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Topic: "open-source"
Reasoning Price War 2: Mistral Magistral + o3's 80% price cut + o3-pro
o3 o3-pro gpt-4.1 claude-4-sonnet gemini-2.5-pro magistral-small magistral-medium mistral-small-3.1 openai anthropic google-deepmind mistral-ai perplexity-ai reasoning token-efficiency price-cut benchmarking open-source model-releases context-windows gpu-optimization swyx sama scaling01 polynoamial nrehiew_ kevinweil gdb flavioad stevenheidel aravsrinivas
OpenAI announced an 80% price cut for its o3 model, making it competitively priced with GPT-4.1 and rivaling Anthropic's Claude 4 Sonnet and Google's Gemini 2.5 Pro. Alongside, o3-pro was released as a more powerful and reliable variant, though early benchmarks showed mixed performance relative to cost. Mistral AI launched its Magistral reasoning models, including an open-source 24B parameter version optimized for efficient deployment on consumer GPUs. The price reduction and new model releases signal intensified competition in reasoning-focused large language models, with notable improvements in token efficiency and cost-effectiveness.
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.
AI Engineer World's Fair Talks Day 1
gemini-2.5 gemma claude-code mistral cursor anthropic openai aie google-deepmind meta-ai-fair agent-based-architecture open-source model-memorization scaling-laws quantization mixture-of-experts language-model-memorization model-generalization langgraph model-architecture
Mistral launched a new Code project, and Cursor released version 1.0. Anthropic improved Claude Code plans, while ChatGPT announced expanded connections. The day was dominated by AIE keynotes and tracks including GraphRAG, RecSys, and Tiny Teams. On Reddit, Google open-sourced the DeepSearch stack for building AI agents with Gemini 2.5 and LangGraph, enabling flexible agent architectures and integration with local LLMs like Gemma. A new Meta paper analyzed language model memorization, showing GPT-style transformers store about 3.5–4 bits/parameter and exploring the transition from memorization to generalization, with implications for Mixture-of-Experts models and quantization effects.
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.
not much happened today
phi-4 phi-4-mini-reasoning qwen3-235b qwen3-moe-235b qwen3-moe-30b qwen3-dense-32b qwen3-dense-14b qwen3-dense-8b qwen3-dense-4b qwen3-dense-0.6b qwen2.5-omni-3b deepseek-prover-v2 llama llama-guard-4 prompt-guard-2 mimo-7b microsoft anthropic cursor alibaba togethercompute deepseek meta-ai-fair xiaomi openrouterai cohere reasoning model-fine-tuning model-evaluation benchmarking model-popularity open-source math model-scaling model-filtering jailbreak-prevention cline reach_vb vipulved akhaliq omarsar0 zhs05232838 huajian_xin mervenoyann karpathy random_walker sarahookr blancheminerva clefourrier
Microsoft released Phi-reasoning 4, a finetuned 14B reasoning model slightly behind QwQ but limited by data transparency and token efficiency issues. Anthropic introduced remote MCP server support and a 45-minute Research mode in Claude. Cursor published a model popularity list. Alibaba launched Qwen3-235B and other Qwen3 variants, highlighting budget-friendly coding and reasoning capabilities, with availability on Together AI API. Microsoft also released Phi-4-Mini-Reasoning with benchmark performance on AIME 2025 and OmniMath. DeepSeek announced DeepSeek-Prover V2 with state-of-the-art math problem solving, scaling to 671B parameters. Meta AI's Llama models hit 1.2 billion downloads, with new Llama Guard 4 and Prompt Guard 2 for input/output filtering and jailbreak prevention. Xiaomi released the open-source reasoning model MiMo-7B trained on 25 trillion tokens. Discussions on AI model evaluation highlighted issues with the LMArena leaderboard, data access biases favoring proprietary models, and challenges in maintaining fair benchmarking, with suggestions for alternatives like OpenRouterAI rankings. "LMArena slop and biased" and "61.3% of all data going to proprietary model providers" were noted concerns.
ChatGPT responds to GlazeGate + LMArena responds to Cohere
qwen3-235b-a22b qwen3 qwen3-moe llama-4 openai cohere lm-arena deepmind x-ai meta-ai-fair alibaba vllm llamaindex model-releases model-benchmarking performance-evaluation open-source multilinguality model-integration fine-tuning model-optimization joannejang arankomatsuzaki karpathy sarahookr reach_vb
OpenAI faced backlash after a controversial ChatGPT update, leading to an official retraction admitting they "focused too much on short-term feedback." Researchers from Cohere published a paper criticizing LMArena for unfair practices favoring incumbents like OpenAI, DeepMind, X.ai, and Meta AI Fair. The Qwen3 family by Alibaba was released, featuring models up to 235B MoE, supporting 119 languages and trained on 36 trillion tokens, with integration into vLLM and support in tools like llama.cpp. Meta announced the second round of Llama Impact Grants to promote open-source AI innovation. Discussions on AI Twitter highlighted concerns about leaderboard overfitting and fairness in model benchmarking, with notable commentary from karpathy and others.
Cognition's DeepWiki, a free encyclopedia of all GitHub repos
o4-mini perception-encoder qwen-2.5-vl dia-1.6b grok-3 gemini-2.5-pro claude-3.7 gpt-4.1 cognition meta-ai-fair alibaba hugging-face openai perplexity-ai vllm vision text-to-speech reinforcement-learning ocr model-releases model-integration open-source frameworks chatbots model-selector silas-alberti mervenoyann reach_vb aravsrinivas vikparuchuri lioronai
Silas Alberti of Cognition announced DeepWiki, a free encyclopedia of all GitHub repos providing Wikipedia-like descriptions and Devin-backed chatbots for public repos. Meta released Perception Encoders (PE) with A2.0 license, outperforming InternVL3 and Qwen2.5VL on vision tasks. Alibaba launched the Qwen Chat App for iOS and Android. Hugging Face integrated the Dia 1.6B SoTA text-to-speech model via FAL. OpenAI expanded deep research usage with a lightweight version powered by o4-mini model, now available to free users. Perplexity AI updated their model selector with Grok 3 Beta, o4-mini, and support for models like gemini 2.5 pro, claude 3.7, and gpt-4.1. vLLM project introduced OpenRLHF framework for reinforcement learning with human feedback. Surya OCR alpha model supports 90+ languages and LaTeX. MegaParse open-source library was introduced for LLM-ready data formats.
Gemini 2.5 Flash completes the total domination of the Pareto Frontier
gemini-2.5-flash o3 o4-mini google openai anthropic tool-use multimodality benchmarking reasoning reinforcement-learning open-source model-releases chain-of-thought coding-agent sama kevinweil markchen90 alexandr_wang polynoamial scaling01 aidan_mclau cwolferesearch
Gemini 2.5 Flash is introduced with a new "thinking budget" feature offering more control compared to Anthropic and OpenAI models, marking a significant update in the Gemini series. OpenAI launched o3 and o4-mini models, emphasizing advanced tool use capabilities and multimodal understanding, with o3 dominating several leaderboards but receiving mixed benchmark reviews. The importance of tool use in AI research and development is highlighted, with OpenAI Codex CLI announced as a lightweight open-source coding agent. The news reflects ongoing trends in AI model releases, benchmarking, and tool integration.
OpenAI o3, o4-mini, and Codex CLI
o3 o4-mini gemini-2.5-pro claude-3-sonnet chatgpt openai reinforcement-learning performance vision tool-use open-source coding-agents model-benchmarking multimodality scaling inference sama aidan_mclau markchen90 gdb aidan_clark_ kevinweil swyx polynoamial scaling01
OpenAI launched the o3 and o4-mini models, emphasizing improvements in reinforcement-learning scaling and overall efficiency, making o4-mini cheaper and better across prioritized metrics. These models showcase enhanced vision and tool use capabilities, though API access for these features is pending. The release includes Codex CLI, an open-source coding agent that integrates with these models to convert natural language into working code. Accessibility extends to ChatGPT Plus, Pro, and Team users, with o3 being notably more expensive than Gemini 2.5 Pro. Performance benchmarks highlight the intelligence gains from scaling inference, with comparisons against models like Sonnet and Gemini. The launch has been well received despite some less favorable evaluation results.
Google's Agent2Agent Protocol (A2A)
kimi-vl-a3b gpt-4o llama-4-scout llama-4-maverick llama-4-behemoth deepcoder-14b o3-mini o1 llama-3.1-nemotron-ultra-253b deepseek-r1 google google-deepmind moonshot-ai meta-ai-fair uc-berkeley openai nvidia hugging-face togethercompute deepseek agent-interoperability multimodality vision math reinforcement-learning coding model-training open-source model-benchmarking context-windows streaming push-notifications enterprise-authentication model-release reach_vb _akhaliq epochairesearch artificialanlys winglian danielhanchen yuchenj_uw jeremyphoward
Google Cloud Next announcements featured the launch of Google and DeepMind's full MCP support and a new Agent to Agent protocol designed for agent interoperability with multiple partners. The protocol includes components like the Agent Card, Task communication channels, Enterprise Auth and Observability, and Streaming and Push Notification support. On the model front, Moonshot AI released Kimi-VL-A3B, a multimodal model with 128K context and strong vision and math benchmark performance, outperforming gpt-4o. Meta AI introduced smaller versions of llama-4 family models: llama-4-scout and llama-4-maverick, with a larger Behemoth model still in training. DeepCoder 14B from UC Berkeley is an open-source coding model rivaling openai's o3-mini and o1 models, trained with reinforcement learning on 24K coding problems. Nvidia released llama-3.1-nemotron-ultra-253b on Hugging Face, noted for beating llama-4-behemoth and maverick and competing with deepseek-r1.
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.
not much happened today
gpt-2 r1 gemma-3 gemmacoder3-12b qwen2.5-omni openai deepseek berkeley alibaba togethercompute nvidia azure runway langchain bmw amazon open-source function-calling benchmarking code-reasoning multimodality inference-speed image-generation voice-generation animation robotics realtime-transcription webrtc sama clémentdelangue lioronai scaling01 cognitivecompai osanseviero jack_w_rae ben_burtenshaw theturingpost vipulved kevinweil tomlikesrobots adcock_brett juberti
OpenAI plans to release its first open-weight language model since GPT-2 in the coming months, signaling a move towards more open AI development. DeepSeek launched its open-source R1 model earlier this year, challenging perceptions of China's AI progress. Gemma 3 has achieved function calling capabilities and ranks on the Berkeley Function-Calling Leaderboard, while GemmaCoder3-12b improves code reasoning performance on LiveCodeBench. Alibaba_Qwen's Qwen2.5-Omni introduces a novel Thinker-Talker system and TMRoPE for multimodal input understanding. The TogetherCompute team achieved 140 TPS on a 671B parameter model, outperforming Azure and DeepSeek API on Nvidia GPUs. OpenAI also expanded ChatGPT features with image generation for all free users and a new voice release. Runway Gen-4 enhances animation for miniature dioramas, and LangChain launched a chat-based generative UI agent. Commercial deployment of Figure 03 humanoid robots at BMW highlights advances in autonomy and manufacturing scaling. New tools include OpenAI's realtime transcription API with WebRTC support and Amazon's Nova Act AI browser agent.
not much happened today
deepseek-r1 gemma-3 gemma-3-27b openai nvidia deepseek hugging-face fp8 model-efficiency hardware-requirements quantization benchmarking model-deployment open-source sam-altman
DeepSeek R1 demonstrates significant efficiency using FP8 precision, outperforming Gemma 3 27B in benchmarks with a Chatbot Arena Elo Score of 1363 vs. 1338, requiring substantial hardware like 32 H100 GPUs and 2,560GB VRAM. OpenAI labels DeepSeek as "state-controlled" and calls for bans on "PRC-produced" models, sparking community backlash accusing OpenAI and Sam Altman of anti-competitive behavior. Discussions emphasize DeepSeek's openness and affordability compared to OpenAI, with users highlighting its local and Hugging Face deployment options. Meanwhile, Gemma 3 receives mixed community feedback on creativity and worldbuilding.
The new OpenAI Agents Platform
reka-flash-3 o1-mini claude-3-7-sonnet llama-3-3-70b sonic-2 qwen-chat olympiccoder openai reka-ai hugging-face deepseek togethercompute alibaba ai-agents api model-releases fine-tuning reinforcement-learning model-training model-inference multimodality voice-synthesis gpu-clusters model-distillation performance-optimization open-source sama reach_vb
OpenAI introduced a comprehensive suite of new tools for AI agents, including the Responses API, Web Search Tool, Computer Use Tool, File Search Tool, and an open-source Agents SDK with integrated observability tools, marking a significant step towards the "Year of Agents." Meanwhile, Reka AI open-sourced Reka Flash 3, a 21B parameter reasoning model that outperforms o1-mini and powers their Nexus platform, with weights available on Hugging Face. The OlympicCoder series surpassed Claude 3.7 Sonnet and much larger models on competitive coding benchmarks. DeepSeek built a 32K GPU cluster capable of training V3-level models in under a week and is exploring AI distillation. Hugging Face announced Cerebras inference support, achieving over 2,000 tokens/s on Llama 3.3 70B, 70x faster than leading GPUs. Reka's Sonic-2 voice AI model delivers 40ms latency via the Together API. Alibaba's Qwen Chat enhanced its multimodal interface with video understanding up to 500MB, voice-to-text, guest mode, and expanded file uploads. Sama praised OpenAI's new API as "one of the most well-designed and useful APIs ever."
not much happened today
jamba-1.6 mistral-ocr qwq-32b o1 o3-mini instella llama-3-2-3b gemma-2-2b qwen-2-5-3b babel-9b babel-83b gpt-4o claude-3-7-sonnet ai21-labs mistral-ai alibaba openai amd anthropic hugging-face multimodality ocr multilinguality structured-output on-prem-deployment reasoning benchmarking api open-source model-training gpu-optimization prompt-engineering function-calling
AI21 Labs launched Jamba 1.6, touted as the best open model for private enterprise deployment, outperforming Cohere, Mistral, and Llama on benchmarks like Arena Hard. Mistral AI released a state-of-the-art multimodal OCR model with multilingual and structured output capabilities, available for on-prem deployment. Alibaba Qwen introduced QwQ-32B, an open-weight reasoning model with 32B parameters and cost-effective usage, showing competitive benchmark scores. OpenAI released o1 and o3-mini models with advanced API features including streaming and function calling. AMD unveiled Instella, open-source 3B parameter language models trained on AMD Instinct MI300X GPUs, competing with Llama-3.2-3B and others. Alibaba also released Babel, open multilingual LLMs performing comparably to GPT-4o. Anthropic launched Claude 3.7 Sonnet, enhancing reasoning and prompt engineering capabilities.
GPT 4.5 — Chonky Orion ships!
gpt-4.5 phi-4-multimodal phi-4-mini command-r7b-arabic openai microsoft cohere creative-writing natural-language-processing multimodality math coding context-windows model-releases open-source arabic-language sama kevinweil aidan_mclau omarsar0 rasbt reach_vb
OpenAI released GPT-4.5 as a research preview, highlighting its deep world knowledge, improved understanding of user intent, and a 128,000 token context window. It is noted for excelling in writing, creative tasks, image understanding, and data extraction but is not a reasoning model. Microsoft unveiled Phi-4 Multimodal and Phi-4 Mini, open-source models integrating text, vision, and speech/audio, with strong performance in math and coding tasks. Cohere released Command R7B Arabic, an open-weights model optimized for Arabic language capabilities targeting enterprises in the MENA region. The community is exploring the impact of larger models on creative writing, intent understanding, and world knowledge, with GPT-4.5 expected to be a basis for GPT-5.
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.
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
deepseek-r1 alphageometry-2 claude deepseek openai google-deepmind anthropic langchain adyen open-source reasoning agentic-ai javascript model-release memes ai-development benchmarking akhaliq lmthang aymericroucher vikhyatk swyx
DeepSeek-R1 surpasses OpenAI in GitHub stars, marking a milestone in open-source AI with rapid growth in community interest. AlphaGeometry2 achieves gold-medalist level performance with an 84% solving rate on IMO geometry problems, showcasing significant advancements in AI reasoning. LangChain releases a tutorial for building AI agents in JavaScript, enhancing developer capabilities in agent deployment. Reflections on Anthropic's Claude model reveal early access and influence on AI development timelines. Lighthearted AI humor includes calls to ban second-order optimizers and challenges in web development longevity. The AI Engineer Summit 2025 workshops were announced, continuing community engagement and education.
How To Scale Your Model, by DeepMind
qwen-0.5 google-deepmind deepseek hugging-face transformers inference high-performance-computing robotics sim2real mixture-of-experts reinforcement-learning bias-mitigation rust text-generation open-source omarsar0 drjimfan tairanhe99 guanyashi lioronai _philschmid awnihannun clementdelangue
Researchers at Google DeepMind (GDM) released a comprehensive "little textbook" titled "How To Scale Your Model" covering modern Transformer architectures, inference optimizations beyond O(N^2) attention, and high-performance computing concepts like rooflines. The resource includes practical problems and real-time comment engagement. On AI Twitter, several key updates include the open-sourced humanoid robotics model ASAP inspired by athletes like Cristiano Ronaldo, LeBron James, and Kobe Bryant; a new paper on Mixture-of-Agents proposing the Self-MoA method for improved LLM output aggregation; training of reasoning LLMs using the GRPO algorithm from DeepSeek demonstrated on Qwen 0.5; findings on bias in LLMs used as judges highlighting the need for multiple independent evaluations; and the release of mlx-rs, a Rust library for machine learning with examples including Mistral text generation. Additionally, Hugging Face launched an AI app store featuring over 400,000 apps with 2,000 new daily additions and 2.5 million weekly visits, enabling AI-powered app search and categorization.
not much happened today
deepseek-r1 deepseek-v3 coder-v2 prover deepseek hugging-face dell openai instruction-tuning performance-benchmarks model-deployment training-costs hardware-scalability ai-safety risk-mitigation ethical-ai open-source gpu-utilization yann-lecun yoshua-bengio francois-chollet giffman
DeepSeek-R1 and DeepSeek-V3 models have made significant advancements, trained on an instruction-tuning dataset of 1.5M samples with 600,000 reasoning and 200,000 non-reasoning SFT data. The models demonstrate strong performance benchmarks and are deployed on-premise via collaborations with Dell and Hugging Face. Training costs are estimated around $5.5M to $6M, with efficient hardware utilization on 8xH100 servers. The International AI Safety Report highlights risks such as malicious use, malfunctions, and systemic risks including AI-driven cyberattacks. Industry leaders like Yann LeCun and Yoshua Bengio provide insights on market reactions, AI safety, and ethical considerations, with emphasis on AI's role in creativity and economic incentives.
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.
OpenAI launches Operator, its first Agent
operator deepseek-r1 videollama-3 llama-4 o1 claude openai anthropic deepseek-ai google-deepmind perplexity-ai computer-using-agent reasoning multimodality performance-benchmarks open-source ai-safety benchmarking video-generation model-evaluation sam-altman swyx
OpenAI launched Operator, a premium computer-using agent for web tasks like booking and ordering, available now for Pro users in the US with an API promised. It features long horizon remote VMs up to 20 minutes and video export, showing state-of-the-art agent performance but not yet human-level. Anthropic had launched a similar agent 3 months earlier as an open source demo. DeepSeek AI unveiled DeepSeek R1, an open-source reasoning model excelling on the Humanity's Last Exam dataset, outperforming models like LLaMA 4 and OpenAI's o1. Google DeepMind open-sourced VideoLLaMA 3, a multimodal foundation model for image and video understanding. Perplexity AI released Perplexity Assistant for Android with reasoning and search capabilities. The Humanity's Last Exam dataset contains 3,000 questions testing AI reasoning, with current models scoring below 10% accuracy, indicating room for improvement. OpenAI's Computer-Using Agent (CUA) shows improved performance on OSWorld and WebArena benchmarks but still lags behind humans. Anthropic AI introduced Citations for safer AI responses. Sam Altman and Swyx commented on Operator's launch and capabilities.
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.
not much happened today
cosmos nvidia openai robotics autonomous-driving open-source fine-tuning foundation-models memory-optimization sama
NVIDIA has launched Cosmos, an open-source video world model trained on 20 million hours of video, aimed at advancing robotics and autonomous driving. The release sparked debate over its open-source status and technical approach. Additionally, NVIDIA announced Digits, a $3,000 personal AI supercomputer designed to democratize AI computing. The AI community expresses mixed feelings about rapid AI progress, with concerns about AGI, job displacement, and investment hype. Discussions also highlight upcoming tools for fine-tuning AI models at home and foundation models for AI robotics.
not much happened to end the year
deepseek-v3 code-llm o1 sonnet-3.5 deepseek smol-ai reinforcement-learning reasoning training-data mixed-precision-training open-source multimodality software-development natural-language-processing interpretability developer-tools real-time-applications search sdk-generation corbtt tom_doerr cognitivecompai alexalbert__ theturingpost svpino bindureddy
Reinforcement Fine-Tuning (RFT) is introduced as a data-efficient method to improve reasoning in LLMs using minimal training data with strategies like First-Correct Solutions (FCS) and Greedily Diverse Solutions (GDS). DeepSeek-V3, a 671B parameter MoE language model trained on 14.8 trillion tokens with FP8 mixed precision training, highlights advances in large-scale models and open-source LLMs. Predictions for AI in 2025 include growth in smaller models, multimodality, and challenges in open-source AI. The impact of AI on software development jobs suggests a need for higher intelligence and specialization as AI automates low-skilled tasks. Enhancements to CodeLLM improve coding assistance with features like in-place editing and streaming responses. Natural Language Reinforcement Learning (NLRL) offers better interpretability and richer feedback for AI planning and critique. AI hiring is growing rapidly with startups seeking strong engineers in ML and systems. New AI-powered tools such as Rivet, Buzee, and Konfig improve real-time applications, search, and SDK generation using technologies like Rust and V8 isolates.
not much happened today
deepseek-v3 chatgpt-4 openai deepseek google qwen overfitting reasoning misguided-attention model-evaluation model-architecture finetuning open-source sam-altman
Sam Altman publicly criticizes DeepSeek and Qwen models, sparking debate about OpenAI's innovation claims and reliance on foundational research like the Transformer architecture. Deepseek V3 shows significant overfitting issues in the Misguided Attention evaluation, solving only 22% of test prompts, raising concerns about its reasoning and finetuning. Despite skepticism about its open-source status, Deepseek V3 is claimed to surpass ChatGPT4 as an open-source model, marking a milestone 1.75 years after ChatGPT4's release on March 14, 2023. The discussions highlight competitive dynamics in AI model performance and innovation sustainability.
Genesis: Generative Physics Engine for Robotics (o1-2024-12-17)
o1 gemini-2.0-pro openai google carnegie-mellon-university universal-physics-engine robotics-simulation physics-simulation photo-realistic-rendering generative-data simulation-platform open-source function-calling vision performance-benchmarks sdk realtime-api zhou-xian aidan_mclau sundar-pichai
Genesis is a newly announced universal physics engine developed by a large-scale collaboration led by CMU PhD student Zhou Xian. It integrates multiple state-of-the-art physics solvers to simulate diverse materials and physical phenomena, targeting robotics applications with features like lightweight, ultra-fast simulation, photo-realistic rendering, and generative data capabilities. The engine is open source and designed for robotics simulation beyond just video generation. Additionally, OpenAI released the o1 model to API with advanced features like function calling and vision support, showing strong math and coding performance. Google teased updates on Gemini 2.0 Pro, accelerating deployment for advanced users.
LMSys killed Model Versioning (gpt 4o 1120, gemini exp 1121)
gpt-4o-2024-11-20 gemini-exp-1121 deepseek-r1 openai google-deepmind anthropic deepseek mistral-ai model-release model-ranking open-source vision coding reasoning market-competition
AI News for 11/21/2024-11/22/2024 highlights the intense frontier lab race with OpenAI's gpt-4o-2024-11-20 and Google DeepMind's gemini-exp-1121 trading top spots on the Lmsys leaderboard. The trend of using date-based model identifiers instead of traditional versioning is noted across leading labs including Anthropic. DeepSeek R1 is gaining attention as a potent open-source alternative, especially in the context of the AI competition between China and the US. Gemini-Exp-1121 is praised for improvements in vision, coding, and reasoning, while MistralAI expands with a new Palo Alto office, signaling growth and hiring.
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
grok-beta llama-3-1-70b claude-3-5-haiku claude-3-opus llama-3 chatgpt gemini meta-ai-fair scale-ai anthropic perplexity-ai langchainai weights-biases qwen pricing national-security defense open-source agentic-ai retrieval-augmented-generation election-predictions real-time-updates annotation ai-ecosystem memes humor alexandr_wang svpino aravsrinivas bindureddy teortaxestex jessechenglyu junyang-lin cte_junior jerryjliu0
Grok Beta surpasses Llama 3.1 70B in intelligence but is less competitive due to its pricing at $5/1M input tokens and $15/1M output tokens. Defense Llama, developed with Meta AI and Scale AI, targets American national security applications. SWE-Kit, an open-source framework, supports building customizable AI software engineers compatible with Llama 3, ChatGPT, and Claude. LangChainAI and Weights & Biases integrate to improve retrievers and reduce hallucinations in RAG applications using Gemini. Perplexity AI offers enhanced election tracking tools for the 2024 elections, including live state results and support for Claude 3.5 Haiku. AI Talk launched featuring discussions on Chinese AI labs with guests from Qwen. Memes highlight Elon Musk and humorous AI coding mishaps.
DeepSeek Janus and Meta SpiRit-LM: Decoupled Image and Expressive Voice Omnimodality
nemotron-70b claude claude-3.5-sonnet gpt-4o deepseek meta-ai-fair wandb nvidia anthropic hugging-face perplexity-ai multimodality image-generation speech-synthesis fine-tuning model-merging benchmarking open-source model-optimization reinforcement-learning bindureddy aravsrinivas danielhanchen clementdelangue cwolferesearch
DeepSeek Janus and Meta SpiRit-LM are two notable multimodality AI models recently released, showcasing advances in image generation and speech synthesis respectively. DeepSeek Janus separates vision encoders for image understanding and generation, achieving better results in both tasks. Meta's SpiRit-LM introduces an expressive speech and writing model generating pitch and style units, improving over standard TTS. Additionally, W&B Weave offers comprehensive LLM observability and multimodality fine-tuning tools. Industry updates include Nvidia's Nemotron 70b model underperforming, Meta open-sourcing Movie Gen Bench for media generation benchmarking, Perplexity launching internal search with multi-step reasoning, and Anthropic updating Claude apps. Open source progress includes Hugging Face's gradient accumulation fix in transformers and advocacy for open source AI to prevent Big Tech dominance. "Model merging for combining skills of multiple models" is also highlighted.
Did Nvidia's Nemotron 70B train on test?
nemotron-70b llama-3.1-70b llama-3.1 ministral-3b ministral-8b gpt-4o claude-3.5-sonnet claude-3.5 nvidia mistral-ai hugging-face zep benchmarking reinforcement-learning reward-models temporal-knowledge-graphs memory-layers context-windows model-releases open-source reach_vb philschmid swyx
NVIDIA's Nemotron-70B model has drawn scrutiny despite strong benchmark performances on Arena Hard, AlpacaEval, and MT-Bench, with some standard benchmarks like GPQA and MMLU Pro showing no improvement over the base Llama-3.1-70B. The new HelpSteer2-Preference dataset improves some benchmarks with minimal losses elsewhere. Meanwhile, Mistral released Ministral 3B and 8B models featuring 128k context length and outperforming Llama-3.1 and GPT-4o on various benchmarks under the Mistral Commercial License. NVIDIA's Nemotron 70B also surpasses GPT-4o and Claude-3.5-Sonnet on key benchmarks using RLHF (REINFORCE) training. Additionally, Zep introduced Graphiti, an open-source temporal knowledge graph memory layer for AI agents, built on Neo4j.
The AI Nobel Prize
claude-3.5-sonnet reka-flash got openai anthropic reka-ai zep artificial-neural-networks nobel-prize knowledge-graphs memory-layers real-time-voice-api vision fine-tuning prompt-caching multimodality function-calling ocr open-source single-sign-on software-testing ai-assisted-coding ai-ethics geoff-hinton john-hopfield philschmid alexalbert mervenoyann clementdelangue svpino bindureddy ylecun rohanpaul_ai
Geoff Hinton and John Hopfield won the Nobel Prize in Physics for their work on Artificial Neural Networks. The award citation spans 14 pages highlighting their contributions. Zep released a new community edition of their low-latency memory layer for AI agents, emphasizing knowledge graphs for memory. At OpenAI's DevDay, new features like real-time voice API, vision model fine-tuning, and prompt caching with a 50% discount on reused tokens were introduced. Anthropic's Claude 3.5 Sonnet was recognized as the best model currently. Reka AI Labs updated their Reka Flash model with enhanced multimodal and function calling capabilities. The GOT (Generic OCR Transformer) achieved 98.79% accuracy on OCR benchmarks. Discussions on open-source AI models highlighted their role in fostering competition and decentralization. Software development insights included the importance of Single Sign-On (SSO), thorough testing, and AI-assisted coding workflows. Ethical and societal topics covered critiques of tax policies and the appointment of France's first Minister of AI.
Liquid Foundation Models: A New Transformers alternative + AINews Pod 2
llama-3-2 gemini-1.5-pro-002 gemini-1.5-flash-002 liquid-ai meta-ai-fair google-deepmind openai reinforcement-learning multimodality model-efficiency foundation-models audio-processing model-deployment open-source ylecun svpino
Liquid.ai emerged from stealth with three subquadratic foundation models demonstrating superior efficiency compared to state space models and Apple’s on-device and server models, backed by a $37M seed round. Meta AI announced Llama 3.2 with multimodal vision-enabled models and lightweight text-only variants for mobile. Google DeepMind introduced production-ready Gemini-1.5-Pro-002 and Gemini-1.5-Flash-002 models with improved pricing and rate limits, alongside AlphaChip, an AI-driven chip design system using reinforcement learning for rapid superhuman layouts. OpenAI enhanced ChatGPT Plus and Teams with Advanced Voice Mode featuring Custom Instructions, Memory, and new nature-inspired voices. California Governor vetoed SB-1047 AI regulation bill, celebrated by AI community figures like ylecun and svpino as a win for open-source AI. Google upgraded NotebookLM with audio overviews supporting YouTube and audio files, turning documents into AI-generated podcasts. "Open source in AI is thriving," noted ylecun, highlighting 1 million models on Github and HuggingFace.
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.
not much happened today
o1-preview o1-mini qwen-2.5 gpt-4o deepseek-v2.5 gpt-4-turbo-2024-04-09 grin llama-3-1-405b veo kat openai qwen deepseek-ai microsoft kyutai-labs perplexity-ai together-ai meta-ai-fair google-deepmind hugging-face google anthropic benchmarking math coding instruction-following model-merging model-expressiveness moe voice voice-models generative-video competition open-source model-deployment ai-agents hyung-won-chung noam-brown bindureddy akhaliq karpathy aravsrinivas fchollet cwolferesearch philschmid labenz ylecun
OpenAI's o1-preview and o1-mini models lead benchmarks in Math, Hard Prompts, and Coding. Qwen 2.5 72B model shows strong performance close to GPT-4o. DeepSeek-V2.5 tops Chinese LLMs, rivaling GPT-4-Turbo-2024-04-09. Microsoft's GRIN MoE achieves good results with 6.6B active parameters. Moshi voice model from Kyutai Labs runs locally on Apple Silicon Macs. Perplexity app introduces voice mode with push-to-talk. LlamaCoder by Together.ai uses Llama 3.1 405B for app generation. Google DeepMind's Veo is a new generative video model for YouTube Shorts. The 2024 ARC-AGI competition increases prize money and plans a university tour. A survey on model merging covers 50+ papers for LLM alignment. The Kolmogorov–Arnold Transformer (KAT) paper proposes replacing MLP layers with KAN layers for better expressiveness. Hugging Face Hub integrates with Google Cloud Vertex AI Model Garden for easier open-source model deployment. Agent.ai is introduced as a professional network for AI agents. "Touching grass is all you need."
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.
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.
not much happened today
qwen2-math-72b gpt-4o claude-3.5-sonnet gemini-1.5-pro llama-3.1-405b idefics3-llama-8b anthropic google mistral-ai llamaindex math fine-tuning synthetic-data reinforcement-learning bug-bounty visual-question-answering open-source retrieval-augmented-generation agentic-ai ai-safety policy rohanpaul_ai anthropicai mervenoyann jeremyphoward omarsar0 ylecun bindureddy
Qwen2-Math-72B outperforms GPT-4o, Claude-3.5-Sonnet, Gemini-1.5-Pro, and Llama-3.1-405B on math benchmarks using synthetic data and advanced optimization techniques. Google AI cuts pricing for Gemini 1.5 Flash by up to 78%. Anthropic expands its bug bounty program targeting universal jailbreaks in next-gen safety systems. Tutorial on QLoRA fine-tuning of IDEFICS3-Llama 8B for visual question answering released. A Chinese open weights model surpasses previous MATH benchmark records. Surveys on Mamba models and LLM-based agents for software engineering highlight advancements and applications. Open-source tools like R2R RAG engine and LlamaIndex Workflows simplify building complex AI applications. Mistral AI introduces customizable AI agents. Concerns raised about California bill SB 1047's focus on existential risk and debates on banning open-source AI. Memes and humor continue in AI communities.
not much happened today
sam-2 gemini-1.5-pro chatgpt midjourney-v6.1 meta-ai-fair google-deepmind scale-ai apple canva hugging-face object-segmentation quantization web-development-framework adversarial-robustness on-device-ai open-source robotics voice vision jeremyphoward demis-hassabis ylecun maartengrootendorst jimfan
Meta released SAM 2, a unified model for real-time object segmentation with a new dataset 4.5x larger and 53x more annotated than previous ones. FastHTML, a new Python web framework by Jeremy Howard, enables easy creation and deployment of interactive web apps. Scale AI launched the SEAL Leaderboard on adversarial robustness, topped by Gemini 1.5 Pro from Google DeepMind. Apple published a technical report on their Intelligence Foundation Language Models for on-device and server use. Yann LeCun emphasized the importance of open source AI in an article co-authored with Martin Casado and Ion Stoica. Maarten Grootendorst's "Visual Guide to Quantization" on efficient LLM inference went viral. ChatGPT started rolling out advanced voice and vision-enabled modes to select users. Leonardo AI was acquired by Canva. Jim Fan shared insights on Project Groot augmenting human demonstration data for robotics. Midjourney v6.1 was released.
Mini, Nemo, Turbo, Lite - Smol models go brrr (GPT4o-mini version)
gpt-4o-mini deepseek-v2-0628 mistral-nemo llama-8b openai deepseek-ai mistral-ai nvidia meta-ai-fair hugging-face langchain keras cost-efficiency context-windows open-source benchmarking neural-networks model-optimization text-generation fine-tuning developer-tools gpu-support parallelization cuda-integration multilinguality long-context article-generation liang-wenfeng
OpenAI launched the GPT-4o Mini, a cost-efficient small model priced at $0.15 per million input tokens and $0.60 per million output tokens, aiming to replace GPT-3.5 Turbo with enhanced intelligence but some performance limitations. DeepSeek open-sourced DeepSeek-V2-0628, topping the LMSYS Chatbot Arena Leaderboard and emphasizing their commitment to contributing to the AI ecosystem. Mistral AI and NVIDIA released the Mistral NeMo, a 12B parameter multilingual model with a record 128k token context window under an Apache 2.0 license, sparking debates on benchmarking accuracy against models like Meta Llama 8B. Research breakthroughs include the TextGrad framework for optimizing compound AI systems via textual feedback differentiation and the STORM system improving article writing by 25% through simulating diverse perspectives and addressing source bias. Developer tooling trends highlight LangChain's evolving context-aware reasoning applications and the Modular ecosystem's new official GPU support, including discussions on Mojo and Keras 3.0 integration.
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.
DeepSeek-V2 beats Mixtral 8x22B with >160 experts at HALF the cost
deepseek-v2 llama-3-120b llama-3-400b gpt-4 mistral phi claude gemini mai-1 med-gemini deepseek-ai mistral-ai microsoft openai scale-ai tesla nvidia google-deepmind mixture-of-experts multi-head-attention model-inference benchmarking overfitting robotics teleoperation open-source multimodality hallucination-detection fine-tuning medical-ai model-training erhartford maximelabonne bindureddy adcock_brett drjimfan clementdelangue omarsar0 rohanpaul_ai
DeepSeek V2 introduces a new state-of-the-art MoE model with 236B parameters and a novel Multi-Head Latent Attention mechanism, achieving faster inference and surpassing GPT-4 on AlignBench. Llama 3 120B shows strong creative writing skills, while Microsoft is reportedly developing a 500B parameter LLM called MAI-1. Research from Scale AI highlights overfitting issues in models like Mistral and Phi, whereas GPT-4, Claude, Gemini, and Llama maintain benchmark robustness. In robotics, Tesla Optimus advances with superior data collection and teleoperation, LeRobot marks a move toward open-source robotics AI, and Nvidia's DrEureka automates robot skill training. Multimodal LLM hallucinations are surveyed with new mitigation strategies, and Google's Med-Gemini achieves SOTA on medical benchmarks with fine-tuned multimodal models.
Apple's OpenELM beats OLMo with 50% of its dataset, using DeLighT
openelm llama-3 llama-3-8b-instruct llama-3-70b apple meta-ai-fair google layer-wise-scaling context-length quantization ai-alignment open-source ai-regulation eric-schmidt sebastian-raschka
Apple advances its AI presence with the release of OpenELM, its first relatively open large language model available in sizes from 270M to 3B parameters, featuring a novel layer-wise scaling architecture inspired by the DeLight paper. Meanwhile, Meta's LLaMA 3 family pushes context length boundaries with models supporting over 160K tokens and an 8B-Instruct model with 262K context length released on Hugging Face, alongside performance improvements in quantized versions. A new paper on AI alignment highlights KTO as the best-performing method, with sensitivity to training data volume noted. In AI ethics and regulation, former Google CEO Eric Schmidt warns about the risks of open-source AI empowering bad actors and geopolitical rivals, while a U.S. proposal aims to enforce "Know Your Customer" rules to end anonymous cloud usage.
Snowflake Arctic: Fully Open 10B+128x4B Dense-MoE Hybrid LLM
snowflake-arctic phi-3 llama-3-70b llama-3 stable-diffusion-3 sd3-turbo gpt-3.5-turbo snowflake databricks deepseek deepspeed nvidia stable-diffusion adobe apple llamaindex lmsys openai mixture-of-experts curriculum-learning model-release image-generation video-upscaling quantization inference-speed benchmarking model-comparison open-source on-device-ai
Snowflake Arctic is a notable new foundation language model released under Apache 2.0, claiming superiority over Databricks in data warehouse AI applications and adopting a mixture-of-experts architecture inspired by DeepSeekMOE and DeepSpeedMOE. The model employs a 3-stage curriculum training strategy similar to the recent Phi-3 paper. In AI image and video generation, Nvidia introduced the Align Your Steps technique improving image quality at low step counts, while Stable Diffusion 3 and SD3 Turbo models were compared for prompt understanding and image quality. Adobe launched an AI video upscaling project enhancing blurry videos to HD, though with some high-resolution artifacts. Apple released open-source on-device language models with code and training logs, diverging from typical weight-only releases. The Llama-3-70b model ties for first place on the LMSYS leaderboard for English queries, and Phi-3 (4B params) outperforms GPT-3.5 Turbo in the banana logic benchmark. Fast inference and quantization of Llama 3 models were demonstrated on MacBook devices.
Multi-modal, Multi-Aspect, Multi-Form-Factor AI
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Between April 12-15, Reka Core launched a new GPT4-class multimodal foundation model with a detailed technical report described as "full Shazeer." Cohere Compass introduced a foundation embedding model for indexing and searching multi-aspect enterprise data like emails and invoices. The open-source IDEFICS 2-8B model continues Google's Flamingo multimodal model reproduction. Rewind pivoted to a multi-platform app called Limitless, moving away from spyware. Reddit discussions highlighted Apple MLX outperforming Ollama and Mistral Instruct on M2 Ultra GPUs, GPU choices for LLMs and Stable Diffusion, and AI-human comparisons by Microsoft Research's Chris Bishop. Former PayPal CEO Dan Schulman predicted GPT-5 will drastically reduce job scopes by 80%. Mistral CEO Arthur Mensch criticized the obsession with AGI as "creating God."
Music's Dall-E moment
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Google's Griffin architecture outperforms transformers with faster inference and lower memory usage on long contexts. Command R+ climbs to 6th place on the LMSYS Chatbot Arena leaderboard, surpassing GPT-4-0613 and GPT-4-0314. Mistral AI releases an open-source 8x22B model with a 64K context window and around 130B total parameters. Google open-sources CodeGemma models with pre-quantized 4-bit versions for faster downloads. Ella weights enhance Stable Diffusion 1.5 with LLM for semantic alignment. Unsloth enables 4x larger context windows and 80% memory reduction for finetuning. Andrej Karpathy releases LLMs implemented in pure C for potential performance gains. Command R+ runs in realtime on M2 Max MacBook using iMat q1 quantization. Cohere's Command R model offers low API costs and strong leaderboard performance. Gemini 1.5 impresses with audio capabilities recognizing speech tone and speaker identification from audio clips.
ReALM: Reference Resolution As Language Modeling
flan-t5 gpt-4 apple openai hugging-face stability-ai reference-resolution finetuning quantization retrieval-augmented-generation open-source coding-agents podcast-generation image-generation ai-industry-trends takuto-takizawa
Apple is advancing in AI with a new approach called ReALM: Reference Resolution As Language Modeling, which improves understanding of ambiguous references using three contexts and finetunes a smaller FLAN-T5 model that outperforms GPT-4 on this task. In Reddit AI news, an open-source coding agent SWE-agent achieves 12.29% on the SWE-bench benchmark, and RAGFlow introduces a customizable retrieval-augmented generation engine. A new quantization method, QuaRot, enables efficient 4-bit inference. AI applications include a t-shirt design generator, podgenai for GPT-4 based podcast generation, and an open-source model from HuggingFace that runs without a GPU. Industry discussions focus on the impact of large language models on the AI field and efforts to decentralize AI development. Takuto Takizawa joins Stability AI Japan as Head of Sales & Partnerships.
Grok-1 in Bio
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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.
MM1: Apple's first Large Multimodal Model
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Apple announced the MM1 multimodal LLM family with up to 30B parameters, claiming performance comparable to Gemini-1 and beating larger older models on VQA benchmarks. The paper targets researchers and hints at applications in embodied agents and business/education. Yann LeCun emphasized that human-level AI requires understanding the physical world, memory, reasoning, and hierarchical planning, while Fran ois Chollet cautioned that NLP is far from solved despite LLM advances. Cohere released Command-R, a model for Retrieval Augmented Generation, and Anthropic highlighted the Claude 3 family (Opus, Sonnet, Haiku) for various application needs. Open-source hardware DexCap enables dexterous robot manipulation data collection affordably. Tools like CopilotKit simplify AI integration into React apps, and migration to Keras 3 with JAX backend offers faster training. New projects improve reranking for retrieval and add financial agents to LangChain. The content includes insights on AI progress, new models, open-source tools, and frameworks.
Welcome Interconnects and OpenRouter
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Discord communities analyzed 22 guilds, 349 channels, and 12885 messages revealing active discussions on model comparisons and optimizations involving Mistral AI, Miqu, and GGUF quantized models. Highlights include comparing Mistral Large with GPT-4, focusing on cost-effectiveness and performance, and exploring quantization techniques like GPTQ and QLORA to reduce VRAM usage. Advanced applications such as role-playing, story-writing, code clarity, and AI-assisted decompilation were emphasized, alongside development of tools like an asynchronous summarization script for Mistral 7b. The intersection of quantum computing and AI was discussed, including DARPA-funded projects and encoder-based diffusion techniques for image processing. Community efforts featured new Spanish LLM announcements, hardware experimentation, and open-source initiatives, with platforms like Perplexity AI and LlamaIndex noted for innovation and integration. Speculation about Mistral AI's open-source commitment and tools like R2R for rapid RAG deployment highlighted collaborative spirit.
Karpathy emerges from stealth?
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Andrej Karpathy released a comprehensive 2-hour tutorial on tokenization, detailing techniques up to GPT-4's tokenizer and noting the complexity of Llama 2 tokenization with SentencePiece. Discussions in AI Discord communities covered model optimization and efficiency, focusing on quantization of models like Mistral 7B and Zephyr-7B to reduce memory usage for consumer GPUs, including Intel's new weight-only quantization algorithm. Efforts to improve computational efficiency included selective augmentation reducing costs by 57.76% and memory token usage versus kNN for Transformers. Challenges in hardware compatibility and software issues were shared, alongside fine-tuning techniques such as LoRA and model merging. Innovative applications of LLMs in retrieval-augmented generation (RAG), multi-model learning, and meta-reasoning were explored. The community emphasized dataset sharing, open-source releases like SDXL VAE encoded datasets and Audiogen AI codecs, and ethical AI use with censorship and guardrails. Collaboration and resource sharing remain strong in these AI communities.
Companies liable for AI hallucination is Good Actually for AI Engineers
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Air Canada faced a legal ruling requiring it to honor refund policies communicated by its AI chatbot, setting a precedent for corporate liability in AI engineering accuracy. The tribunal ordered a refund of $650.88 CAD plus damages after the chatbot misled a customer about bereavement travel refunds. Meanwhile, AI community discussions highlighted innovations in quantization techniques for GPU inference, Retrieval-Augmented Generation (RAG) and fine-tuning of LLMs, and CUDA optimizations for PyTorch models. New prototype models like Mistral-Next and the Large World Model (LWM) were introduced, showcasing advances in handling large text contexts and video generation with models like Sora. Ethical and legal implications of AI autonomy were debated alongside challenges in dataset management. Community-driven projects such as the open-source TypeScript agent framework bazed-af emphasize collaborative AI development. Additionally, benchmarks like BABILong for up to 10M context evaluation and tools from karpathy were noted.
AI gets Memory
miqumaid-v2-70b mixtral-8x7b-qlora mistral-7b phi-2 medalpaca aya openai langchain thebloke cohere unsloth-ai mistral-ai microsoft rag memory-modeling context-windows open-source finetuning sequential-fine-tuning direct-preference-optimization rlhf ppo javascript-python-integration hardware-optimization gpu-overclocking quantization model-training large-context multilinguality joanne-jang
AI Discords analysis covered 20 guilds, 312 channels, and 6901 messages. The report highlights the divergence of RAG style operations for context and memory, with implementations like MemGPT rolling out in ChatGPT and LangChain. The TheBloke Discord discussed open-source large language models such as the Large World Model with contexts up to 1 million tokens, and the Cohere aya model supporting 101 languages. Roleplay-focused models like MiquMaid-v2-70B were noted for performance improvements with enhanced hardware. Finetuning techniques like Sequential Fine-Tuning (SFT) and Direct Preference Optimization (DPO) were explained, with tools like Unsloth AI's apply_chat_template preferred over Alpaca. Integration of JavaScript and Python via JSPyBridge in the SillyTavern project was also discussed. Training challenges with Mixtral 8x7b qlora versus Mistral 7b were noted. The LM Studio Discord focused on hardware limitations affecting large model loading, medical LLMs like medAlpaca, and hardware discussions around GPU upgrades and overclocking. Anticipation for IQ3_XSS 1.5 bit quantization support in LM Studio was expressed.
The Core Skills of AI Engineering
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AI Discords for 2/2/2024 analyzed 21 guilds, 312 channels, and 4782 messages saving an estimated 382 minutes of reading time. Discussions included Eugene Yan initiating a deep dive into AI engineering challenges, highlighting overlaps between software engineering and data science skills. The TheBloke Discord featured talks on MiquMaid, OLMo (an open-source 65B LLM by AI2 under Apache 2.0), Aphrodite model batching, AWQ quantization, and LoRA fine-tuning techniques like QLoRA and LoftQ. The LAION Discord discussed SSD-1B distillation issues, data quality optimization with captioning datasets like BLIP, COCO, and LLaVA, and tokenization strategies for prompt adherence in image generation. Other topics included AI security with watermarking, superconductors and carbon nanotubes for hardware, and deployment of LLMs via Hugging Face tools.
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.
12/11/2023: Mixtral beats GPT3.5 and Llama2-70B
mixtral-8x7b gpt-4 gpt-3.5-turbo llama-3 openhermes-2.5 llava-v1.5-13b-gptq mistral-ai openai huggingface sparse-mixture-of-experts fine-tuning quantization gpu-hardware transformers model-deployment open-source coding-datasets
Mistral AI announced the Mixtral 8x7B model featuring a Sparse Mixture of Experts (SMoE) architecture, sparking discussions on its potential to rival GPT-4. The community debated GPU hardware options for training and fine-tuning transformer models, including RTX 4070s, A4500, RTX 3090s with nvlink, and A100 GPUs. Interest was expressed in fine-tuning Mixtral and generating quantized versions, alongside curating high-quality coding datasets. Resources shared include a YouTube video on open-source model deployment, an Arxiv paper, GitHub repositories, and a blog post on Mixture-of-Experts. Discussions also touched on potential open-source releases of GPT-3.5 Turbo and llama-3, and running OpenHermes 2.5 on Mac M3 Pro with VRAM considerations.
12/10/2023: not much happened today
mixtral-8x7b-32kseqlen mistral-7b stablelm-zephyr-3b openhermes-2.5-neural-chat-v3-3-slerp gpt-3.5 gpt-4 nous-research openai mistral-ai hugging-face ollama lm-studio fine-tuning mixture-of-experts model-benchmarking inference-optimization model-evaluation open-source decentralized-ai gpu-optimization community-engagement andrej-karpathy yann-lecun richard-blythman gabriel-syme pradeep1148 cyborg_1552
Nous Research AI Discord community discussed attending NeurIPS and organizing future AI events in Australia. Highlights include interest in open-source and decentralized AI projects, with Richard Blythman seeking co-founders. Users shared projects like Photo GPT AI and introduced StableLM Zephyr 3B. The Mixtral model, based on Mistral, sparked debate on performance and GPU requirements, with comparisons to GPT-3.5 and potential competitiveness with GPT-4 after fine-tuning. Tools like Tensorboard, Wandb, and Llamahub were noted for fine-tuning and evaluation. Discussions covered Mixture of Experts (MoE) architectures, fine-tuning with limited data, and inference optimization strategies for ChatGPT. Memes and community interactions referenced AI figures like Andrej Karpathy and Yann LeCun. The community also shared resources such as GitHub links and YouTube videos related to these models and tools.
12/8/2023 - Mamba v Mistral v Hyena
mistral-8x7b-moe mamba-3b stripedhyena-7b claude-2.1 gemini gpt-4 dialogrpt-human-vs-machine cybertron-7b-v2-gguf falcon-180b mistral-ai togethercompute stanford anthropic google hugging-face mixture-of-experts attention-mechanisms prompt-engineering alignment image-training model-deployment gpu-requirements cpu-performance model-inference long-context model-evaluation open-source chatbots andrej-karpathy tri-dao maxwellandrews raddka
Three new AI models are highlighted: Mistral's 8x7B MoE model (Mixtral), Mamba models up to 3B by Together, and StripedHyena 7B, a competitive subquadratic attention model from Stanford's Hazy Research. Discussions on Anthropic's Claude 2.1 focus on its prompting technique and alignment challenges. The Gemini AI from Google is noted as potentially superior to GPT-4. The community also explores Dreambooth for image training and shares resources like the DialogRPT-human-vs-machine model on Hugging Face. Deployment challenges for large language models, including CPU performance and GPU requirements, are discussed with references to Falcon 180B and transformer batching techniques. User engagement includes meme sharing and humor.