLU, though some concerns exist about benchmark selection and synthetic data verification. The release is notable for its truly open-source licensing and no synthetic data usage, sparking community optimism for support in frameworks such as llama.cpp and mlx.
Gemini 2.5 Pro (06-05) launched at AI Engineer World's Fair
gemini-2.5-pro qwen3-embedding-8b openthinker3-7b google qwen lighton morph-labs openai nvidia benchmarking reasoning coding math embedding-models late-interaction dataset-release model-performance model-architecture ai-conferences greg_brockman jensen_huang christian_szegedy swyx
At the second day of AIE, Google's Gemini 2.5 Pro reclaimed the top spot on the LMArena leaderboard with a score of 1470 and a +24 Elo increase, showing improvements in coding, reasoning, and math. Qwen3 released state-of-the-art embedding and reranking models, with Qwen3-Embedding-8B topping the MTEB multilingual leaderboard. OpenThinker3-7B emerged as the top open reasoning model trained on the OpenThoughts3-1.2M dataset, outperforming previous models by 33%. LightOn introduced FastPlaid, achieving up to a 554% speedup for late-interaction models. Morph Labs hired Christian Szegedy as Chief Scientist to lead Verified Superintelligence development. The AI Engineer World's Fair featured a fireside chat with Greg Brockman and NVIDIA CEO Jensen Huang, highlighting the return of basic research and engineering best practices.
DeepSeek-R1-0528 - Gemini 2.5 Pro-level model, SOTA Open Weights release
deepseek-r1-0528 gemini-2.5-pro qwen-3-8b qwen-3-235b deepseek-ai anthropic meta-ai-fair nvidia alibaba google-deepmind reinforcement-learning benchmarking model-performance open-weights reasoning quantization post-training model-comparison artificialanlys scaling01 cline reach_vb zizhpan andrewyng teortaxestex teknim1 lateinteraction abacaj cognitivecompai awnihannun
DeepSeek R1-0528 marks a significant upgrade, closing the gap with proprietary models like Gemini 2.5 Pro and surpassing benchmarks from Anthropic, Meta, NVIDIA, and Alibaba. This Chinese open-weights model leads in several AI benchmarks, driven by reinforcement learning post-training rather than architecture changes, and demonstrates increased reasoning token usage (23K tokens per question). The China-US AI race intensifies as Chinese labs accelerate innovation through transparency and open research culture. Key benchmarks include AIME 2024, LiveCodeBench, and GPQA Diamond.
not much happened today
deepseek-r1-0528 pali-gemma-2 gemma-3 shieldgemma-2 txgemma gemma-3-qat gemma-3n-preview medgemma dolphingemma signgemma claude-4 opus-4 claude-sonnet-4 codestral-embed bagel qwen nemotron-cortexa gemini-2.5-pro deepseek-ai huggingface gemma claude bytedance qwen nemotron sakana-ai-labs benchmarking model-releases multimodality code-generation model-performance long-context reinforcement-learning model-optimization open-source yuchenj_uw _akhaliq clementdelangue osanseviero alexalbert__ guillaumelample theturingpost lmarena_ai epochairesearch scaling01 nrehiew_ ctnzr
DeepSeek R1 v2 model released with availability on Hugging Face and inference partners. The Gemma model family continues prolific development including PaliGemma 2, Gemma 3, and others. Claude 4 and its variants like Opus 4 and Claude Sonnet 4 show top benchmark performance, including new SOTA on ARC-AGI-2 and WebDev Arena. Codestral Embed introduces a 3072-dimensional code embedder. BAGEL, an open-source multimodal model by ByteDance, supports reading, reasoning, drawing, and editing with long mixed contexts. Benchmarking highlights include Nemotron-CORTEXA topping SWEBench and Gemini 2.5 Pro performing on VideoGameBench. Discussions on random rewards effectiveness focus on Qwen models. "Opus 4 NEW SOTA ON ARC-AGI-2. It's happening - I was right" and "Claude 4 launch has dev moving at a different pace" reflect excitement in the community.
Mistral's Agents API and the 2025 LLM OS
qwen claude-4 chatgpt o3 o4 mistral-ai langchain-ai openai meta-ai-fair agent-frameworks multi-agent-systems tool-use code-execution web-search model-context-protocol persistent-memory function-calling open-source no-code reinforcement-learning model-performance agent-orchestration omarsar0 simonw swyx scaling01
The LLM OS concept has evolved since 2023, with Mistral AI releasing a new Agents API that includes code execution, web search, persistent memory, and agent orchestration. LangChainAI introduced the Open Agent Platform (OAP), an open-source no-code platform for intelligent agents. OpenAI plans to develop ChatGPT into a super-assistant by H1 2025, competing with Meta. Discussions around Qwen models focus on reinforcement learning effects, while Claude 4 performance is also noted. The AI Engineer World's Fair is calling for volunteers.
Google I/O: new Gemini native voice, Flash, DeepThink, AI Mode (DeepSearch+Mariner+Astra)
gemini-2.5-pro gemini-2.5 google google-deepmind ai-assistants reasoning generative-ai developer-tools ai-integration model-optimization ai-application model-updates ai-deployment model-performance demishassabis philschmid jack_w_rae
Google I/O 2024 showcased significant advancements with Gemini 2.5 Pro and Deep Think reasoning mode from google-deepmind, emphasizing AI-driven transformations and developer opportunities. GeminiApp aims to become a universal AI assistant on the path to AGI, with new features like AI Mode in Google Search expanding generative AI access. The event included multiple keynotes and updates on over a dozen models and 20+ AI products, highlighting Google's leadership in AI innovation. Influential voices like demishassabis and philschmid provided insights and recaps, while the launch of Jules as a competitor to Codex/Devin was noted.
not much happened today
kernelllm-8b gpt-4o deepseek-v3 mistral-medium-3 qwen3 blip3-o xgen-small anisora stable-audio-open-small alphaevolve meta-ai-fair mistral-ai qwen deepseek salesforce bilibili stability-ai google benchmarking model-performance multilinguality hardware-optimization multimodality image-generation video-generation text-to-audio model-parallelism chain-of-thought instruction-following reasoning mitigation-strategies reach_vb lmarena_ai theadimeline adcock_brett jxmnop dair_ai omarsar0
Meta released KernelLLM 8B, outperforming GPT-4o and DeepSeek V3 on KernelBench-Triton Level 1. Mistral Medium 3 debuted strongly in multiple benchmarks. Qwen3 models introduced a unified framework with multilingual support. DeepSeek-V3 features hardware-aware co-design. BLIP3-o family released for multimodal tasks using diffusion transformers. Salesforce launched xGen-Small models excelling in long-context and math benchmarks. Bilibili released AniSORA for anime video generation. Stability AI open-sourced Stable Audio Open Small optimized for Arm devices. Google’s AlphaEvolve coding agent improved Strassen's algorithm for the first time since 1969. Research shows chain-of-thought reasoning can harm instruction-following ability, with mitigation strategies like classifier-selective reasoning being most effective, but reasoning techniques show high variance and limited generalization. "Chain-of-thought (CoT) reasoning can harm a model’s ability to follow instructions" and "Mitigation strategies such as few-shot in-context learning, self-reflection, self-selective reasoning, and classifier-selective reasoning can counteract reasoning-induced failures".
ChatGPT Codex, OpenAI's first cloud SWE agent
codex-1 openai-o3 codex-mini gemma-3 blip3-o qwen-2.5 marigold-iid deepseek-v3 lightlab gemini-2.0 lumina-next openai runway salesforce qwen deepseek google google-deepmind j1 software-engineering parallel-processing multimodality diffusion-models depth-estimation scaling-laws reinforcement-learning fine-tuning model-performance multi-turn-conversation reasoning audio-processing sama kevinweil omarsar0 iscienceluvr akhaliq osanseviero c_valenzuelab mervenoyann arankomatsuzaki jasonwei demishassabis philschmid swyx teortaxestex jaseweston
OpenAI launched Codex, a cloud-based software engineering agent powered by codex-1 (an optimized version of OpenAI o3) available in research preview for Pro, Enterprise, and Team ChatGPT users, featuring parallel task execution like refactoring and bug fixing. The Codex CLI was enhanced with quick sign-in and a new low-latency model, codex-mini. Gemma 3 is highlighted as the best open model runnable on a single GPU. Runway released the Gen-4 References API for style transfer in generation. Salesforce introduced BLIP3-o, a unified multimodal model family using diffusion transformers for CLIP image features. The Qwen 2.5 models (1.5B and 3B versions) were integrated into the PocketPal app with various chat templates. Marigold IID, a new state-of-the-art open-source depth estimation model, was released.
In research, DeepSeek shared insights on scaling and hardware for DeepSeek-V3. Google unveiled LightLab, a diffusion-based light source control in images. Google DeepMind's AlphaEvolve uses Gemini 2.0 to discover new math and reduce costs without reinforcement learning. Omni-R1 studied audio's role in fine-tuning audio LLMs. Qwen proposed a parallel scaling law inspired by classifier-free guidance. Salesforce released Lumina-Next on the Qwen base, outperforming Janus-Pro. A study found LLM performance degrades in multi-turn conversations due to unreliability. J1 is incentivizing LLM-as-a-Judge thinking via reinforcement learning. A new Qwen study correlates question and strategy similarity to predict reasoning strategies.
Granola launches team notes, while Notion launches meeting transcription
gpt-4.1 gpt-4o-mini gpt-4.1-mini claude-opus claude-sonnet claude-o3 qwen3 seed1.5-vl llama-4 am-thinking-v1 openai anthropic alibaba meta-ai-fair huggingface granola coding instruction-following benchmarking model-releases reasoning image-generation collaborative-software model-performance kevinweil scaling01 steph_palazzolo andersonbcdefg reach_vb yuchenj_uw qtnx_ _akhaliq risingsayak
GPT-4.1 is now available in ChatGPT for Plus, Pro, and Team users, focusing on coding and instruction following, with GPT 4.1 mini replacing GPT 4o mini. Anthropic is releasing new Claude models including Claude Opus and Claude Sonnet, though some criticism about hallucinations in Claude O3 was noted. Alibaba shared the Qwen3 Technical Report with strong benchmark results from Seed1.5-VL. Meta FAIR announced new models and datasets but faced criticism on Llama 4. AM-Thinking-v1 launched on Hugging Face as a 32B scale reasoning model. Granola raised $43M in Series B and launched Granola 2.0 with a Notion-like UI. The AI ecosystem shows rapid iteration and cloning of ideas, emphasizing execution and distribution.
not much happened today
hunyuan-turbos qwen3-235b-a22b o3 gpt-4.1-nano grok-3 gemini-2.5-pro seed1.5-vl kling-2.0 tencent openai bytedance meta-ai-fair nvidia deepseek benchmarking model-performance moe reasoning vision video-understanding vision-language multimodality model-evaluation model-optimization lmarena_ai artificialanlys gdb _jasonwei iScienceLuvr _akhaliq _philschmid teortaxesTex mervenoyann reach_vb
Tencent's Hunyuan-Turbos has risen to #8 on the LMArena leaderboard, showing strong performance across major categories and significant improvement since February. The Qwen3 model family, especially the Qwen3 235B-A22B (Reasoning) model, is noted for its intelligence and efficient parameter usage. OpenAI introduced HealthBench, a new health evaluation benchmark developed with input from over 250 physicians, where models like o3, GPT-4.1 nano, and Grok 3 showed strong results. ByteDance released Seed1.5-VL, a vision-language model with a 532M-parameter vision encoder and a 20B active parameter MoE LLM, achieving state-of-the-art results on 38 public benchmarks. In vision-language, Kling 2.0 leads image-to-video generation, and Gemini 2.5 Pro excels in video understanding with advanced multimodal capabilities. Meta's Vision-Language-Action framework and updates on VLMs for 2025 were also highlighted.
not much happened today
gemini-2.5-flash gemini-2.0-flash mistral-medium-3 llama-4-maverick claude-3.7-sonnet qwen3 pangu-ultra-moe deepseek-r1 o4-mini x-reasoner google-deepmind mistral-ai alibaba huawei openai microsoft deepseek model-performance reasoning cost-analysis reinforcement-learning chain-of-thought multilinguality code-search model-training vision model-integration giffmana artificialanlys teortaxestex akhaliq john__allard
Gemini 2.5 Flash shows a 12 point increase in the Artificial Analysis Intelligence Index but costs 150x more than Gemini 2.0 Flash due to 9x more expensive output tokens and 17x higher token usage during reasoning. Mistral Medium 3 competes with Llama 4 Maverick, Gemini 2.0 Flash, and Claude 3.7 Sonnet with better coding and math reasoning at a significantly lower price. Alibaba's Qwen3 family supports reasoning and multilingual tasks across 119 languages and includes a Web Dev tool for app building. Huawei's Pangu Ultra MoE matches DeepSeek R1 performance on Ascend NPUs, with new compute and upcoming V4 training. OpenAI's o4-mini now supports Reinforcement Fine-Tuning (RFT) using chain-of-thought reasoning. Microsoft's X-REASONER enables generalizable reasoning across modalities post-trained on general-domain text. Deep research integration with GitHub repos in ChatGPT enhances codebase search and reporting. The AI Engineer World's Fair offers an Early Bird discount for upcoming tickets.
not much happened today
open-code-reasoning-32b open-code-reasoning-14b open-code-reasoning-7b mistral-medium-3 llama-4-maverick gemini-2.5-pro gemini-2.5-flash claude-3.7-sonnet absolute-zero-reasoner x-reasoner fastvlm parakeet-asr openai nvidia mistral-ai google apple huggingface reinforcement-learning fine-tuning code-generation reasoning vision on-device-ai model-performance dataset-release model-optimization reach_vb artificialanlys scaling01 iscienceluvr arankomatsuzaki awnihannun risingsayak
OpenAI launched both Reinforcement Finetuning and Deep Research on GitHub repos, drawing comparisons to Cognition's DeepWiki. Nvidia open-sourced Open Code Reasoning models (32B, 14B, 7B) with Apache 2.0 license, showing 30% better token efficiency and compatibility with llama.cpp, vLLM, transformers, and TGI. Independent evaluations highlight Mistral Medium 3 rivaling Llama 4 Maverick, Gemini 2.0 Flash, and Claude 3.7 Sonnet in coding and math reasoning, priced significantly lower but no longer open-source. Google's Gemini 2.5 Pro is noted as their most intelligent model with improved coding from simple prompts, while Gemini 2.5 Flash incurs a 150x cost increase over Gemini 2.0 Flash due to higher token usage and cost. The Absolute Zero Reasoner (AZR) achieves SOTA performance in coding and math reasoning via reinforced self-play without external data. Vision-language model X-REASONER is post-trained on general-domain text for reasoning. Apple ML research released FastVLM with on-device iPhone demo. HiDream LoRA trainer supports QLoRA fine-tuning under memory constraints. Nvidia's Parakeet ASR model tops Hugging Face ASR leaderboard with MLX implementation. New datasets SwallowCode and SwallowMath boost LLM performance in math and code. Overall, a quiet day with significant model releases and performance insights.
Cursor @ $9b, OpenAI Buys Windsurf @ $3b
llama-nemotron-ultra llama-nemotron-super llama-nemotron-nano qwen3-235b-a22b prover-v2 phi-4-reasoning ernie-4.5-turbo ernie-x1-turbo suno-v4.5 gen-4-references o1-mini openai cursor nvidia alibaba deepseek microsoft baidu suno runway keras reasoning inference-efficiency open-license moe-models math-reasoning theorem-proving model-performance music-generation image-generation recommender-systems tpu-optimization _akhaliq adcock_brett lmarena_ai fchollet
OpenAI is reportedly close to closing a deal with Windsurf, coinciding with Cursor's $900M funding round at a $9B valuation. Nvidia launched the Llama-Nemotron series featuring models from 8B to 253B parameters, praised for reasoning and inference efficiency. Alibaba released the Qwen3 family with MoE and dense models up to 235B parameters, ranking highly in coding and math benchmarks. DeepSeek introduced Prover-V2, an open-source AI for math reasoning with an 88.9% pass rate on MiniF2F-test. Microsoft released reasoning-focused Phi-4 models, outperforming OpenAI's o1-mini. Baidu debuted turbo versions of ERNIE 4.5 and X1 for faster, cheaper inference. Suno v4.5 added advanced AI music generation features, while Runway Gen-4 References enable placing characters into scenes with high consistency. KerasRS, a new recommender system library optimized for TPUs, was released by Fran ois Chollet.
not much happened today
qwen3-14b qwen3-32b qwen3-235b phi-4-reasoning o3-mini command-a gemini-2.5-pro o4-mini olm-o2-1b o3 alibaba together-ai scaling01 microsoft deepseek cohere google epoch-ai-research inception-labs openai allenai quantization fine-tuning reinforcement-learning benchmarking video-generation diffusion-models model-performance model-evaluation model-release text-generation cline _philschmid iscienceluvr alexalbert__ _lewtun teortaxestex sarahookr reach_vb
Qwen model family released quantized versions of Qwen3 models including 14B, 32B, and 235B parameters, with promising coding capabilities in Qwen3-235B. Microsoft launched Phi-4-reasoning, a 14B parameter model distilled from OpenAI's o3-mini, emphasizing supervised fine-tuning and reinforcement learning, outperforming larger models in some benchmarks. Cohere's Command A leads SQL performance on Bird Bench. Google introduced the TRAJAN eval for video generation temporal consistency and updated the Gemini OpenAI compatibility layer. Inception Labs launched a diffusion LLM API claiming 5x speed improvements over autoregressive models. Community rankings show OpenAI's o3 model debuting strongly in web app-building tasks. Other releases include AllenAI's OLMo2 1B and additional Phi 4 variants. "Qwen3-235B shows promise for coding" and "Phi-4-reasoning tech report emphasizes SFT gains" highlight key advancements.
gpt-image-1 - ChatGPT's imagegen model, confusingly NOT 4o, now available in API
gpt-image-1 o3 o4-mini gpt-4.1 eagle-2.5-8b gpt-4o qwen2.5-vl-72b openai nvidia hugging-face x-ai image-generation content-moderation benchmarking long-context multimodality model-performance supercomputing virology video-understanding model-releases kevinweil lmarena_ai _philschmid willdepue arankomatsuzaki epochairesearch danhendrycks reach_vb mervenoyann _akhaliq
OpenAI officially launched the gpt-image-1 API for image generation and editing, supporting features like alpha channel transparency and a "low" content moderation policy. OpenAI's models o3 and o4-mini are leading in benchmarks for style control, math, coding, and hard prompts, with o3 ranking #1 in several categories. A new benchmark called Vending-Bench reveals performance variance in LLMs on extended tasks. GPT-4.1 ranks in the top 5 for hard prompts and math. Nvidia's Eagle 2.5-8B matches GPT-4o and Qwen2.5-VL-72B in long-video understanding. AI supercomputer performance doubles every 9 months, with xAI's Colossus costing an estimated $7 billion and the US dominating 75% of global performance. The Virology Capabilities Test shows OpenAI's o3 outperforms 94% of expert virologists. Nvidia also released the Describe Anything Model (DAM), a multimodal LLM for detailed image and video captioning, now available on Hugging Face.
not much happened today
grok-3 grok-3-mini gpt-4.5 claude-3.7-sonnet quasar-alpha optimus-alpha gpt-4.1 kaleidoscope internvl3 internvit qwen2.5vl transmamba fantasytalking openai alibaba cmu reinforcement-learning reasoning benchmarks vision multilinguality multimodality transformers attention-mechanisms agents code-generation model-performance rasbt sarahookr mervenoyann gneubig svpino mathemagic1an
The AI news recap highlights independent evaluations showing Grok-3 outperforming models like GPT-4.5 and Claude 3.7 Sonnet on reasoning benchmarks, while Grok-3 mini excels in reasoning tasks. Research on reinforcement learning (RL) fine-tuning reveals potential improvements for small reasoning models but also notes instability in reported gains. Benchmark results suggest Quasar Alpha and Optimus Alpha may be versions of GPT-4.1. Vision and multimodal models like Kaleidoscope, supporting 18 languages, and InternVL3, built on InternViT and Qwen2.5VL, demonstrate advances in multilingual vision and reasoning. The fusion model TransMamba combines transformer precision with speed via SSM mechanisms. Alibaba's FantasyTalking generates realistic talking portraits. Agent-focused events at CMU and tools like FilmAgent AI for virtual film production and BrowseComp benchmark for browsing agents were announced. The coding assistant Augment supports multiple IDEs with code analysis and suggestions. Discussions also covered Google’s new agent-to-agent protocol concept.
DeepCoder: A Fully Open-Source 14B Coder at O3-mini Level
deepcoder-14b o3-mini o1 gemini-2.5-pro kimi-vl-a3b gpt-4o llama-4-scout maverick behemoth gen-4-turbo imagen-3 together-ai agentica opena bytedance google-deepmind moonshot-ai meta-ai-fair runway open-source reinforcement-learning code-generation multimodality model-training mixture-of-experts l2-normalization image-generation model-performance context-windows philschmid lepikhin reach_vb akhaliq yuchenj_uw epochairesearch danielhanchen c_valenzuelab
Together AI and Agentica released DeepCoder-14B, an open-source 14B parameter coding model rivaling OpenAI's o3-mini and o1 on coding benchmarks, trained with an open-source RL framework from ByteDance and costing about $26,880. Google DeepMind launched Gemini 2.5 Pro with experimental "Flash" versions available to subscribers. Moonshot AI introduced Kimi-VL-A3B, a multimodal model with 128K context outperforming gpt-4o on vision and math benchmarks. Meta AI released Llama 4 Scout and Maverick, with a larger Behemoth model in training, featuring mixture-of-experts and L2 norm techniques. Runway launched Gen-4 Turbo with 10x better results than Gen-3 at the same cost. Google announced Imagen 3, a high-quality text-to-image model now in Vertex AI, enabling easier object removal. The report highlights open-source contributions, reinforcement learning training optimizations, and significant model performance improvements across coding, multimodal, and image generation domains.
Llama 4's Controversial Weekend Release
llama-4 llama-3 llama-3-2 meta mixture-of-experts early-fusion attention-mechanisms fp8-training training-data benchmarking model-performance model-release multimodality open-models ahmad_al_dahle ylecun reach_vb yuchenj_uw
Meta released Llama 4, featuring two new medium-size MoE open models and a promised 2 Trillion parameter "behemoth" model, aiming to be the largest open model ever. The release included advanced training techniques like Chameleon-like early fusion with MetaCLIP, interleaved chunked attention without RoPE, native FP8 training, and training on up to 40 trillion tokens. Despite the hype, the release faced criticism for lack of transparency compared to Llama 3, implementation issues, and poor performance on some benchmarks. Meta leadership, including Ahmad Al Dahle, denied allegations of training on test sets. The smallest Scout model at 109B parameters is too large for consumer GPUs, and the claimed 10 million token context is disputed. The community response has been mixed, with some praising the openness and others pointing out discrepancies and quality concerns.
not much happened today
gemini-2.5-pro chatgpt deepseek-v3 qwen-2.5 claude-3.5-sonnet claude-3.7-sonnet google anthropic openai llama_index langchain runway deepseek math benchmarking chains-of-thought model-performance multi-agent-systems agent-frameworks media-generation long-horizon-planning code-generation rasbt danielhanchen hkproj
Gemini 2.5 Pro shows strengths and weaknesses, notably lacking LaTex math rendering unlike ChatGPT, and scored 24.4% on the 2025 US AMO. DeepSeek V3 ranks 8th and 12th on recent leaderboards. Qwen 2.5 models have been integrated into the PocketPal app. Research from Anthropic reveals that Chains-of-Thought (CoT) reasoning is often unfaithful, especially on harder tasks, raising safety concerns. OpenAI's PaperBench benchmark shows AI agents struggle with long-horizon planning, with Claude 3.5 Sonnet achieving only 21.0% accuracy. CodeAct framework generalizes ReAct for dynamic code writing by agents. LangChain explains multi-agent handoffs in LangGraph. Runway Gen-4 marks a new phase in media creation.
>$41B raised today (OpenAI @ 300b, Cursor @ 9.5b, Etched @ 1.5b)
deepseek-v3-0324 gemini-2.5-pro claude-3.7-sonnet openai deepseek gemini cursor etched skypilot agent-evals open-models model-releases model-performance coding multimodality model-deployment cost-efficiency agent-evaluation privacy kevinweil sama lmarena_ai scaling01 iscienceluvr stevenheidel lepikhin dzhng raizamrtn karpathy
OpenAI is preparing to release a highly capable open language model, their first since GPT-2, with a focus on reasoning and community feedback, as shared by @kevinweil and @sama. DeepSeek V3 0324 has achieved the #5 spot on the Arena leaderboard, becoming the top open model with an MIT license and cost advantages. Gemini 2.5 Pro is noted for outperforming models like Claude 3.7 Sonnet in coding tasks, with upcoming pricing and improvements expected soon. New startups like Sophont are building open multimodal foundation models for healthcare. Significant fundraises include Cursor closing $625M at a $9.6B valuation and Etched raising $85M at $1.5B. Innovations in AI infrastructure include SkyPilot's cost-efficient cloud provisioning and the launch of AgentEvals, an open-source package for evaluating AI agents. Discussions on smartphone privacy highlight iPhone's stronger user defense compared to Android.
not much happened today
gpt-4o deepseek-v3-0324 gemini-2.5-pro gemini-3 claude-3.7-sonnet openai hugging-face sambanova google-cloud instruction-following image-generation content-filtering model-performance api coding model-deployment benchmarking model-release abacaj nrehiew_ sama joannejang giffmana lmarena_ai _philschmid
OpenAI announced the new GPT-4o model with enhanced instruction-following, complex problem-solving, and native image generation capabilities. The model shows improved performance in math, coding, and creativity, with features like transparent background image generation. Discussions around content filtering and policy for image generation emphasize balancing creative freedom and harm prevention. DeepSeek V3-0324 APIs, available on Hugging Face and powered by SambaNovaAI, outperform benchmarks and models like Gemini 2.0 Pro and Claude 3.7 Sonnet. Gemini 2.5 Pro is recommended for coding, and Gemini 3 can be deployed easily on Google Cloud Vertex AI via the new Model Garden SDK. The Gemma 3 Technical Report has been released on arXiv.
OpenAI adopts MCP
gemini-2.5-pro gemini-1.5-pro gemini-2.0-flash qwen-2.5-omni-7b deepseek-v3-0324 deepseek-r1 openai google-deepmind alibaba togethercompute model-benchmarking multimodality reasoning scaling-laws model-quantization synthetic-data model-performance context-windows speech-recognition translation audio-processing video-processing swyx
OpenAI announced support for MCP, a significant technical update. Google's Gemini 2.5 Pro leads benchmarks with top scores in MMLU-Pro (86%), GPQA Diamond (83%), and AIME 2024 (88%), featuring a 1 million token context window and multimodal inputs. Alibaba's Qwen 2.5 Omni 7B was released as a fully multimodal, interactive, open-source model with a novel "thinker-talker" architecture supporting voice and video chat. DeepSeek V3-0324 outperforms its predecessor on multiple benchmarks. Research on reasoning features in large language models using sparse autoencoders was highlighted, alongside a study on scaling laws of synthetic data showing performance plateaus near 300B tokens. Discussions also covered the fastest output speeds of Gemini models and concerns about over-reliance on benchmarks for intelligence measurement. Swyx will curate the Data Council AI Engineering Track in April.
Halfmoon is Reve Image: a new SOTA Image Model from ex-Adobe/Stability trio
deepseek-v3-0324 qwen-2.5-vl-32b-instruct recraft artificial-analysis stability-ai adobe deepseek alibaba text-to-image prompt-understanding model-composition visual-generation language-understanding model-performance complex-prompting iterative-generation christian-cantrell taesung-park michael-gharbi
Reve, a new composite AI model from former Adobe and Stability alums Christian Cantrell, Taesung Park, and Michaël Gharbi, has emerged as the top-rated image generation model, surpassing previous state-of-the-art models like Recraft and Ideogram in text rendering and typography. The team emphasizes "enhancing visual generative models with logic" and "understanding user intent with advanced language capabilities" to iteratively amend visuals based on natural language input. Additionally, DeepSeek-V3-0324 and Alibaba's Qwen2.5-VL-32B-Instruct models were released with notable performance improvements, including better vision task benchmarks and mathematical reasoning.
Promptable Prosody, SOTA ASR, and Semantic VAD: OpenAI revamps Voice AI
gpt-4o-transcribe gpt-4o-mini-tts o1-pro kokoro-82m openai replicate speech-to-text text-to-speech voice-activity-detection prompt-engineering real-time-processing model-release api function-calling structured-outputs model-performance juberti sama reach_vb kevinweil omarsar0
OpenAI has launched three new state-of-the-art audio models in their API, including gpt-4o-transcribe, a speech-to-text model outperforming Whisper, and gpt-4o-mini-tts, a text-to-speech model with promptable prosody allowing control over timing and emotion. The Agents SDK now supports audio, enabling voice agents. OpenAI also updated turn detection for real-time voice activity detection (VAD) based on speech content. Additionally, OpenAI's o1-pro model is available to select developers with advanced features like vision and function calling, though at higher compute costs. The community shows strong enthusiasm for these audio advancements, with a radio contest for TTS creations underway. Meanwhile, Kokoro-82M v1.0 emerges as a leading open weights TTS model with competitive pricing on Replicate.
Cohere's Command A claims #3 open model spot (after DeepSeek and Gemma)
command-a mistral-ai-small-3.1 smoldocling qwen-2.5-vl cohere mistral-ai hugging-face context-windows multilinguality multimodality fine-tuning benchmarking ocr model-performance model-releases model-optimization aidangomez sophiamyang mervenoyann aidan_mclau reach_vb lateinteraction
Cohere's Command A model has solidified its position on the LMArena leaderboard, featuring an open-weight 111B parameter model with an unusually long 256K context window and competitive pricing. Mistral AI released the lightweight, multilingual, and multimodal Mistral AI Small 3.1 model, optimized for single RTX 4090 or Mac 32GB RAM setups, with strong performance on instruct and multimodal benchmarks. The new OCR model SmolDocling offers fast document reading with low VRAM usage, outperforming larger models like Qwen2.5VL. Discussions highlight the importance of system-level improvements over raw LLM advancements, and MCBench is recommended as a superior AI benchmark for evaluating model capabilities across code, aesthetics, and awareness.
not much happened today
gemini-2.0-flash-thinking command-a qwq-32b gemma-3-27b gemma-3 shieldgemma-2 llama-3-70b deepseek-r1 o1-mini deepseek-v3 google-deepmind cohere meta-ai-fair alibaba hugging-face model-updates model-performance benchmarking reinforcement-learning transformers normalization-layers image-generation vision memory-efficiency context-windows fine-tuning yann-lecun
Google DeepMind announced updates to Gemini 2.0, including an upgraded Flash Thinking model with stronger reasoning and native image generation capabilities. Cohere launched Command A, a 111B parameter dense model with a 256K context window and competitive pricing, available on Hugging Face. Meta AI proposed Dynamic Tanh (DyT) as a replacement for normalization layers in Transformers, supported by Yann LeCun. Alibaba released QwQ-32B, a 32.5B parameter model excelling in math and coding, fine-tuned with reinforcement learning and freely available under Apache 2.0 license. Google DeepMind also released Gemma 3 models ranging from 1B to 27B parameters with a 128K token context window and over 140 language support, plus ShieldGemma 2, an image safety checker. Benchmarking shows Gemma 3 27B has strong vision and memory efficiency but is outperformed by larger models like Llama 3.3 70B and DeepSeek V3 671B. The Hugging Face LLM leaderboard history was shared by @_lewtun.
Gemma 3 beats DeepSeek V3 in Elo, 2.0 Flash beats GPT4o with Native Image Gen
gemma-3 gemini-1.5-pro gemini-2 o1-preview o3-mini-high deepseek-v3 claude-3.7-sonnet qwen-2.5-max google-deepmind openai multimodality multilinguality context-window quantization image-generation model-benchmarking model-performance vision reach_vb _philschmid danielhanchen lmarena_ai osanseviero
Google DeepMind launched the Gemma 3 family of models featuring a 128k context window, multimodal input (image and video), and multilingual support for 140+ languages. The Gemma 3-27B model ranks among the top open models on LMArena benchmarks, outperforming several competitors and matching Gemini-1.5-Pro on benchmarks. Additionally, Gemini 2 introduced Flash Native Image Generation with advanced image editing capabilities, a feature teased by OpenAI but not launched. The updates highlight significant advances in context length, multimodality, and model efficiency via quantization.
DeepSeek's Open Source Stack
qwen-qwq-32b start character-3 gemini gemini-2.0 mercury-coder gpt-4.5 jamba-mini-1.6 gemini-2.0-flash gpt-4o-mini mistral-small-3 mistral-ocr deepseek pyspur hugging-face togethercompute hedra-labs google-deepmind deeplearningai openai ai21-labs mistral-ai fine-tuning benchmarking multimodality code-generation diffusion-models model-performance model-optimization ocr embedding-models context-windows runtime-limits _akhaliq lmarena_ai reach_vb danielhanchen _philschmid aidan_mclau vikhyatk jerryjliu0
DeepSeek's Open Source Week was summarized by PySpur, highlighting multiple interesting releases. The Qwen QwQ-32B model was fine-tuned into START, excelling in PhD-level science QA and math benchmarks. Character-3, an omnimodal AI video generation model by Hedra Labs and Together AI, enables realistic animated content creation. Google DeepMind introduced the Gemini embedding model with an 8k context window, ranking #1 on MMTEB, alongside the Gemini 2.0 Code Executor supporting Python libraries and auto-fix features. Inception Labs' Mercury Coder is a diffusion-based code generation model offering faster token processing. OpenAI released GPT-4.5, their largest model yet but with less reasoning ability than some competitors. AI21 Labs launched Jamba Mini 1.6, noted for superior output speed compared to Gemini 2.0 Flash, GPT-4o mini, and Mistral Small 3. A new dataset of 1.9M scanned pages was released for OCR benchmarking, with Mistral OCR showing competitive but not top-tier document parsing performance compared to LLM/LVM-powered methods. "Cracked engineers are all you need."
not much happened today
aya-vision-8b aya-vision-32b llama-3-2-90b-vision molmo-72b phi-4-mini phi-4-multimodal cogview4 wan-2-1 weights-and-biases coreweave cohereforai microsoft alibaba google llamaindex weaviate multilinguality vision multimodality image-generation video-generation model-releases benchmarking funding agentic-ai model-performance mervenoyann reach_vb jayalammar sarahookr aidangomez nickfrosst dair_ai akhaliq bobvanluijt jerryjliu0
Weights and Biases announced a $1.7 billion acquisition by CoreWeave ahead of CoreWeave's IPO. CohereForAI released the Aya Vision models (8B and 32B parameters) supporting 23 languages, outperforming larger models like Llama-3.2 90B Vision and Molmo 72B. Microsoft introduced Phi-4-Mini (3.8B parameters) and Phi-4-Multimodal models, excelling in math, coding, and multimodal benchmarks. CogView4, a 6B parameter text-to-image model with 2048x2048 resolution and Apache 2.0 license, was released. Alibaba launched Wan 2.1, an open-source video generation model with 720p output and 16 fps generation. Google announced new AI features for Pixel devices including Scam Detection and Gemini integrations. LlamaCloud reached General Availability and raised $19M Series A funding, serving over 100 Fortune 500 companies. Weaviate launched the Query Agent, the first of three Weaviate Agents.
Anthropic's $61.5B Series E
gpt-4.5 claude-3.7-sonnet deepseek-r1 anthropic openai deepseek lmsys perplexity-ai deutsche-telekom model-performance benchmarking style-control coding multi-turn funding partnerships workflow lmarena_ai teortaxestex casper_hansen_ omarsar0 aidan_mclau willdepue vikhyatk teknim1 reach_vb _aidan_clark_ cto_junior aravsrinivas
Anthropic raised a $3.5 billion Series E funding round at a $61.5 billion valuation, signaling strong financial backing for the Claude AI model. GPT-4.5 achieved #1 rank across all categories on the LMArena leaderboard, excelling in multi-turn conversations, coding, math, creative writing, and style control. DeepSeek R1 tied with GPT-4.5 for top performance on hard prompts with style control. Discussions highlighted comparisons between GPT-4.5 and Claude 3.7 Sonnet in coding and workflow applications. The importance of the LMSYS benchmark was emphasized, though some questioned the relevance of benchmarks versus user acquisition. Additionally, Perplexity AI partnered with Deutsche Telekom to integrate the Perplexity Assistant into a new AI phone.
not much happened today
gpt-4.5 gpt-4 gpt-4o o1 claude-3.5-sonnet claude-3.7 claude-3-opus deepseek-v3 grok-3 openai anthropic perplexity-ai deepseek scaling01 model-performance humor emotional-intelligence model-comparison pricing context-windows model-size user-experience andrej-karpathy jeremyphoward abacaj stevenheidel yuchenj_uw aravsrinivas dylan522p random_walker
GPT-4.5 sparked mixed reactions on Twitter, with @karpathy noting users preferred GPT-4 in a poll despite his personal favor for GPT-4.5's creativity and humor. Critics like @abacaj highlighted GPT-4.5's slowness and questioned its practical value and pricing compared to other models. Performance-wise, GPT-4.5 ranks above GPT-4o but below o1 and Claude 3.5 Sonnet, with Claude 3.7 outperforming it on many tasks yet GPT-4.5 praised for its humor and "vibes." Speculation about GPT-4.5's size suggests around 5 trillion parameters. Discussions also touched on pricing disparities, with Perplexity Deep Research at $20/month versus ChatGPT at $200/month. The emotional intelligence and humor of models like Claude 3.7 were also noted.
lots of small launches
gpt-4o claude-3.7-sonnet claude-3.7 claude-3.5-sonnet deepseek-r1 deepseek-v3 grok-3 openai anthropic amazon cloudflare perplexity-ai deepseek-ai togethercompute elevenlabs elicitorg inceptionailabs mistral-ai voice model-releases cuda gpu-optimization inference open-source api model-performance token-efficiency context-windows cuda jit-compilation lmarena_ai alexalbert__ aravsrinivas reach_vb
GPT-4o Advanced Voice Preview is now available for free ChatGPT users with enhanced daily limits for Plus and Pro users. Claude 3.7 Sonnet has achieved the top rank in WebDev Arena with improved token efficiency. DeepSeek-R1 with 671B parameters benefits from the Together Inference platform optimizing NVIDIA Blackwell GPU usage, alongside the open-source DeepGEMM CUDA library delivering up to 2.7x speedups on Hopper GPUs. Perplexity launched a new Voice Mode and a Deep Research API. The upcoming Grok 3 API will support a 1M token context window. Several companies including Elicit, Amazon, Anthropic, Cloudflare, FLORA, Elevenlabs, and Inception Labs announced new funding rounds, product launches, and model releases.
not much happened today
claude-3.7-sonnet claude-3.7 deepseek-r1 o3-mini deepseek-v3 gemini-2.0-pro gpt-4o qwen2.5-coder-32b-instruct anthropic perplexity-ai amazon google-cloud deepseek_ai coding reasoning model-benchmarking agentic-workflows context-window model-performance open-source moe model-training communication-libraries fp8 nvlink rdma cli-tools skirano omarsar0 reach_vb artificialanlys terryyuezhuo _akhaliq _philschmid catherineols goodside danielhanchen
Claude 3.7 Sonnet demonstrates exceptional coding and reasoning capabilities, outperforming models like DeepSeek R1, O3-mini, and GPT-4o on benchmarks such as SciCode and LiveCodeBench. It is available on platforms including Perplexity Pro, Anthropic, Amazon Bedrock, and Google Cloud, with pricing at $3/$15 per million tokens. Key features include a 64k token thinking mode, 200k context window, and the CLI-based coding assistant Claude Code. Meanwhile, DeepSeek released DeepEP, an open-source communication library optimized for MoE model training and inference with support for NVLink, RDMA, and FP8. These updates highlight advancements in coding AI and efficient model training infrastructure.
AI Engineer Summit Day 1
grok-3 o3-mini deepseek-r1 qwen-2.5-vl openai anthropic xai togethercompute alibaba sakana-ai benchmarking model-performance cuda model-training open-source debugging inference-speed batch-size reinforcement-learning aidan_mclau giffmana nrehiew_ teortaxestex epochairesearch andrew_n_carr borismpower yuhu_ai_
The AIE Summit in NYC highlighted key talks including Grace Isford's Trends Keynote, Neo4j/Pfizer's presentation, and OpenAI's first definition of Agents. Speakers announced $930 million in funding. On AI Twitter, discussions focused on Grok-3 and o3-mini models, with debates on performance and benchmarking, including Grok-3's record compute scale of 4e26 to 5e26 FLOP. The o3-mini model uncovered a critical CUDA kernel bug in Sakana AI's code. DeepSeek-R1 was promoted as an open-source alternative with notable training batch sizes. Additionally, Alibaba announced the Qwen 2.5-VL model release.
X.ai Grok 3 and Mira Murati's Thinking Machines
grok-3 grok-3-mini gemini-2-pro gpt-4o o3-mini-high o1 deepseek-r1 anthropic openai thinking-machines benchmarking reasoning reinforcement-learning coding multimodality safety alignment research-publishing model-performance creative-ai mira-murati lmarena_ai karpathy omarsar0 ibab arankomatsuzaki iscienceluvr scaling01
Grok 3 has launched with mixed opinions but strong benchmark performance, notably outperforming models like Gemini 2 Pro and GPT-4o. The Grok-3 mini variant shows competitive and sometimes superior capabilities, especially in reasoning and coding, with reinforcement learning playing a key role. Mira Murati has publicly shared her post-OpenAI plan, founding the frontier lab Thinking Machines, focusing on collaborative, personalizable AI, multimodality, and empirical safety and alignment research, reminiscent of Anthropic's approach.
not much happened today
chatgpt-4o deepseek-r1 o3 o3-mini gemini-2-flash qwen-2.5 qwen-0.5b hugging-face openai perplexity-ai deepseek-ai gemini qwen metr_evals reasoning benchmarking model-performance prompt-engineering model-optimization model-deployment small-language-models mobile-ai ai-agents speed-optimization _akhaliq aravsrinivas lmarena_ai omarsar0 risingsayak
Smolagents library by Huggingface continues trending. ChatGPT-4o latest version
chatgpt-40-latest-20250129 released. DeepSeek R1 671B sets speed record at 198 t/s, fastest reasoning model, recommended with specific prompt settings. Perplexity Deep Research outperforms models like Gemini Thinking, o3-mini, and DeepSeek-R1 on Humanity's Last Exam benchmark with 21.1% score and 93.9% accuracy on SimpleQA. ChatGPT-4o ranks #1 on Arena leaderboard in multiple categories except math. OpenAI's o3 model powers Deep Research tool for ChatGPT Pro users. Gemini 2 Flash and Qwen 2.5 models support LLMGrading verifier. Qwen 2.5 models added to PocketPal app. MLX shows small LLMs like Qwen 0.5B generate tokens at high speed on M4 Max and iPhone 16 Pro. Gemini Flash 2.0 leads new AI agent leaderboard. DeepSeek R1 is most liked on Hugging Face with over 10 million downloads. small news items
gpt-4.5 gpt-5 deepseek-r1-distilled-qwen-1.5b o1-preview modernbert-0.3b qwen-0.5b o3 openai ollama mistral perplexity cerebras alibaba groq bytedance math benchmarking fine-tuning model-performance reinforcement-learning model-architecture partnerships funding jeremyphoward arankomatsuzaki sama nrehiew_ danhendrycks akhaliq
OpenAI announced plans for GPT-4.5 (Orion) and GPT-5, with GPT-5 integrating the o3 model and offering unlimited chat access in the free tier. DeepSeek R1 Distilled Qwen 1.5B outperforms OpenAI's o1-preview on math benchmarks, while ModernBERT 0.3b surpasses Qwen 0.5b at MMLU without fine-tuning. Mistral and Perplexity adopt Cerebras hardware for 10x performance gains. OpenAI's o3 model won a gold medal at the 2024 International Olympiad in Informatics. Partnerships include Qwen with Groq. Significant RLHF activity is noted in Nigeria and the global south, and Bytedance is expected to rise in AI prominence soon. "GPT5 is all you need."
not much happened today
zonos-v0.1 audiobox-aesthetics moshi sonar llama-3-70b gpt-4o-mini claude-3.5-haiku gpt-4o claude-3.5-sonnet deepseek-r1-distilled-qwen-1.5b reasonflux-32b o1-preview zyphra-ai meta-ai-fair kyutai-labs perplexity-ai cerebras uc-berkeley brilliant-labs google-deepmind text-to-speech speech-to-speech benchmarking model-performance reinforcement-learning math real-time-processing open-source cross-platform-integration multilinguality zero-shot-learning danhendrycks
Zyphra AI launched Zonos-v0.1, a leading open-weight text-to-speech model supporting multiple languages and zero-shot voice cloning. Meta FAIR released the open-source Audiobox Aesthetics model trained on 562 hours of audio data. Kyutai Labs introduced Moshi, a real-time speech-to-speech system with low latency. Perplexity AI announced the Sonar model based on Llama 3.3 70b, outperforming top models like GPT-4o and Claude 3.5 Sonnet with 1200 tokens/second speed, powered by Cerebras infrastructure. UC Berkeley open-sourced a 1.5B model trained with reinforcement learning that beats o1-preview on math tasks. ReasonFlux-32B achieved 91.2% on the MATH benchmark, outperforming OpenAI o1-preview. CrossPoster, an AI agent for cross-platform posting, was released using LlamaIndex workflows. Brilliant Labs integrated the Google DeepMind Gemini Live API into smart glasses for real-time translation and object identification.
not much happened today
gemini-2.0-flash-thinking-experimental-1-21 zonos openr1-math-220k huginn-3.5b deepseek-r1 o1 claude google zyphraai hugging-face anthropic deepseek openai vision multilingual-models text-to-speech voice-cloning math reasoning latent-reasoning chain-of-thought dataset-release fine-tuning model-training model-performance context-windows benchmarking jeremyphoward andrej-karpathy tom-goldstein reach_vb iscienceluvr
Google released Gemini 2.0 Flash Thinking Experimental 1-21, a vision-language reasoning model with a 1 million-token context window and improved accuracy on science, math, and multimedia benchmarks, surpassing DeepSeek-R1 but trailing OpenAI's o1. ZyphraAI launched Zonos, a multilingual Text-to-Speech model with instant voice cloning and controls for speaking rate, pitch, and emotions, running at ~2x real-time speed on RTX 4090. Hugging Face released OpenR1-Math-220k, a large-scale math reasoning dataset with 220K problems and 800K reasoning traces generated on 512 H100 GPUs. Tom Goldstein introduced Huginn-3.5B, an open-source latent reasoning model trained on 800B tokens that outperforms larger models on reasoning tasks like GSM8K. Discussions by Jeremy Howard and iScienceLuvr highlight advances in implicit latent reasoning and debate the future of human-readable reasoning traces. Anthropic launched the Anthropic Economic Index to analyze AI's economic impact using millions of Claude conversations.
OpenAI takes on Gemini's Deep Research
o3 o3-mini-high o3-deep-research-mini openai google-deepmind nyu uc-berkeley hku reinforcement-learning benchmarking inference-speed model-performance reasoning test-time-scaling agent-design sama danhendrycks ethan-mollick dan-shipper
OpenAI released the full version of the o3 agent, with a new Deep Research variant showing significant improvements on the HLE benchmark and achieving SOTA results on GAIA. The release includes an "inference time scaling" chart demonstrating rigorous research, though some criticism arose over public test set results. The agent is noted as "extremely simple" and currently limited to 100 queries/month, with plans for a higher-rate version. Reception has been mostly positive, with some skepticism. Additionally, advances in reinforcement learning were highlighted, including a simple test-time scaling technique called budget forcing that improved reasoning on math competitions by 27%. Researchers from Google DeepMind, NYU, UC Berkeley, and HKU contributed to these findings. The original Gemini Deep Research team will participate in the upcoming AI Engineer NYC event.
o3-mini launches, OpenAI on "wrong side of history"
o3-mini o1 gpt-4o mistral-small-3-24b deepseek-r1 openai mistral-ai deepseek togethercompute fireworksai_hq ai-gradio replicate reasoning safety cost-efficiency model-performance benchmarking api open-weight-models model-releases sam-altman
OpenAI released o3-mini, a new reasoning model available for free and paid users with a "high" reasoning effort option that outperforms the earlier o1 model on STEM tasks and safety benchmarks, costing 93% less per token. Sam Altman acknowledged a shift in open source strategy and credited DeepSeek R1 for influencing assumptions. MistralAI launched Mistral Small 3 (24B), an open-weight model with competitive performance and low API costs. DeepSeek R1 is supported by Text-generation-inference v3.1.0 and available via ai-gradio and replicate. The news highlights advancements in reasoning, cost-efficiency, and safety in AI models.
Mistral Small 3 24B and Tulu 3 405B
mistral-small-3 tulu-3-405b llama-3 tiny-swallow-1.5b qwen-2.5-max deepseek-v3 claude-3.5-sonnet gemini-1.5-pro gpt4o-mini llama-3-3-70b mistral-ai ai2 sakana-ai alibaba_qwen deepseek ollama llamaindex reinforcement-learning model-fine-tuning local-inference model-performance model-optimization on-device-ai instruction-following api training-data natural-language-processing clementdelangue dchaplot reach_vb
Mistral AI released Mistral Small 3, a 24B parameter model optimized for local inference with low latency and 81% accuracy on MMLU, competing with Llama 3.3 70B, Qwen-2.5 32B, and GPT4o-mini. AI2 released Tülu 3 405B, a large finetuned model of Llama 3 using Reinforcement Learning from Verifiable Rewards (RVLR), competitive with DeepSeek v3. Sakana AI launched TinySwallow-1.5B, a Japanese language model using TAID for on-device use. Alibaba_Qwen released Qwen 2.5 Max, trained on 20 trillion tokens, with performance comparable to DeepSeek V3, Claude 3.5 Sonnet, and Gemini 1.5 Pro, and updated API pricing. These releases highlight advances in open models, efficient inference, and reinforcement learning techniques.
TinyZero: Reproduce DeepSeek R1-Zero for $30
deepseek-r1 qwen o1 claude-3-sonnet claude-3 prime ppo grpo llama-stack deepseek berkeley hugging-face meta-ai-fair openai deeplearningai reinforcement-learning fine-tuning chain-of-thought multi-modal-benchmark memory-management model-training open-source agentic-workflow-automation model-performance jiayi-pan saranormous reach_vb lmarena_ai nearcyan omarsar0 philschmid hardmaru awnihannun winglian
DeepSeek Mania continues to reshape the frontier model landscape with Jiayi Pan from Berkeley reproducing the OTHER result from the DeepSeek R1 paper, R1-Zero, in a cost-effective Qwen model fine-tune for two math tasks. A key finding is a lower bound to the distillation effect at 1.5B parameters, with RLCoT reasoning emerging as an intrinsic property. Various RL techniques like PPO, DeepSeek's GRPO, or PRIME show similar outcomes, and starting from an Instruct model speeds convergence. The Humanity’s Last Exam (HLE) Benchmark introduces a challenging multi-modal test with 3,000 expert-level questions across 100+ subjects, where models perform below 10%, with DeepSeek-R1 achieving 9.4%. DeepSeek-R1 excels in chain-of-thought reasoning, outperforming models like o1 while being 20x cheaper and MIT licensed. The WebDev Arena Leaderboard ranks DeepSeek-R1 #2 in technical domains and #1 under Style Control, closing in on Claude 3.5 Sonnet. OpenAI's Operator is deployed to 100% of Pro users in the US, enabling tasks like ordering meals and booking reservations, and functions as a research assistant for AI paper searches and summaries. Hugging Face announces a leadership change after significant growth, while Meta AI releases the first stable version of Llama Stack with streamlined upgrades and automated verification. DeepSeek-R1's open-source success is celebrated, and technical challenges like memory management on macOS 15+ are addressed with residency sets in MLX for stability.
Project Stargate: $500b datacenter (1.7% of US GDP) and Gemini 2 Flash Thinking 2
gemini-2.0-flash deepseek-r1 qwen-32b openai softbank oracle arm microsoft nvidia huggingface deepseek-ai long-context quantization code-interpretation model-distillation open-source agi-research model-performance memory-optimization noam-shazeer liang-wenfeng
Project Stargate, a US "AI Manhattan project" led by OpenAI and Softbank, supported by Oracle, Arm, Microsoft, and NVIDIA, was announced with a scale comparable to the original Manhattan project costing $35B inflation adjusted. Despite Microsoft's reduced role as exclusive compute partner, the project is serious but not immediately practical. Meanwhile, Noam Shazeer revealed a second major update to Gemini 2.0 Flash Thinking, enabling 1M token long context usable immediately. Additionally, AI Studio introduced a new code interpreter feature. On Reddit, DeepSeek R1, a distillation of Qwen 32B, was released for free on HuggingChat, sparking discussions on self-hosting, performance issues, and quantization techniques. DeepSeek's CEO Liang Wenfeng highlighted their focus on fundamental AGI research, efficient MLA architecture, and commitment to open-source development despite export restrictions, positioning DeepSeek as a potential alternative to closed-source AI trends.
not much happened today
helium-1 qwen-2.5 phi-4 sky-t1-32b-preview o1 codestral-25.01 phi-3 mistral llama-3 gpt-3.5 llama-3 gpt-3.5 llmquoter kyutai-labs lmstudio mistralai llamaindex huggingface langchainai hyperbolic-labs replit fchollet philschmid multilinguality token-level-distillation context-windows model-performance open-source reasoning coding retrieval-augmented-generation hybrid-retrieval multiagent-systems video large-video-language-models dynamic-ui voice-interaction gpu-rentals model-optimization semantic-deduplication model-inference reach_vb awnihannun lior_on_ai sophiamyang omarsar0 skirano yuchenj_uw fchollet philschmid
Helium-1 Preview by kyutai_labs is a 2B-parameter multilingual base LLM outperforming Qwen 2.5, trained on 2.5T tokens with a 4096 context size using token-level distillation from a 7B model. Phi-4 (4-bit) was released in lmstudio on an M4 max, noted for speed and performance. Sky-T1-32B-Preview is a $450 open-source reasoning model matching o1's performance with strong benchmark scores. Codestral 25.01 by mistralai is a new SOTA coding model supporting 80+ programming languages and offering 2x speed.
Innovations include AutoRAG for optimizing retrieval-augmented generation pipelines, Agentic RAG for autonomous query reformulation and critique, Multiagent Finetuning using societies of models like Phi-3, Mistral, LLaMA-3, and GPT-3.5 for reasoning improvements, and VideoRAG incorporating video content into RAG with LVLMs.
Applications include a dynamic UI AI chat app by skirano on Replit, LangChain tools like DocTalk for voice PDF conversations, AI travel agent tutorials, and news summarization agents. Hyperbolic Labs offers competitive GPU rentals including H100, A100, and RTX 4090. LLMQuoter enhances RAG accuracy by identifying key quotes.
Infrastructure updates include MLX export for LLM inference from Python to C++ by fchollet and SemHash semantic text deduplication by philschmid.
PRIME: Process Reinforcement through Implicit Rewards
claude-3.5-sonnet gpt-4o deepseek-v3 gemini-2.0 openai together-ai deepseek langchain lucidrains reinforcement-learning scaling-laws model-performance agent-architecture software-development compute-scaling multi-expert-models sama aidan_mclau omarsar0 akhaliq hwchase17 tom_doerr lmarena_ai cwolferesearch richardmcngo
Implicit Process Reward Models (PRIME) have been highlighted as a significant advancement in online reinforcement learning, trained on a 7B model with impressive results compared to gpt-4o. The approach builds on the importance of process reward models established by "Let's Verify Step By Step." Additionally, AI Twitter discussions cover topics such as proto-AGI capabilities with claude-3.5-sonnet, the role of compute scaling for Artificial Superintelligence (ASI), and model performance nuances. New AI tools like Gemini 2.0 coder mode and LangGraph Studio enhance agent architecture and software development. Industry events include the LangChain AI Agent Conference and meetups fostering AI community connections. Company updates reveal OpenAI's financial challenges with Pro subscriptions and DeepSeek-V3's integration with Together AI APIs, showcasing efficient 671B MoE parameter models. Research discussions focus on scaling laws and compute efficiency in large language models.
o3 solves AIME, GPQA, Codeforces, makes 11 years of progress in ARC-AGI and 25% in FrontierMath
o3 o3-mini o1-mini gpt-3 gpt-4o o1 openai benchmarking math reasoning model-performance inference-speed cost-efficiency alignment safety-testing sama eric-wallace
OpenAI announced the o3 and o3-mini models with groundbreaking benchmark results, including a jump from 2% to 25% on the FrontierMath benchmark and 87.5% on the ARC-AGI reasoning benchmark, representing about 11 years of progress on the GPT3 to GPT4o scaling curve. The o1-mini model shows superior inference efficiency compared to o3-full, promising significant cost reductions on coding tasks. The announcement was accompanied by community discussions, safety testing applications, and detailed analyses. Sama highlighted the unusual cost-performance tradeoff, and Eric Wallace shared insights on the o-series deliberative alignment strategy.
ModernBert: small new Retriever/Classifier workhorse, 8k context, 2T tokens,
modernbert gemini-2.0-flash-thinking o1 llama answerdotai lightonio hugging-face google-deepmind openai meta-ai-fair figure encoder-only-models long-context alternating-attention natural-language-understanding reasoning robotics-simulation physics-engine humanoid-robots model-performance model-releases jeremyphoward alec-radford philschmid drjimfan bindureddy
Answer.ai/LightOn released ModernBERT, an updated encoder-only model with 8k token context, trained on 2 trillion tokens including code, with 139M/395M parameters and state-of-the-art performance on retrieval, NLU, and code tasks. It features Alternating Attention layers mixing global and local attention. Gemini 2.0 Flash Thinking debuted as #1 in Chatbot Arena, and the O1 model scored top in reasoning benchmarks. Llama downloads surpassed 650 million, doubling in 3 months. OpenAI launched desktop app integrations with voice capabilities. Figure delivered its first humanoid robots commercially. Advances in robotics simulation and a new physics engine Genesis claiming 430,000x faster than real-time were highlighted.
o1 API, 4o/4o-mini in Realtime API + WebRTC, DPO Finetuning
o1-2024-12-17 o1 o1-pro 4o 4o-mini gemini-2-0-flash claude-3.5-sonnet claude-3.5 openai google google-deepmind function-calling structured-outputs vision reasoning webrtc realtime-api preference-tuning fine-tuning api model-performance aidan_mclau kevinweil simonw michpokrass morgymcg juberti
OpenAI launched the o1 API with enhanced features including vision inputs, function calling, structured outputs, and a new
reasoning_effort parameter, achieving 60% fewer reasoning tokens on average. The o1 pro variant is confirmed as a distinct implementation coming soon. Improvements to the Realtime API with WebRTC integration offer easier usage, longer sessions (up to 30 minutes), and significantly reduced pricing (up to 10x cheaper with mini models). DPO Preference Tuning for fine-tuning is introduced, currently available for the 4o model. Additional updates include official Go and Java SDKs and OpenAI DevDay videos. The news also highlights discussions on Google Gemini 2.0 Flash model's performance reaching 83.6% accuracy. Meta Llama 3.3: 405B/Nova Pro performance at 70B price
llama-3-70b llama-3.3-70b gpt-4o gemini-exp-1206 meta-ai-fair openai google-deepmind hugging-face llamacloud reinforcement-learning fine-tuning model-performance document-processing pricing-models alignment online-rl sama steven-heidel aidan_mclau lmarena_ai oriolvinyalsml jerryjliu0
Meta AI released Llama 3.3 70B, matching the performance of the 405B model with improved efficiency using "a new alignment process and progress in online RL techniques". OpenAI announced Reinforcement Fine-Tuning (RFT) for building expert models with limited data, offering alpha access to researchers and enterprises. Google DeepMind's Gemini-Exp-1206 leads benchmarks, tying with GPT-4o in coding performance. LlamaCloud enhanced document processing with table extraction and analytics. Discussions on OpenAI's pricing plans continue in the community.
$200 ChatGPT Pro and o1-full/pro, with vision, without API, and mixed reviews
o1 o1-pro claude-3.5-sonnet pali-gemma-2 openai google llamaindex multimodality vision fine-tuning benchmarking model-performance image-generation document-processing model-release sama bindureddy mervenoyann fchollet
OpenAI launched the o1 model with multimodal capabilities, faster reasoning, and image input support, marking it as a state-of-the-art model despite some bugs and mixed community reviews. The new o1-pro tier offers unlimited access for $200/month with notable benchmark improvements but some performance trade-offs compared to claude-3.5-sonnet. Google released the PaliGemma 2 vision-language model family in sizes 3B, 10B, and 28B, excelling in visual question answering, image segmentation, and OCR, with day-0 support for fine-tuning. LlamaIndex announced discounts and feature updates for large-scale document processing. The AI community also reacted humorously to the new pricing tiers and model comparisons. "o1 can see now, which makes it the SOTA multimodal model" and "most users will be best served by free/Plus tiers" were notable sentiments.
not much happened today
o1-full sora gpt-4.5 gpt-4 claude-3.5-sonnet llama-3-1-nemotron-51b llama-3-1 llama-3 nemotron-51b openai google-deepmind anthropic nvidia huggingface vision model-performance neural-architecture-search model-optimization multimodality model-release model-training reinforcement-learning image-generation lucas-beyer alexander-kolesnikov xiaohua-zhai aidan_mclau giffmana joannejang sama
OpenAI announced their "12 Days of OpenAI" event with daily livestreams and potential releases including the O1 full model, Sora video model, and GPT-4.5. Google DeepMind released the GenCast weather model capable of 15-day forecasts in 8 minutes using TPU chips, and launched Genie 2, a model generating playable 3D worlds from single images. Leading vision researchers Lucas Beyer, Alexander Kolesnikov, and Xiaohua Zhai moved from DeepMind to OpenAI, which is opening a Zürich office. Criticism arose over OpenAI's strategy and model quality compared to Anthropic and Claude 3.5 Sonnet. On Reddit, a modified llama.cpp supports Nvidia's Llama-3_1-Nemotron-51B, matching performance of larger 70B models via NAS optimization.
Olympus has dropped (aka, Amazon Nova Micro|Lite|Pro|Premier|Canvas|Reel)
amazon-nova claude-3 llama-3-70b gemini-1.5-flash gpt-4o amazon anthropic google-deepmind sakana-ai-labs multimodality benchmarking model-merging model-performance model-architecture model-optimization population-based-learning philschmid bindureddy
Amazon announced the Amazon Nova family of multimodal foundation models at AWS Re:Invent, available immediately with no waitlist in configurations like Micro, Lite, Pro, Canvas, and Reel, with Premier and speech-to-speech coming next year. These models offer 2-4x faster token speeds and are 25%-400% cheaper than competitors like Anthropic Claude models, positioning Nova as a serious contender in AI engineering. Pricing undercuts models such as Google DeepMind Gemini Flash 8B, and some Nova models extend context length up to 300k tokens. However, benchmarking controversy exists as some evaluations show Nova scoring below Llama-3 70B in LiveBench AI metrics. Separately, CycleQD was introduced by Sakana AI Labs, using evolutionary computation for population-based model merging to develop niche LLM agents.
DeepSeek-R1 claims to beat o1-preview AND will be open sourced
deepseek-r1-lite-preview o1-preview hopper blackwell alphaqubit deepseek nvidia google-deepmind reasoning benchmarking quantum-error-correction quantum-computing model-performance model-release yann-lecun
DeepSeek has released DeepSeek-R1-Lite-Preview, an open-source reasoning model achieving o1-preview-level performance on math benchmarks with transparent thought processes, showing promise in real-time problem-solving. NVIDIA reported a record $35.1 billion revenue in Q3 with 112% year-on-year data center growth, driven by Hopper and Blackwell architectures, the latter offering 2.2x performance improvement. Google DeepMind introduced AlphaQubit, a quantum computing system improving error correction and outperforming leading decoders, though challenges remain in scaling and speed. The AI community continues to focus on reasoning models, benchmarking, and quantum error correction advancements.
Perplexity starts Shopping for you
pixtral-large-124b llama-3.1-405b claude-3.6 claude-3.5 stripe perplexity-ai mistral-ai hugging-face cerebras anthropic weights-biases google vllm-project multi-modal image-generation inference context-windows model-performance model-efficiency sdk ai-integration one-click-checkout memory-optimization patrick-collison jeff-weinstein mervenoyann sophiamyang tim-dettmers omarsar0 akhaliq aravsrinivas
Stripe launched their Agent SDK, enabling AI-native shopping experiences like Perplexity Shopping for US Pro members, featuring one-click checkout and free shipping via the Perplexity Merchant Program. Mistral AI released the Pixtral Large 124B multi-modal image model, now on Hugging Face and supported by Le Chat for image generation. Cerebras Systems offers a public inference endpoint for Llama 3.1 405B with a 128k context window and high throughput. Claude 3.6 shows improvements over Claude 3.5 but with subtle hallucinations. The Bi-Mamba 1-bit architecture improves LLM efficiency. The wandb SDK is preinstalled on Google Colab, and Pixtral Large is integrated into AnyChat and supported by vLLM for efficient model usage.
BitNet was a lie?
qwen-2.5-coder-32b-instruct gpt-4o llama-3 sambanova alibaba hugging-face quantization scaling-laws model-efficiency fine-tuning model-performance code-generation open-source unit-testing ci-cd tanishq-kumar tim-dettmers
Scaling laws for quantization have been modified by a group led by Chris Re, analyzing over 465 pretraining runs and finding benefits plateau at FP6 precision. Lead author Tanishq Kumar highlights that longer training and more data increase sensitivity to quantization, explaining challenges with models like Llama-3. Tim Dettmers, author of QLoRA, warns that the era of efficiency gains from low-precision quantization is ending, signaling a shift from scaling to optimizing existing resources. Additionally, Alibaba announced Qwen 2.5-Coder-32B-Instruct, which matches or surpasses GPT-4o on coding benchmarks, and open-source initiatives like DeepEval for LLM testing are gaining traction.
not much happened today
smollm2 llama-3-2 stable-diffusion-3.5 claude-3.5-sonnet gemini openai anthropic google meta-ai-fair suno-ai perplexity-ai on-device-ai model-performance robotics multimodality ai-regulation model-releases natural-language-processing prompt-engineering agentic-ai ai-application model-optimization sam-altman akhaliq arav-srinivas labenz loubnabenallal1 alexalbert fchollet stasbekman svpino rohanpaul_ai hamelhusain
ChatGPT Search was launched by Sam Altman, who called it his favorite feature since ChatGPT's original launch, doubling his usage. Comparisons were made between ChatGPT Search and Perplexity with improvements noted in Perplexity's web navigation. Google introduced a "Grounding" feature in the Gemini API & AI Studio enabling Gemini models to access real-time web information. Despite Gemini's leaderboard performance, developer adoption lags behind OpenAI and Anthropic. SmolLM2, a new small, powerful on-device language model, outperforms Meta's Llama 3.2 1B. A Claude desktop app was released for Mac and Windows. Meta AI announced robotics advancements including Meta Sparsh, Meta Digit 360, and Meta Digit Plexus. Stable Diffusion 3.5 Medium, a 2B parameter model with a permissive license, was released. Insights on AGI development suggest initial inferiority but rapid improvement. Anthropic advocates for early targeted AI regulation. Discussions on ML specialization predict training will concentrate among few companies, while inference becomes commoditized. New AI tools include Suno AI Personas for music creation, PromptQL for natural language querying over data, and Agent S for desktop task automation. Humor was shared about Python environment upgrades.
Llama 3.2: On-device 1B/3B, and Multimodal 11B/90B (with AI2 Molmo kicker)
llama-3-2 llama-3-1 claude-3-haiku gpt-4o-mini molmo-72b molmo-7b gemma-2 phi-3-5 llama-3-2-vision llama-3-2-3b llama-3-2-20b meta-ai-fair ai2 qualcomm mediatek arm ollama together-ai fireworks-ai weights-biases cohere weaviate multimodality vision context-windows quantization model-release tokenization model-performance model-optimization rag model-training instruction-following mira-murati daniel-han
Meta released Llama 3.2 with new multimodal versions including 3B and 20B vision adapters on a frozen Llama 3.1, showing competitive performance against Claude Haiku and GPT-4o-mini. AI2 launched multimodal Molmo 72B and 7B models outperforming Llama 3.2 in vision tasks. Meta also introduced new 128k-context 1B and 3B models competing with Gemma 2 and Phi 3.5, with collaborations hinted with Qualcomm, Mediatek, and Arm for on-device AI. The release includes a 9 trillion token count for Llama 1B and 3B. Partner launches include Ollama, Together AI offering free 11B model access, and Fireworks AI. Additionally, a new RAG++ course from Weights & Biases, Cohere, and Weaviate offers systematic evaluation and deployment guidance for retrieval-augmented generation systems based on extensive production experience.
ChatGPT Advanced Voice Mode
o1-preview qwen-2.5 llama-3 claude-3.5 openai anthropic scale-ai togethercompute kyutai-labs voice-synthesis planning multilingual-datasets retrieval-augmented-generation open-source speech-assistants enterprise-ai price-cuts benchmarking model-performance sam-altman omarsar0 bindureddy rohanpaul_ai _philschmid alexandr_wang svpino ylecun _akhaliq
OpenAI rolled out ChatGPT Advanced Voice Mode with 5 new voices and improved accent and language support, available widely in the US. Ahead of rumored updates for Llama 3 and Claude 3.5, Gemini Pro saw a significant price cut aligning with the new intelligence frontier pricing. OpenAI's o1-preview model showed promising planning task performance with 52.8% accuracy on Randomized Mystery Blocksworld. Anthropic is rumored to release a new model, generating community excitement. Qwen 2.5 was released with models up to 32B parameters and support for 128K tokens, matching GPT-4 0613 benchmarks. Research highlights include PlanBench evaluation of o1-preview, OpenAI's release of a multilingual MMMLU dataset covering 14 languages, and RAGLAB framework standardizing Retrieval-Augmented Generation research. New AI tools include PDF2Audio for converting PDFs to audio, an open-source AI starter kit for local model deployment, and Moshi, a speech-based AI assistant from Kyutai. Industry updates feature Scale AI nearing $1B ARR with 4x YoY growth and Together Compute's enterprise platform offering faster inference and cost reductions. Insights from Sam Altman's blog post were also shared.
a calm before the storm
o1 o1-mini qwen2.5 gpt-4 llama-2-70b llama-7b anthropic openai alibaba microsoft blackrock groq aramco disney eth-zurich pudu-robotics slack long-context kv-cache-quantization diffusion-models reinforcement-learning robotics ai-integration multilinguality model-benchmarking model-performance model-optimization adcock_brett philschmid rohanpaul_ai jvnixon kateclarktweets sama
Anthropic is raising funds at a valuation up to $40 billion ahead of anticipated major releases. OpenAI launched new reasoning models o1 and o1-mini, with increased rate limits and a multilingual MMLU benchmark. Alibaba released the open-source Qwen2.5 model supporting 29+ languages, showing competitive performance to gpt-4 at lower cost. Microsoft and Blackrock plan to invest $30 billion in AI data centers, with Groq partnering with Aramco to build the world's largest AI inference center. Robotics advances include Disney Research and ETH Zurich's diffusion-based motion generation for robots and Pudu Robotics' semi-humanoid robot. Slack and Microsoft introduced AI-powered agents integrated into their platforms. Research highlights include long-context scaling for llama-2-70b using Dual Chunk Attention and KV cache quantization enabling 1 million token context on llama-7b models.
o1 destroys Lmsys Arena, Qwen 2.5, Kyutai Moshi release
o1-preview o1-mini qwen-2.5 qwen-plus llama-3-1 deepseek-v2.5 openai anthropic google alibaba deepseek kyutai weights-biases mistral-ai chain-of-thought multimodality model-benchmarking model-performance streaming-neural-architecture llm-observability experiment-tracking rate-limiting sama guillaumelample
OpenAI's o1-preview model has achieved a milestone by fully matching top daily AI news stories without human intervention, consistently outperforming other models like Anthropic, Google, and Llama 3 in vibe check evaluations. OpenAI models dominate the top 4 slots on LMsys benchmarks, with rate limits increasing to 500-1000 requests per minute. In open source, Alibaba's Qwen 2.5 suite surpasses Llama 3.1 at the 70B scale and updates its closed Qwen-Plus models to outperform DeepSeek V2.5 but still lag behind leading American models. Kyutai Moshi released its open weights realtime voice model featuring a unique streaming neural architecture with an "inner monologue." Weights & Biases introduced Weave, an LLM observability toolkit that enhances experiment tracking and evaluation, turning prompting into a more scientific process. The news also highlights upcoming events like the WandB LLM-as-judge hackathon in San Francisco. "o1-preview consistently beats out our vibe check evals" and "OpenAI models are gradually raising rate limits by the day."
Learnings from o1 AMA
o1-preview o1-mini claude-3.5-sonnet gpt-4o openai weights-biases cohere weaviate reinforcement-learning chain-of-thought reasoning model-performance prompting code-editing rag hybrid-search sama rohanpaul_ai gdb andrew-mayne
OpenAI released the o1 model series, touted as their "most capable and aligned models yet," trained with reinforcement learning to enhance reasoning. The o1-preview model scored 21% on ARC-AGI, ~80% on aider code editing (surpassing Claude 3.5 Sonnet's 77%), and ~52% on Cognition-Golden, showcasing a shift from memorizing answers to memorizing reasoning. The model employs a unique chain-of-thought approach enabling "System II thinking" for better problem-solving. Experts like Andrew Mayne advise framing o1 as a smart friend providing thoughtful explanations. Additionally, an advanced RAG course sponsored by Weights & Biases, Cohere, and Weaviate offers strategies for hybrid search and prompting to optimize AI solutions.
o1: OpenAI's new general reasoning models
o1 o1-preview o1-mini gpt-4o llama openai nvidia test-time-reasoning reasoning-tokens token-limit competitive-programming benchmarking scaling-laws ai-chip-competition inference training model-performance jason-wei jim-fan
OpenAI has released the o1 model family, including o1-preview and o1-mini, focusing on test-time reasoning with extended output token limits over 30k tokens. The models show strong performance, ranking in the 89th percentile on competitive programming, excelling in USA Math Olympiad qualifiers, and surpassing PhD-level accuracy on physics, biology, and chemistry benchmarks. Notably, o1-mini performs impressively despite its smaller size compared to gpt-4o. The release highlights new scaling laws for test-time compute that scale loglinearly. Additionally, Nvidia is reportedly losing AI chip market share to startups, with a shift in developer preference from CUDA to llama models for web development, though Nvidia remains dominant in training. This news reflects significant advances in reasoning-focused models and shifts in AI hardware competition.
Pixtral 12B: Mistral beats Llama to Multimodality
pixtral-12b mistral-nemo-12b llama-3-1-70b llama-3-1-8b deeps-eek-v2-5 gpt-4-turbo llama-3-1 strawberry claude mistral-ai meta-ai-fair hugging-face arcee-ai deepseek-ai openai anthropic vision multimodality ocr benchmarking model-release model-architecture model-performance fine-tuning model-deployment reasoning code-generation api access-control reach_vb devendra_chapilot _philschmid rohanpaul_ai
Mistral AI released Pixtral 12B, an open-weights vision-language model with a Mistral Nemo 12B text backbone and a 400M vision adapter, featuring a large vocabulary of 131,072 tokens and support for 1024x1024 pixel images. This release notably beat Meta AI in launching an open multimodal model. At the Mistral AI Summit, architecture details and benchmark performances were shared, showing strong OCR and screen understanding capabilities. Additionally, Arcee AI announced SuperNova, a distilled Llama 3.1 70B & 8B model outperforming Meta's Llama 3.1 70B instruct on benchmarks. DeepSeek released DeepSeek-V2.5, scoring 89 on HumanEval, surpassing GPT-4-Turbo, Opus, and Llama 3.1 in coding tasks. OpenAI plans to release Strawberry as part of ChatGPT soon, though its capabilities are debated. Anthropic introduced Workspaces for managing multiple Claude deployments with enhanced access controls.
not much happened today + AINews Podcast?
superforecaster-ai llama-3 reflection-70b glean sambanova cerebras stanford google apple hugging-face lmsys prompt-engineering research-ideas inference-speed retrieval-augmented-generation evaluation-methods visual-intelligence on-device-ai model-performance benchmarking novelty-detection danhendrycks benjamin-clavie bclavie bindureddy swyx borismpower corbtt drjimfan clementdelangue rohanpaul_ai
Glean doubled its valuation again. Dan Hendrycks' Superforecaster AI generates plausible election forecasts with interesting prompt engineering. A Stanford study found that LLM-generated research ideas are statistically more novel than those by expert humans. SambaNova announced faster inference for llama-3 models, surpassing Cerebras. Benjamin Clavie gave a notable talk on retrieval-augmented generation techniques. Strawberry is reported to launch in two weeks. Google Illuminate offers AI-generated podcast discussions about papers and books. Apple unveiled new AI features in iOS 18, including visual intelligence and improved Siri, with on-device and cloud processing for camera-based event additions. The Reflection 70B model sparked controversy over performance claims. Experts highlighted the unreliability of traditional benchmarks like MMLU and HumanEval, recommending alternative evaluation methods such as LMSys Chatbot Arena and Hugging Face's open-sourced Lighteval suite. The AI research community continues to explore AI's role in generating novel research ideas and improving benchmarking.
not much happened this weekend
jamba-1.5 dream-machine-1.5 ideogram-v2 mistral-nemo-minitron-8b mistral-7b llama-3-8b nous-research cursor-ai gdm george-hotz agibot unitree eth-zurich disney uc-san-diego ai21-labs luma-labs ideogram nvidia mistral-ai meta-ai-fair distributed-ai optimizer inter-gpu-communication low-latency-training open-source humanoid-robots robotics physics-based-motion teleoperation multilingual-models long-context text-to-video text-to-image model-performance george-hotz adcock_brett aman
Nous Research announced DisTrO, a new optimizer that drastically reduces inter-GPU communication by 1000x to 10,000x enabling efficient training on slow networks, offering an alternative to GDM's DiLoCo. Cursor AI gained viral attention from an 8-year-old user and announced a new fundraise, with co-host Aman returning to their podcast. George Hotz launched tinybox for sale. In robotics, AGIBOT revealed 5 new humanoid robots with open-source plans, and Unitree showcased its G1 humanoid robot nearing mass production at $16,000. ETH Zurich and Disney developed an AI system for physics-based robot motion generation from text or images. UC San Diego released ACE, an open-source teleoperation system for controlling multiple robots. AI21 Labs unveiled Jamba 1.5, a multilingual model with 256k context length and permissive licensing. Luma Labs released Dream Machine 1.5 for improved text-to-video generation. Ideogram launched v2 of its text-to-image model with near-perfect text generation. Nvidia and Mistral released Mistral-NeMo-Minitron 8B, a small model outperforming Mistral-7B and llama-3-8b on the Open LLM leaderboard.
super quiet day
jamba-1.5 phi-3.5 dracarys llama-3-1-70b llama-3-1 ai21-labs anthropic stanford hugging-face langchain qdrant aws elastic state-space-models long-context benchmarking ai-safety virtual-environments multi-agent-systems resource-management community-engagement model-performance bindu-reddy rohanpaul_ai jackclarksf danhendrycks reach_vb iqdotgraph
AI21 Labs released Jamba 1.5, a scaled-up State Space Model optimized for long context windows with 94B parameters and up to 2.5X faster inference, outperforming models like Llama 3.1 70B on benchmarks. The Phi-3.5 model was praised for its safety and performance, while Dracarys, a new 70B open-source coding model announced by Bindu Reddy, claims superior benchmarks over Llama 3.1 70B. Discussions on California's SB 1047 AI safety legislation involve Stanford and Anthropic, highlighting a balance between precaution and industry growth. Innovations include uv virtual environments for rapid setup, LangChain's LangSmith resource tags for project management, and multi-agent systems in Qdrant enhancing data workflows. Community events like the RAG workshop by AWS, LangChain, and Elastic continue to support AI learning and collaboration. Memes remain a popular way to engage with AI industry culture.
Ideogram 2 + Berkeley Function Calling Leaderboard V2
llama-3-70b gpt-4 phi-3.5 functionary-llama-3-70b llama-3 ideogram midjourney berkeley openai hugging-face microsoft meta-ai-fair baseten kai claude functionary function-calling benchmarking image-generation model-optimization vision multimodality model-performance fine-tuning context-windows cybersecurity code-analysis ai-assisted-development
Ideogram returns with a new image generation model featuring color palette control, a fully controllable API, and an iOS app, reaching a milestone of 1 billion images created. Meanwhile, Midjourney released a Web UI but still lacks an API. In function calling, the Berkeley Function Calling Leaderboard (BFCL) updated to BFCL V2 • Live, adding 2251 live, user-contributed function documentation and queries to improve evaluation quality. GPT-4 leads the leaderboard, but the open-source Functionary Llama 3-70B finetune from Kai surpasses Claude. On AI model releases, Microsoft launched three Phi-3.5 models with impressive reasoning and context window capabilities, while Meta AI FAIR introduced UniBench, a unified benchmark suite for over 50 vision-language model tasks. Baseten improved Llama 3 inference speed by up to 122% using Medusa. A new cybersecurity benchmark, Cyberbench, featuring 40 CTF tasks, was released. Additionally, Codegen was introduced as a tool for programmatic codebase analysis and AI-assisted development. "Multiple functions > parallel functions" was highlighted as a key insight in function calling.
not much happened today
gpt-4o claude-3.5-sonnet phi-3.5-mini phi-3.5-moe phi-3.5-vision llama-3-1-405b qwen2-math-72b openai anthropic microsoft meta-ai-fair hugging-face langchain box fine-tuning benchmarking model-comparison model-performance diffusion-models reinforcement-learning zero-shot-learning math model-efficiency ai-regulation ai-safety ai-engineering prompt-engineering swyx ylecun
OpenAI launched GPT-4o finetuning with a case study on Cosine. Anthropic released Claude 3.5 Sonnet with 8k token output. Microsoft Phi team introduced Phi-3.5 in three variants: Mini (3.8B), MoE (16x3.8B), and Vision (4.2B), noted for sample efficiency. Meta released Llama 3.1 405B, deployable on Google Cloud Vertex AI, offering GPT-4 level capabilities. Qwen2-Math-72B achieved state-of-the-art math benchmark performance with a Gradio demo. Discussions included model comparisons like ViT vs CNN and Mamba architecture. Tools updates featured DSPy roadmap, Flux Schnell improving diffusion speed on M1 Max, and LangChain community events. Research highlights zero-shot DUP prompting for math reasoning and fine-tuning best practices. AI ethics covered California's AI Safety Bill SB 1047 and regulatory concerns from Yann LeCun. Commentary on AI engineer roles by Swyx. "Chat with PDF" feature now available for Box Enterprise Plus users.
not much happened today
grok-2 claude-3.5-sonnet claude-3.5 gpt-4 chatgpt-4o-latest anthropic x-ai google-deepmind openai mistral-ai meta-ai-fair salesforce box prompt-caching model-performance vision fine-tuning multilinguality ai-safety design-automation document-processing ai-agents ai-integration ai-job-market ai-acceleration humor demis-hassabis francois-chollet
Anthropic rolled out prompt caching in its API, reducing input costs by up to 90% and latency by 80%, enabling instant fine-tuning with longer prompts. xAI released Grok-2, a new model competing with frontier models from Google DeepMind, OpenAI, Anthropic, Mistral AI, and Meta AI Fair, supporting vision and text inputs and integrating external image generation models. Claude 3.5 Sonnet is reported to outperform GPT-4 in coding and reasoning, while ChatGPT-4o-latest shows reasoning improvements. François Chollet proposed a theory defining intelligence as the efficiency of operationalizing past information for future tasks. The Aya project involves 3000 collaborators building multilingual AI datasets. Demis Hassabis discussed AI hype and safe AI development in a podcast. Tools like Dora AI for Figma and Box's AI API enhance design automation and document processing. Salesforce released DEI, an open AI software engineering agents framework with a 55% resolve rate on SWE-Bench Lite. Industry trends highlight rapid AI integration, networking importance in the AI job market, and potential OpenAI GPT-4 expansion in response to competitors. Memes include humor about Apple Vision Pro.
not much happened today
llama-3 llama-3-1 grok-2 claude-3.5-sonnet gpt-4-turbo nous-research nvidia salesforce goodfire-ai anthropic x-ai google-deepmind box langchain fine-tuning prompt-caching mechanistic-interpretability model-performance multimodality agent-frameworks software-engineering-agents api document-processing text-generation model-releases vision image-generation efficiency scientific-discovery fchollet demis-hassabis
GPT-5 delayed again amid a quiet news day. Nous Research released Hermes 3 finetune of Llama 3 base models, rivaling FAIR's instruct tunes but sparking debate over emergent existential crisis behavior with 6% roleplay data. Nvidia introduced Minitron finetune of Llama 3.1. Salesforce launched a DEI agent scoring 55% on SWE-Bench Lite. Goodfire AI secured $7M seed funding for mechanistic interpretability work. Anthropic rolled out prompt caching in their API, cutting input costs by up to 90% and latency by 80%, aiding coding assistants and large document processing. xAI released Grok-2, matching Claude 3.5 Sonnet and GPT-4 Turbo on LMSYS leaderboard with vision+text inputs and image generation integration. Claude 3.5 Sonnet reportedly outperforms GPT-4 in coding and reasoning. François Chollet defined intelligence as efficient operationalization of past info for future tasks. Salesforce's DEI framework surpasses individual agent performance. Google DeepMind's Demis Hassabis discussed AGI's role in scientific discovery and safe AI development. Dora AI plugin generates landing pages in under 60 seconds, boosting web team efficiency. Box AI API beta enables document chat, data extraction, and content summarization. LangChain updated Python & JavaScript integration docs.
Grok 2! and ChatGPT-4o-latest confuses everybody
gpt-4o grok-2 claude-3.5-sonnet flux-1 stable-diffusion-3 gemini-advanced openai x-ai black-forest-labs google-deepmind benchmarking model-performance tokenization security-vulnerabilities multi-agent-systems research-automation text-to-image conversational-ai model-integration ylecun rohanpaul_ai karpathy
OpenAI quietly released a new GPT-4o model in ChatGPT, distinct from the API version, reclaiming the #1 spot on Lmsys arena benchmarks across multiple categories including math, coding, and instruction-following. Meanwhile, X.ai launched Grok 2, outperforming Claude 3.5 Sonnet and previous GPT-4o versions, with plans for enterprise API release. Grok 2 integrates Black Forest Labs' Flux.1, an open-source text-to-image model surpassing Stable Diffusion 3. Google DeepMind announced Gemini Advanced with enhanced conversational features and Pixel device integration. AI researcher ylecun highlighted LLM limitations in learning and creativity, while rohanpaul_ai discussed an AI Scientist system generating publishable ML research at low cost. karpathy warned of security risks in LLM tokenizers akin to SQL injection.
Gemini Live
gemini-1.5-pro genie falcon-mamba gemini-1.5 llamaindex google anthropic tii supabase perplexity-ai llamaindex openai hugging-face multimodality benchmarking long-context retrieval-augmented-generation open-source model-releases model-integration model-performance software-engineering linear-algebra hugging-face-hub debugging omarsar0 osanseviero dbrxmosaicai alphasignalai perplexity_ai _jasonwei svpino
Google launched Gemini Live on Android for Gemini Advanced subscribers during the Pixel 9 event, featuring integrations with Google Workspace apps and other Google services. The rollout began on 8/12/2024, with iOS support planned. Anthropic released Genie, an AI software engineering system achieving a 57% improvement on SWE-Bench. TII introduced Falcon Mamba, a 7B attention-free open-access model scalable to long sequences. Benchmarking showed that longer context lengths do not always improve Retrieval-Augmented Generation. Supabase launched an AI-powered Postgres service dubbed the "ChatGPT of databases," fully open source. Perplexity AI partnered with Polymarket to integrate real-time probability predictions into search results. A tutorial demonstrated a multimodal recipe recommender using Qdrant, LlamaIndex, and Gemini. An OpenAI engineer shared success tips emphasizing debugging and hard work. The connection between matrices and graphs in linear algebra was highlighted for insights into nonnegative matrices and strongly connected components. Keras 3.5.0 was released with Hugging Face Hub integration for model saving and loading.
a quiet weekend
sam-2 qwen2-math gpt-4 claude-3.5 figure deepmind boston-dynamics alibaba llamaindex robotics object-segmentation real-time-processing disease-prediction speech-recognition cli-tools model-performance adcock_brett rasbt hamel-husain rohanpaul_ai
Figure unveiled Figure 02, claimed as the most advanced humanoid robot, operating autonomously at BMW's Plant Spartanburg. DeepMind developed a table tennis robot achieving 100% wins against beginners and 55% against intermediates. Boston Dynamics showcased the dexterity of its fully-electric Atlas robot performing pushups and burpees. An autonomous dental robot performed the world's first dental procedure on a human, reducing a 2-hour process to 15 minutes using a 3D volumetric scanner. SAM 2 was introduced as an open model for real-time object segmentation without custom adaptation. Alibaba released Qwen2-Math, outperforming GPT-4 and Claude 3.5 in math capabilities. A new Listening-While-Speaking Language Model (LSLM) enables simultaneous listening and speaking in real-time. Researchers developed a disease prediction AI with 95% accuracy for diseases like coronary artery disease, type 2 diabetes, and breast cancer. Tools like LlamaParse CLI and MLX Whisper package enhance PDF parsing and speech recognition, with the latter running 40X faster than realtime on M1 Max. The news highlights significant advancements in robotics, AI models, and practical AI tools.
GPT4o August + 100% Structured Outputs for All (GPT4o August edition)
gpt-4o-2024-08-06 llama-3-1-405b llama-3 claude-3.5-sonnet gemini-1.5-pro gpt-4o yi-large-turbo openai meta-ai-fair google-deepmind yi-large nvidia groq langchain jamai langsmith structured-output context-windows model-pricing benchmarking parameter-efficient-expert-retrieval retrieval-augmented-generation mixture-of-experts model-performance ai-hardware model-deployment filtering multi-lingual vision john-carmack jonathan-ross rohanpaul_ai
OpenAI released the new gpt-4o-2024-08-06 model with 16k context window and 33-50% lower pricing than the previous 4o-May version, featuring a new Structured Output API that improves output quality and reduces retry costs. Meta AI launched Llama 3.1, a 405-billion parameter model surpassing GPT-4 and Claude 3.5 Sonnet on benchmarks, alongside expanding the Llama Impact Grant program. Google DeepMind quietly released Gemini 1.5 Pro, outperforming GPT-4o, Claude-3.5, and Llama 3.1 on LMSYS benchmarks and leading the Vision Leaderboard. Yi-Large Turbo was introduced as a cost-effective upgrade priced at $0.19 per million tokens. In hardware, NVIDIA H100 GPUs were highlighted by John Carmack for their massive AI workload power, and Groq announced plans to deploy 108,000 LPUs by Q1 2025. New AI tools and techniques include RAG (Retrieval-Augmented Generation), the JamAI Base platform for Mixture of Agents systems, and LangSmith's enhanced filtering capabilities. Google DeepMind also introduced PEER (Parameter Efficient Expert Retrieval) architecture.
Llama 3.1 Leaks: big bumps to 8B, minor bumps to 70b, and SOTA OSS 405b model
llama-3-1-405b llama-3-8b llama-3-70b llama-3-1-8b gpt-4o gpt-4o-mini claude-3-5 qwen-2 meta-ai-fair openai alibaba multilinguality code-generation context-windows model-training synthetic-data benchmarking reasoning fine-tuning model-performance dataset-release swyx philschmid jjitsev lewtun teknium1 adcock_brett
Llama 3.1 leaks reveal a 405B dense model with 128k context length, trained on 39.3M GPU hours using H100-80GB GPUs, and fine-tuned with over 25M synthetic examples. The model shows significant benchmark improvements, especially for the 8B and 70B variants, with some evals suggesting the 70B outperforms GPT-4o. GPT-4o Mini launched as a cost-efficient variant with strong performance but some reasoning weaknesses. Synthetic datasets like NuminaMath enable models such as Alibaba Qwen 2 to surpass GPT-4o and Claude 3.5 in math competitions. Discussions include reasoning task benchmarks and dataset building for improved reasoning.
DataComp-LM: the best open-data 7B model/benchmark/dataset
mistral-nemo-12b gpt-4o-mini deepseek-v2-0628 mistral-7b llama-3 gemma-2 qwen-2 datacomp hugging-face openai nvidia mistral-ai deepseek dataset-design scaling-laws model-benchmarking model-performance fine-tuning multilinguality function-calling context-windows open-source-models model-optimization cost-efficiency benchmarking sam-altman guillaume-lample philschmid miramurati
DataComp team released a competitive 7B open data language model trained on only 2.5T tokens from the massive DCLM-POOL dataset of 240 trillion tokens, showing superior scaling trends compared to FineWeb. OpenAI launched GPT-4o mini, a cost-effective model with 82% MMLU and performance near GPT-4-Turbo, aimed at developers for broad applications. NVIDIA and Mistral jointly released the Mistral NeMo 12B model featuring a 128k token context window, FP8 checkpoint, multilingual support, and Apache 2.0 licensing. DeepSeek announced DeepSeek-V2-0628 as the top open-source model on the LMSYS Chatbot Arena leaderboard with strong rankings in coding, math, and hard prompts. This news highlights advances in dataset design, model efficiency, and open-source contributions in the AI community.
Mini, Nemo, Turbo, Lite - Smol models go brrr (GPT4o version)
gpt-4o-mini mistral-nemo llama-3 llama-3-400b deepseek-v2 openai nvidia mistral-ai togethercompute deepseek-ai lmsys model-quantization context-windows instruction-following model-performance cost-efficiency multimodality benchmarking open-source model-release sam-altman
GPT-4o-mini launches with a 99% price reduction compared to text-davinci-003, offering 3.5% the price of GPT-4o and matching Opus-level benchmarks. It supports 16k output tokens, is faster than previous models, and will soon support text, image, video, and audio inputs and outputs. Mistral Nemo, a 12B parameter model developed with Nvidia, features a 128k token context window, FP8 checkpoint, and strong benchmark performance. Together Lite and Turbo offer fp8/int4 quantizations of Llama 3 with up to 4x throughput and significantly reduced costs. DeepSeek V2 is now open-sourced. Upcoming releases include at least 5 unreleased models and Llama 4 leaks ahead of ICML 2024.
SciCode: HumanEval gets a STEM PhD upgrade
gpt-4 claude-3.5-sonnet llama-3-7b llama-3 dolphin-2.9.3-yi-1.5-34b-32k-gguf anthropic hugging-face nvidia benchmarks coding model-training gpu-optimization model-performance synthetic-data compiler-optimization zero-shot-learning yi-tay rohanpaul_ai alexalbert__ tri_dao abacaj
PhD-level benchmarks highlight the difficulty of coding scientific problems for LLMs, with GPT-4 and Claude 3.5 Sonnet scoring under 5% on the new SciCode benchmark. Anthropic doubled the max output token limit for Claude 3.5 Sonnet to 8192 tokens. The Q-GaLore method enables training LLaMA-7B on a single 16GB GPU. The Mosaic compiler now generates efficient code for NVIDIA H100 GPUs. The Dolphin 2.9.3-Yi-1.5-34B-32k-GGUF model on Hugging Face has over 111k downloads. Llama 3 shows strong performance, achieving 90% zero-shot accuracy on the MATH dataset. Discussions continue on the limitations and forms of synthetic data for model training.
Microsoft AgentInstruct + Orca 3
mistral-7b orca-2.5 microsoft-research apple tencent hugging-face synthetic-data fine-tuning instruction-following transformers model-performance hallucination-detection dataset-quality flashattention mixture-of-experts philschmid sama bindureddy rohanpaul_ai zachtratar dair_ai
Microsoft Research released AgentInstruct, the third paper in its Orca series, introducing a generative teaching pipeline that produces 25.8 million synthetic instructions to fine-tune mistral-7b, achieving significant performance gains: +40% AGIEval, +19% MMLU, +54% GSM8K, +38% BBH, +45% AlpacaEval, and a 31.34% reduction in hallucinations. This synthetic data approach follows the success of FineWeb and Apple's Rephrasing research in improving dataset quality. Additionally, Tencent claims to have generated 1 billion diverse personas for synthetic data. On AI Twitter, notable discussions included a shooting incident at a Trump rally and recent ML research highlights such as FlashAttention-3, RankRAG, and Mixture of A Million Experts.
Problems with MMLU-Pro
mmlu-pro llama-3-8b-q8 gpt4all-3.0 chatgpt claude llama gemini mobilellm runway-gen-3-alpha meta-3d-gen huggingface meta-ai-fair salesforce runway nomic-ai pineapple argil-ai benchmarking prompt-engineering model-evaluation model-performance multimodality automated-dataset-generation video-generation open-source-models ai-assistants text-to-3d deepfake transformers reasoning wenhu-chen danhendrycks clementine ylecun adcock_brett svpino rohanpaul_ai
MMLU-Pro is gaining attention as the successor to MMLU on the Open LLM Leaderboard V2 by HuggingFace, despite community concerns about evaluation discrepancies and prompt sensitivity affecting model performance, notably a 10-point improvement in Llama-3-8b-q8 with simple prompt tweaks. Meta's MobileLLM research explores running sub-billion parameter LLMs on smartphones using shared weights and deeper architectures. Salesforce's APIGen introduces an automated dataset generation system for function-calling tasks outperforming larger models. Runway Gen-3 Alpha launches an AI video generator for paid users creating realistic 10-second clips. Nomic AI's GPT4All 3.0 offers an open-source desktop app supporting thousands of local models. AI assistants with multimodal capabilities and affordable access to multiple LLMs like ChatGPT, Claude, Llama, and Gemini are emerging. Meta 3D Gen advances text-to-3D asset generation, while Argil AI enables deepfake video creation from text threads. Research on transformer grokking and reasoning highlights advances in robust reasoning capabilities.
RouteLLM: RIP Martian? (Plus: AINews Structured Summaries update)
gpt-4 gemma-2-27b gemma-2-9b lmsys openai llm-routing cost-efficiency model-performance model-optimization data-augmentation syntax-based-routing mixture-of-experts inference-throughput software-2.0 computer-vision karpathy bindureddy armand-joulin
LMSys introduces RouteLLM, an open-source router framework trained on preference data from Chatbot Arena, achieving cost reductions over 85% on MT Bench, 45% on MMLU, and 35% on GSM8K while maintaining 95% of GPT-4's performance. This approach surpasses previous task-specific routing by using syntax-based Mixture of Experts (MoE) routing and data augmentation, beating commercial solutions by 40%. The update highlights advances in LLM routing, cost-efficiency, and model performance optimization across multiple models rather than single-model or MoE-level improvements. Additionally, the AI Twitter recap notes the Gemma 2 model family as a top open model, the Block Transformer architecture for improved inference throughput, and a proposal for a fully Software 2.0 computer vision system by karpathy.
Claude Crushes Code - 92% HumanEval and Claude.ai Artifacts
claude-3.5-sonnet claude-3-opus gpt-4o anthropic openai cognition benchmarking model-performance coding model-optimization fine-tuning instruction-following model-efficiency model-release api performance-optimization alex-albert
Claude 3.5 Sonnet, released by Anthropic, is positioned as a Pareto improvement over Claude 3 Opus, operating at twice the speed and costing one-fifth as much. It achieves state-of-the-art results on benchmarks like GPQA, MMLU, and HumanEval, surpassing even GPT-4o and Claude 3 Opus on vision tasks. The model demonstrates significant advances in coding capabilities, passing 64% of test cases compared to 38% for Claude 3 Opus, and is capable of autonomously fixing pull requests. Anthropic also introduced the Artifacts feature, enabling users to interact with AI-generated content such as code snippets and documents in a dynamic workspace, similar to OpenAI's Code Interpreter. This release highlights improvements in performance, cost-efficiency, and coding proficiency, signaling a growing role for LLMs in software development.
Gemini launches context caching... or does it?
nemotron llama-3-70b chameleon-7b chameleon-34b gemini-1.5-pro deepseek-coder-v2 gpt-4-turbo claude-3-opus gemini-1.5-pro nvidia meta-ai-fair google deepseek hugging-face context-caching model-performance fine-tuning reinforcement-learning group-relative-policy-optimization large-context model-training coding model-release rohanpaul_ai _philschmid aman-sanger
Nvidia's Nemotron ranks #1 open model on LMsys and #11 overall, surpassing Llama-3-70b. Meta AI released Chameleon 7B/34B models after further post-training. Google's Gemini introduced context caching, offering a cost-efficient middle ground between RAG and finetuning, with a minimum input token count of 33k and no upper limit on cache duration. DeepSeek launched DeepSeek-Coder-V2, a 236B parameter model outperforming GPT-4 Turbo, Claude-3-Opus, and Gemini-1.5-Pro in coding tasks, supporting 338 programming languages and extending context length to 128K. It was trained on 6 trillion tokens using the Group Relative Policy Optimization (GRPO) algorithm and is available on Hugging Face with a commercial license. These developments highlight advances in model performance, context caching, and large-scale coding models.
Hybrid SSM/Transformers > Pure SSMs/Pure Transformers
mamba-2-hybrid gpt-4 qwen-72b table-llava-7b nvidia lamini-ai sakana-ai luma-labs mixture-of-experts benchmarking fine-tuning multimodality text-to-video model-performance memory-optimization preference-optimization video-understanding multimodal-tables bryan-catanzaro bindureddy ylecun ctnzr corbtt realsharonzhou andrew-n-carr karpathy _akhaliq omarsar0
NVIDIA's Bryan Catanzaro highlights a new paper on Mamba models, showing that mixing Mamba and Transformer blocks outperforms either alone, with optimal attention below 20%. Mixture-of-Agents (MoA) architecture improves LLM generation quality, scoring 65.1% on AlpacaEval 2.0 versus GPT-4 Omni's 57.5%. The LiveBench AI benchmark evaluates reasoning, coding, writing, and data analysis. A hybrid Mamba-2-Hybrid model with 7% attention surpasses a Transformer on MMLU accuracy, jumping from 50% to 53.6%. GPT-4 performs better at temperature=1. Qwen 72B leads open-source models on LiveBench AI. LaminiAI Memory Tuning achieves 95% accuracy on a SQL agent task, improving over instruction fine-tuning. Sakana AI Lab uses evolutionary strategies for preference optimization. Luma Labs Dream Machine demonstrates advanced text-to-video generation. The MMWorld benchmark evaluates multimodal video understanding, and Table-LLaVa 7B competes with GPT-4V on multimodal table tasks.
Not much happened today
gemini-1.5-flashmodel gemini-pro mixtral mamba-2 phi-3-medium phi-3-small gpt-3.5-turbo-0613 llama-3-8b llama-2-70b mistral-finetune twelve-labs livekit groq openai nea nvidia lmsys mistral-ai model-performance prompt-engineering data-curation ai-safety model-benchmarking model-optimization training sequence-models state-space-models daniel-kokotajlo rohanpaul_ai _arohan_ tri_dao _albertgu _philschmid sarahcat21 hamelhusain jachiam0 willdepue teknium1
Twelve Labs raised $50m in Series A funding co-led by NEA and NVIDIA's NVentures to advance multimodal AI. Livekit secured $22m in funding. Groq announced running at 800k tokens/second. OpenAI saw a resignation from Daniel Kokotajlo. Twitter users highlighted Gemini 1.5 FlashModel for high performance at low cost and Gemini Pro ranking #2 in Japanese language tasks. Mixtral models can run up to 8x faster on NVIDIA RTX GPUs using TensorRT-LLM. Mamba-2 model architecture introduces state space duality for larger states and faster training, outperforming previous models. Phi-3 Medium (14B) and Small (7B) models benchmark near GPT-3.5-Turbo-0613 and Llama 3 8B. Prompt engineering is emphasized for unlocking LLM capabilities. Data quality is critical for model performance, with upcoming masterclasses on data curation. Discussions on AI safety include a Frontier AI lab employee letter advocating whistleblower protections and debates on aligning AI to user intent versus broader humanity interests.
1 TRILLION token context, real time, on device?
gemini-1.5-pro gemini-1.5 cartesia mistral-ai scale-ai state-space-models voice-models multimodality model-performance on-device-ai long-context evaluation-leaderboards learning-rate-optimization scientific-publishing research-vs-engineering yann-lecun elon-musk
Cartesia, a startup specializing in state space models (SSMs), launched a low latency voice model outperforming transformer-based models with 20% lower perplexity, 2x lower word error, and 1 point higher NISQA quality. This breakthrough highlights the potential for models that can continuously process and reason over massive streams of multimodal data (text, audio, video) with a trillion token context window on-device. The news also covers recent AI developments including Mistral's Codestral weights release, Schedule Free optimizers paper release, and Scale AI's new elo-style eval leaderboards. Additionally, a debate between yann-lecun and elon-musk on the importance of publishing AI research versus engineering achievements was noted. The Gemini 1.5 Pro/Advanced models were mentioned for their strong performance.
Ten Commandments for Deploying Fine-Tuned Models
claude-3-opus claude-3 gpt-4o anthropic google openai fine-tuning prompt-engineering model-evaluation feature-alteration benchmarking model-performance open-source-models kyle-corbitt bindureddy alexalbert__
Gemini-in-Google-Slides is highlighted as a useful tool for summarizing presentations. Kyle Corbitt's talk on deploying fine-tuned models in production emphasizes avoiding fine-tuning unless necessary, focusing on prompting, data quality, appropriate model choice, and thorough evaluation. Anthropic showcased feature alteration in Claude AI, demonstrating control over model behavior and increased understanding of large language models. Open-source models like GPT-4o are approaching closed-source performance on benchmarks like MMLU for simple tasks, though advanced models remain necessary for complex automation.
Skyfall
gemini-1.5-pro gemini-1.5-flash yi-1.5 kosmos-2.5 paligemma falcon-2 deepseek-v2 hunyuan-dit gemini-1.5 gemini-1.5-flash yi-1.5 google-deepmind yi-ai microsoft hugging-face langchain maven multimodality mixture-of-experts transformer model-optimization long-context model-performance model-inference fine-tuning local-ai scaling-laws causal-models hallucination-detection model-distillation model-efficiency hamel-husain dan-becker clement-delangue philschmid osanseviero arankomatsuzaki jason-wei rohanpaul_ai
Between 5/17 and 5/20/2024, key AI updates include Google DeepMind's Gemini 1.5 Pro and Flash models, featuring sparse multimodal MoE architecture with up to 10M context and a dense Transformer decoder that is 3x faster and 10x cheaper. Yi AI released Yi-1.5 models with extended context windows of 32K and 16K tokens. Other notable releases include Kosmos 2.5 (Microsoft), PaliGemma (Google), Falcon 2, DeepSeek v2 lite, and HunyuanDiT diffusion model. Research highlights feature an Observational Scaling Laws paper predicting model performance across families, a Layer-Condensed KV Cache technique boosting inference throughput by up to 26×, and the SUPRA method converting LLMs into RNNs for reduced compute costs. Hugging Face expanded local AI capabilities enabling on-device AI without cloud dependency. LangChain updated its v0.2 release with improved documentation. The community also welcomed a new LLM Finetuning Discord by Hamel Husain and Dan Becker for Maven course users. "Hugging Face is profitable, or close to profitable," enabling $10 million in free shared GPUs for developers.
Chameleon: Meta's (unreleased) GPT4o-like Omnimodal Model
chameleon gpt-4o gemini-1.5-flash claude-3 meta-ai-fair openai google-deepmind anthropic reddit multimodality early-fusion benchmarking model-training tokenization streaming tool-use vision coding hallucination-detection model-performance armen-aghajanyan sama alexandr-wang abacaj alexalbert__
Meta AI FAIR introduced Chameleon, a new multimodal model family with 7B and 34B parameter versions trained on 10T tokens of interleaved text and image data enabling "early fusion" multimodality that can natively output any modality. While reasoning benchmarks are modest, its "omnimodality" approach competes well with pre-GPT4o multimodal models. OpenAI launched GPT-4o, a model excelling in benchmarks like MMLU and coding tasks, with strong multimodal capabilities but some regression in ELO scores and hallucination issues. Google DeepMind announced Gemini 1.5 Flash, a small model with 1M context window and flash performance, highlighting convergence trends between OpenAI and Google models. Anthropic updated Claude 3 with streaming support, forced tool use, and vision tool integration for multimodal knowledge extraction. OpenAI also partnered with Reddit, raising industry attention.
Cursor reaches >1000 tok/s finetuning Llama3-70b for fast file editing
gpt-4 gpt-4o gpt-4-turbo gpt-4o-mini llama bloom stable-diffusion cursor openai anthropic google-deepmind huggingface speculative-decoding code-edits multimodality image-generation streaming tool-use fine-tuning benchmarking mmlu model-performance evaluation synthetic-data context-windows sama abacaj imjaredz erhartford alexalbert svpino maximelabonne _philschmid
Cursor, an AI-native IDE, announced a speculative edits algorithm for code editing that surpasses GPT-4 and GPT-4o in accuracy and latency, achieving speeds of over 1000 tokens/s on a 70b model. OpenAI released GPT-4o with multimodal capabilities including audio, vision, and text, noted to be 2x faster and 50% cheaper than GPT-4 turbo, though with mixed coding performance. Anthropic introduced streaming, forced tool use, and vision features for developers. Google DeepMind unveiled Imagen Video and Gemini 1.5 Flash, a small model with a 1M-context window. HuggingFace is distributing $10M in free GPUs for open-source AI models like Llama, BLOOM, and Stable Diffusion. Evaluation insights highlight challenges with LLMs on novel problems and benchmark saturation, with new benchmarks like MMLU-Pro showing significant drops in top model performance.
Google I/O in 60 seconds
gemini-1.5-pro gemini-flash gemini-ultra gemini-pro gemini-nano gemma-2 llama-3-70b paligemma imagen-3 veo google google-deepmind youtube tokenization model-performance fine-tuning vision multimodality model-release model-training model-optimization ai-integration image-generation watermarking hardware-optimization voice video-understanding
Google announced updates to the Gemini model family, including Gemini 1.5 Pro with 2 million token support, and the new Gemini Flash model optimized for speed with 1 million token capacity. The Gemini suite now includes Ultra, Pro, Flash, and Nano models, with Gemini Nano integrated into Chrome 126. Additional Gemini features include Gemini Gems (custom GPTs), Gemini Live for voice conversations, and Project Astra, a live video understanding assistant. The Gemma model family was updated with Gemma 2 at 27B parameters, offering near-llama-3-70b performance at half the size, plus PaliGemma, a vision-language open model inspired by PaLI-3. Other launches include DeepMind's Veo, Imagen 3 for photorealistic image generation, and a Music AI Sandbox collaboration with YouTube. SynthID watermarking now extends to text, images, audio, and video. The Trillium TPUv6 codename was revealed. Google also integrated AI across its product suite including Workspace, Email, Docs, Sheets, Photos, Search, and Lens. "The world awaits Apple's answer."
GPT-4o: the new SOTA-EVERYTHING Frontier model (GPT4O version)
gpt-4o gpt-4-turbo openai lmsys multion adept multimodality vision speech-recognition tokenization real-time-processing coding model-performance model-optimization desktop-agents sama gdb
OpenAI has released GPT-4o, a new multimodal model capable of reasoning across text, audio, and video in real time with low latency (~300ms). It features voice and vision capabilities, improved non-English language performance with an expanded 200k vocabulary tokenizer, and is available to all ChatGPT users including free plans. GPT-4o is half the price and twice as fast as GPT-4-turbo with 5x rate limits. The model supports real-time voice and video input/output and shows strong coding capabilities. The release includes a new desktop app that can read screen and clipboard history, challenging existing desktop agent startups. The announcement was accompanied by demos including image generation and 3D object handling, with OpenAI achieving state-of-the-art performance in ASR and vision tasks. The update was widely discussed on social media, with comparisons to GPT-4T highlighting GPT-4o's speed and versatility. "GPT-4o is smart, fast, natively multimodal, and a step towards more natural human-computer interaction" and "extremely versatile and fun to play with".
Evals: The Next Generation
gpt-4 gpt-5 gpt-3.5 phi-3 mistral-7b llama-3 scale-ai mistral-ai reka-ai openai moderna sanctuary-ai microsoft mit meta-ai-fair benchmarking data-contamination multimodality fine-tuning ai-regulation ai-safety ai-weapons neural-networks model-architecture model-training model-performance robotics activation-functions long-context sam-altman jim-fan
Scale AI highlighted issues with data contamination in benchmarks like MMLU and GSM8K, proposing a new benchmark where Mistral overfits and Phi-3 performs well. Reka released the VibeEval benchmark for multimodal models addressing multiple choice benchmark limitations. Sam Altman of OpenAI discussed GPT-4 as "dumb" and hinted at GPT-5 with AI agents as a major breakthrough. Researchers jailbroke GPT-3.5 via fine-tuning. Global calls emerged to ban AI-powered weapons, with US officials urging human control over nuclear arms. Ukraine launched an AI consular avatar, while Moderna partnered with OpenAI for medical AI advancements. Sanctuary AI and Microsoft collaborate on AI for general-purpose robots. MIT introduced Kolmogorov-Arnold networks with improved neural network efficiency. Meta AI is training Llama 3 models with over 400 billion parameters, featuring multimodality and longer context.
Not much happened today
command-r-35b goliath-120 miqu-120 llama-3-8b tensorrt-llm llama-cpp gpt2-chat gpt-4-turbo llama-3 deepmind-alphazero anthropic openai perplexity-ai amazon apple microsoft deepmind creative-writing context-windows benchmarking model-performance self-learning function-calling retrieval-augmented-generation ai-assistants on-device-ai ai-lobbying copyright-infringement code-reasoning image-generation
Anthropic released a team plan and iOS app about 4 months after OpenAI. The Command-R 35B model excels at creative writing, outperforming larger models like Goliath-120 and Miqu-120. The Llama-3 8B model now supports a 1 million token context window, improving long-context understanding with minimal training on a single 8xA800 GPU machine. TensorRT-LLM benchmarks show it is 30-70% faster than llama.cpp on consumer hardware. A benchmark suggests GPT2-Chat may have better reasoning than GPT-4-Turbo, though results are debated. Demos include a self-learning Llama-3 voice agent running locally on Jetson Orin and a Self-Learning Large Action Model (LAM). Amazon CodeWhisperer was renamed to Q Developer, expanding its generative AI assistant capabilities. Apple plans an AI-enabled Safari browser with an on-device LLM in iOS 18 and macOS 15. Big Tech dominates AI lobbying in Washington, while major U.S. newspapers sued OpenAI and Microsoft for copyright infringement. DeepMind's AlphaZero became the greatest chess player in 9 hours, and their Naturalized Execution Tuning (NExT) method improves LLM code reasoning by 14-26%. Stable Diffusion is used for diverse image generation applications.
Perplexity, the newest AI unicorn
llama-3-8b llama-3-70b llama-3 llava-llama-3-8b-v1_1 phi-3 gpt-3.5 perplexity-ai meta-ai-fair hugging-face groq context-length fine-tuning quantization instruction-following model-comparison multimodality benchmarking memory-optimization model-performance daniel-gross aravind-srinivas
Perplexity doubles its valuation shortly after its Series B with a Series B-1 funding round. Significant developments around Llama 3 include context length extension to 16K tokens, new multimodal LLaVA models outperforming Llama 2, and fine-tuning improvements like QDoRA surpassing QLoRA. The Llama-3-70B model is praised for instruction following and performance across quantization formats. Phi-3 models by Meta AI released in multiple sizes show competitive benchmark results, with the 14B model achieving 78% on MMLU and the 3.8B model nearing GPT-3.5 performance.
Llama-3-70b is GPT-4-level Open Model
llama-3-70b llama-3-8b llama-3 llama-2-70b mistral-7b grok-3 stable-diffusion-3 vasa-1 meta-ai-fair groq nvidia amazon microsoft benchmarking model-performance fine-tuning function-calling arithmetic image-generation video-generation energy-usage gpu-demand political-bias ai-safety scaling context-windows tokenization elon-musk
Meta has released Llama 3, their most capable open large language model with 8B and 70B parameter versions supporting 8K context length and outperforming previous models including Llama 2 and Mistral 7B. Groq serves the Llama 3 70B model at 500-800 tokens/second, making it the fastest GPT-4-level token source. Discussions highlight AI scaling challenges with Elon Musk stating that training Grok 3 will require 100,000 Nvidia H100 GPUs, and AWS planning to acquire 20,000 B200 GPUs for a 27 trillion parameter model. Microsoft unveiled VASA-1 for lifelike talking face generation, while Stable Diffusion 3 and its extensions received mixed impressions. Concerns about AI energy usage and political bias in AI were also discussed.
Mixtral 8x22B Instruct sparks efficiency memes
mixtral-8x22b llama-2-7b olmo-7b mistral-ai hugging-face google microsoft intel softbank nvidia multilinguality math code-generation context-window model-performance model-release retrieval-augmented-generation deepfake ai-investment ai-chip hybrid-architecture training-data guillaume-lample osanseviero _philschmid svpino
Mistral released an instruct-tuned version of their Mixtral 8x22B model, notable for using only 39B active parameters during inference, outperforming larger models and supporting 5 languages with 64k context window and math/code capabilities. The model is available on Hugging Face under an Apache 2.0 license for local use. Google plans to invest over $100 billion in AI, with other giants like Microsoft, Intel, and SoftBank also making large investments. The UK criminalized non-consensual deepfake porn, raising enforcement debates. A former Nvidia employee claims Nvidia's AI chip lead is unmatchable this decade. AI companions could become a $1 billion market. AI has surpassed humans on several basic tasks but lags on complex ones. Zyphra introduced Zamba, a novel 7B parameter hybrid model outperforming LLaMA-2 7B and OLMo-7B with less training data, trained on 128 H100 GPUs over 30 days. GroundX API advances retrieval-augmented generation accuracy.
Lilian Weng on Video Diffusion
wizardlm-2 llama-3 reka-core devin opus sora openai adobe reka-ai diffusion-models video-generation training-free-adaptation multimodality intuition creativity analogy-recognition self-improving-ai model-recognition agi-timelines model-performance startup-competition lilian-weng sam-altman geoffrey-hinton yann-lecun
OpenAI expands with a launch in Japan, introduces a Batch API, and partners with Adobe to bring the Sora video model to Premiere Pro. Reka AI releases the Reka Core multimodal language model. WizardLM-2 is released showing impressive performance, and Llama 3 news is anticipated soon. Geoffrey Hinton highlights AI models exhibiting intuition, creativity, and analogy recognition beyond humans. The Devin AI model notably contributes to its own codebase. Opus demonstrates the ability to recognize its own generated outputs. Sam Altman warns startups about being steamrolled by OpenAI if they don't adapt quickly. Yann LeCun discusses AGI timelines, emphasizing it is inevitable but not imminent or solely from LLMs. Lilian Weng's blog on diffusion models for video generation highlights training-free adaptation as a breakthrough technique.
Mergestral, Meta MTIAv2, Cohere Rerank 3, Google Infini-Attention
mistral-8x22b command-r-plus rerank-3 infini-attention llama-3 sd-1.5 cosxl meta-ai-fair mistral-ai cohere google stability-ai hugging-face ollama model-merging training-accelerators retrieval-augmented-generation linear-attention long-context foundation-models image-generation rag-pipelines model-benchmarking context-length model-performance aidan_gomez ylecun swyx
Meta announced their new MTIAv2 chips designed for training and inference acceleration with improved architecture and integration with PyTorch 2.0. Mistral released the 8x22B Mixtral model, which was merged back into a dense model to effectively create a 22B Mistral model. Cohere launched Rerank 3, a foundation model enhancing enterprise search and retrieval-augmented generation (RAG) systems supporting 100+ languages. Google published a paper on Infini-attention, an ultra-scalable linear attention mechanism demonstrated on 1B and 8B models with 1 million sequence length. Additionally, Meta's Llama 3 is expected to start rolling out soon. Other notable updates include Command R+, an open model surpassing GPT-4 in chatbot performance with 128k context length, and advancements in Stable Diffusion models and RAG pipelines.
Claude 3 is officially America's Next Top Model
claude-3-opus claude-3-sonnet claude-3-haiku gpt-4o-mini mistral-7b qwen-72b anthropic mistral-ai huggingface openrouter stable-diffusion automatic1111 comfyui fine-tuning model-merging alignment ai-ethics benchmarking model-performance long-context cost-efficiency model-evaluation mark_riedl ethanjperez stuhlmueller ylecun aravsrinivas
Claude 3 Opus outperforms GPT4T and Mistral Large in blind Elo rankings, with Claude 3 Haiku marking a new cost-performance frontier. Fine-tuning techniques like QLoRA on Mistral 7B and evolutionary model merging on HuggingFace models are highlighted. Public opinion shows strong opposition to ASI development. Research supervision opportunities in AI alignment are announced. The Stable Diffusion 3 (SD3) release raises workflow concerns for tools like ComfyUI and automatic1111. Opus shows a 5% performance dip on OpenRouter compared to the Anthropic API. A new benchmark stresses LLM recall at long contexts, with Mistral 7B struggling and Qwen 72b performing well.
Grok-1 in Bio
grok-1 mixtral miqu-70b claude-3-opus claude-3 claude-3-haiku xai mistral-ai perplexity-ai groq anthropic openai mixture-of-experts model-release model-performance benchmarking finetuning compute hardware-optimization mmlu model-architecture open-source memes sam-altman arthur-mensch daniel-han arav-srinivas francis-yao
Grok-1, a 314B parameter Mixture-of-Experts (MoE) model from xAI, has been released under an Apache 2.0 license, sparking discussions on its architecture, finetuning challenges, and performance compared to models like Mixtral and Miqu 70B. Despite its size, its MMLU benchmark performance is currently unimpressive, with expectations that Grok-2 will be more competitive. The model's weights and code are publicly available, encouraging community experimentation. Sam Altman highlighted the growing importance of compute resources, while Grok's potential deployment on Groq hardware was noted as a possible game-changer. Meanwhile, Anthropic's Claude continues to attract attention for its "spiritual" interaction experience and consistent ethical framework. The release also inspired memes and humor within the AI community.
Dia de las Secuelas (StarCoder, The Stack, Dune, SemiAnalysis)
starcoder-2 starcoder2-15b hugging-face bigcode code-generation model-training dataset-release model-performance dylan-patel
HuggingFace/BigCode has released StarCoder v2, including the StarCoder2-15B model trained on over 600 programming languages using the The Stack v2 dataset. This release marks a state-of-the-art achievement for models of this size, with opt-out requests excluded from training data. A detailed technical report is available, highlighting the model's capabilities and training methodology. Additionally, a live event featuring Dylan Patel discussing GPU economics is announced for San Francisco.
Miqu confirmed to be an early Mistral-medium checkpoint
miqu-1-70b mistral-medium llama-2-70b-chat mixtral sqlcoder-70b codellama-70b bagelmistery-tour-v2 psyfighter-v2 mistral-ai hugging-face nous-research aiatmeta instruction-following sampling-methods fp16-quantization fine-tuning model-training context-length text-to-sql model-performance model-optimization intrstllrninja
Miqu, an open access model, scores 74 on MMLU and 84.5 on EQ-Bench, sparking debates about its performance compared to Mistral Medium. The CEO of Mistral confirmed these results. Discussions in the TheBloke Discord highlight Miqu's superiority in instruction-following and sampling methods like dynatemp and min-p. Developers also explore browser preferences and Discord UI themes. Role-playing with models like BagelMistery Tour v2 and Psyfighter v2 is popular, alongside technical talks on fp16 quantization of Miqu-1-70b. Training and fine-tuning tips for models like Unsloth and Mistral 7B are shared. In the Nous Research AI Discord, the Activation Beacon method is discussed for extending LLM context length from 4K to 400K tokens. SQLCoder-70B, fine-tuned on CodeLlama-70B, leads in text-to-SQL generation and is available on Hugging Face. The Miqu model also impresses with an 83.5 EQ-Bench score, fueling speculation about its capabilities.
CodeLLama 70B beats GPT4 on HumanEval
codellama miqu mistral-medium llama-2-70b aphrodite-engine mixtral flatdolphinmaid noromaid rpcal chatml mistral-7b activation-beacon eagle-7b rwkv-v5 openhermes2.5 nous-hermes-2-mixtral-8x7b-dpo imp-v1-3b bakllava moondream qwen-vl meta-ai-fair ollama nous-research mistral-ai hugging-face ai-ethics alignment gpu-optimization direct-prompt-optimization fine-tuning cuda-programming optimizer-technology quantization multimodality context-length dense-retrieval retrieval-augmented-generation multilinguality model-performance open-source code-generation classification vision
Meta AI surprised the community with the release of CodeLlama, an open-source model now available on platforms like Ollama and MLX for local use. The Miqu model sparked debate over its origins, possibly linked to Mistral Medium or a fine-tuned Llama-2-70b, alongside discussions on AI ethics and alignment risks. The Aphrodite engine showed strong performance on A6000 GPUs with specific configurations. Role-playing AI models such as Mixtral and Flatdolphinmaid faced challenges with repetitiveness, while Noromaid and Rpcal performed better, with ChatML and DPO recommended for improved responses. Learning resources like fast.ai's course were highlighted for ML/DL beginners, and fine-tuning techniques with optimizers like Paged 8bit lion and adafactor were discussed.
At Nous Research AI, the Activation Beacon project introduced a method for unlimited context length in LLMs using "global state" tokens, potentially transforming retrieval-augmented models. The Eagle-7B model, based on RWKV-v5, outperformed Mistral in benchmarks with efficiency and multilingual capabilities. OpenHermes2.5 was recommended for consumer hardware due to its quantization methods. Multimodal and domain-specific models like IMP v1-3b, Bakllava, Moondream, and Qwen-vl were explored for classification and vision-language tasks. The community emphasized centralizing AI resources for collaborative research.
RWKV "Eagle" v5: Your move, Mamba
rwkv-v5 mistral-7b miqu-1-70b mistral-medium llama-2 mistral-instruct-v0.2 mistral-tuna llama-2-13b kunoichi-dpo-v2-7b gpt-4 eleutherai mistral-ai hugging-face llamaindex nous-research rwkv lmsys fine-tuning multilinguality rotary-position-embedding model-optimization model-performance quantization speed-optimization prompt-engineering model-benchmarking reinforcement-learning andrej-karpathy
RWKV v5 Eagle was released with better-than-mistral-7b evaluation results, trading some English performance for multilingual capabilities. The mysterious miqu-1-70b model sparked debate about its origins, possibly a leak or distillation of Mistral Medium or a fine-tuned Llama 2. Discussions highlighted fine-tuning techniques, including the effectiveness of 1,000 high-quality prompts over larger mixed-quality datasets, and tools like Deepspeed, Axolotl, and QLoRA. The Nous Research AI community emphasized the impact of Rotary Position Embedding (RoPE) theta settings on LLM extrapolation, improving models like Mistral Instruct v0.2. Speed improvements in Mistral Tuna kernels reduced token processing costs, enhancing efficiency. The launch of Eagle 7B with 7.52B parameters showcased strong multilingual performance, surpassing other 7B class models.
1/17/2024: Help crowdsource function calling datasets
mistral-7b dolphin-2.7-mixtral-8x7b mega-dolphin dolphin-2.6-mistral-7b-dpo llama-cpp lm-studio mistral-ai microsoft hugging-face apple function-calling quantization model-performance gpu-optimization model-selection closed-source memory-optimization linux-server api-fees headless-mode yagilb heyitsyorkie
LM Studio updated its FAQ clarifying its closed-source status and perpetual freeness for personal use with no data collection. The new beta release includes fixes and hints at upcoming 2-bit quantization support. For gaming, models like Dolphin 2.7 Mixtral 8x7B, MegaDolphin, and Dolphin 2.6 Mistral 7B DPO with Q4_K_M quantization were recommended. Discussions highlighted that single powerful GPUs outperform multi-GPU setups due to bottlenecks, with older GPUs like Tesla P40 being cost-effective. Microsoft's AutoGen Studio was introduced but has issues and requires API fees for open-source models. Linux users are advised to use llama.cpp over LM Studio due to lack of headless mode. Additional tools like LLMFarm for iOS and various Hugging Face repositories were also mentioned. "LM Studio must be running to use the local inference server as there is no headless mode available" and "matching model size to GPU memory is key for performance" were notable points.
1/11/2024: Mixing Experts vs Merging Models
gpt-4-turbo gpt-4-0613 mixtral deepseekmoe phixtral deepseek-ai hugging-face nous-research teenage-engineering discord mixture-of-experts model-merging fine-tuning rag security discord-tos model-performance prompt-engineering function-calling semantic-analysis data-frameworks ash_prabaker shacrw teknium 0xevil everyoneisgross ldj pramod8481 mgreg_42266 georgejrjrjr kenakafrosty
18 guilds, 277 channels, and 1342 messages were analyzed with an estimated reading time saved of 187 minutes. The community switched to GPT-4 turbo and discussed the rise of Mixture of Experts (MoE) models like Mixtral, DeepSeekMOE, and Phixtral. Model merging techniques, including naive linear interpolation and "frankenmerges" by SOLAR and Goliath, are driving new performance gains on open leaderboards. Discussions in the Nous Research AI Discord covered topics such as AI playgrounds supporting prompt and RAG parameters, security concerns about third-party cloud usage, debates on Discord bots and TOS, skepticism about Teenage Engineering's cloud LLM, and performance differences between GPT-4 0613 and GPT-4 turbo. The community also explored fine-tuning strategies involving DPO, LoRA, and safetensors, integration of RAG with API calls, semantic differences between MoE and dense LLMs, and data frameworks like llama index and SciPhi-AI's synthesizer. Issues with anomalous characters in fine-tuning were also raised.
12/29/2023: TinyLlama on the way
tinyllama-1.1b openai hugging-face gpu-optimization model-deployment discord-bots embedding-models inference-server hardware-compatibility model-performance beta-testing autogen context-window
The Nous/Axolotl community is pretraining a 1.1B model on 3 trillion tokens, showing promising results on HellaSwag for a small 1B model. The LM Studio Discord discussions cover extensive GPU-related issues, Discord bot integration with the OpenAI API, and hardware limitations affecting model usage. Community members also discuss server hosting for embeddings and LLMs, propose updates for Discord channels to improve model development collaboration, and address a gibberish problem in beta releases. The Autogen tool's installation and operational challenges are also clarified by users.
12/27/2023: NYT vs OpenAI
phi2 openhermes-2.5-mistral-7b llama-2-7b llama-2-13b microsoft-research mistral-ai apple amd model-performance fine-tuning llm-api gpu-optimization hardware-configuration multi-gpu inference-speed plugin-release conversation-history
The LM Studio Discord community extensively discussed model performance comparisons, notably between Phi2 by Microsoft Research and OpenHermes 2.5 Mistral 7b, with focus on U.S. history knowledge and fine-tuning for improved accuracy. Technical challenges around LLM API usage, conversation history maintenance, and GPU optimization for inference speed were addressed. Hardware discussions covered DDR4 vs DDR5, multi-GPU setups, and potential of Apple M1/M3 and AMD AI CPUs for AI workloads. The community also announced the ChromaDB Plugin v3.0.2 release enabling image search in vector databases. Users shared practical tips on running multiple LM Studio instances and optimizing resource usage.
12/26/2023: not much happened today
llava exllama2 meta-ai-fair google-deepmind gpu-offloading vram-utilization model-conversion moe-models multimodality model-performance hardware-configuration model-saving chatml installation-issues music-generation
LM Studio users extensively discussed its performance, installation issues on macOS, and upcoming features like Exllama2 support and multimodality with the Llava model. Conversations covered GPU offloading, vRAM utilization, MoE model expert selection, and model conversion compatibility. The community also addressed inefficient help requests referencing the blog 'Don't Ask to Ask, Just Ask'. Technical challenges with ChromaDB Plugin, server vs desktop hardware performance, and saving model states with Autogen were highlighted. Discussions included comparisons with other chatbots and mentions of AudioCraft from meta-ai-fair and MusicLM from google-deepmind for music generation.
12/18/2023: Gaslighting Mistral for fun and profit
gpt-4-turbo gpt-3.5-turbo claude-2.1 claude-instant-1 gemini-pro gpt-4.5 dalle-3 openai anthropic google-deepmind prompt-engineering api model-performance ethics role-play user-experience ai-impact-on-jobs ai-translation technical-issues sam-altman
OpenAI Discord discussions reveal comparisons among language models including GPT-4 Turbo, GPT-3.5 Turbo, Claude 2.1, Claude Instant 1, and Gemini Pro, with GPT-4 Turbo noted for user-centric explanations. Rumors about GPT-4.5 remain unconfirmed, with skepticism prevailing until official announcements. Users discuss technical challenges like slow responses and API issues, and explore role-play prompt techniques to enhance model performance. Ethical concerns about AI's impact on academia and employment are debated. Future features for Dalle 3 and a proposed new GPT model are speculated upon, while a school project seeks help using the OpenAI API. The community also touches on AI glasses and job market implications of AI adoption.
12/13/2023 SOLAR10.7B upstages Mistral7B?
solar-10.7b llama-2 mistral-7b phi-2 gpt-4 gemini upstage nous-research openai mistral-ai microsoft depth-up-scaling pretraining synthetic-data gpu-training api-usage model-integration agi asi chat-models vision model-performance fine-tuning
Upstage released the SOLAR-10.7B model, which uses a novel Depth Up-Scaling technique built on the llama-2 architecture and integrates mistral-7b weights, followed by continued pre-training. The Nous community finds it promising but not exceptional. Additionally, weights for the phi-2 base model were released, trained on 1.4 trillion tokens including synthetic texts created by GPT-3 and filtered by GPT-4, using 96 A100 GPUs over 14 days. On OpenAI's Discord, users discussed challenges with various GPT models, including incoherent outputs, API usage limitations, and issues with GPT-4 Vision API. Conversations also covered understanding AGI and ASI, concerns about OpenAI's partnership with Axel Springer, and pricing changes for GPT Plus. Discussions included the Gemini chat model integrated into Bard and comparisons with GPT-4 performance.
12/9/2023: The Mixtral Rush
mixtral hermes-2.5 hermes-2 mistral-yarn ultrachat discoresearch fireworks-ai hugging-face mistral-ai benchmarking gpu-requirements multi-gpu quantization gptq chain-of-thought min-p-sampling top-p-sampling model-sampling model-merging model-performance small-models reasoning-consistency temperature-sampling bjoernp the_bloke rtyax kalomaze solbus calytrix
Mixtral's weights were released without code, prompting the Disco Research community and Fireworks AI to implement it rapidly. Despite efforts, no significant benchmark improvements were reported, limiting its usefulness for local LLM usage but marking progress for the small models community. Discussions in the DiscoResearch Discord covered Mixtral's performance compared to models like Hermes 2.5 and Hermes 2, with evaluations on benchmarks such as winogrande, truthfulqa_mc2, and arc_challenge. Technical topics included GPU requirements, multi-GPU setups, and quantization via GPTQ. Benchmarking strategies like grammar-based evaluation, chain of thought (CoT), and min_p sampling were explored, alongside model sampling techniques like Min P and Top P to enhance response stability and creativity. Users also discussed GPTs' learning limitations and the adaptability of models under varying conditions, emphasizing min_p sampling's role in enabling higher temperature settings for creativity.
12/7/2023: Anthropic says "skill issue"
claude-2.1 gpt-4 gpt-3.5 gemini-pro gemini-ultra gpt-4.5 chatgpt bingchat dall-e gpt-5 anthropic openai google prompt-engineering model-performance regulation language-model-performance image-generation audio-processing midi-sequence-analysis subscription-issues network-errors
Anthropic fixed a glitch in their Claude 2.1 model's needle in a haystack test by adding a prompt. Discussions on OpenAI's Discord compared Google's Gemini Pro and Gemini Ultra models with OpenAI's GPT-4 and GPT-3.5, with some users finding GPT-4 superior in benchmarks. Rumors about a GPT-4.5 release circulated without official confirmation. Concerns were raised about "selective censorship" affecting language model performance. The EU's potential regulation of AI, including ChatGPT, was highlighted. Users reported issues with ChatGPT Plus message limits and subscription upgrades, and shared experiences with BingChat and DALL-E. The community discussed prompt engineering techniques and future applications like image generation and MIDI sequence analysis, expressing hopes for GPT-5.