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Person: "osanseviero"
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.
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.
Prime Intellect's INTELLECT-2 and PRIME-RL advance distributed reinforcement learning
intellect-2 dreamo qwen gemini-2.5-pro dynamic-byte-latent-transformer gen-4-references mistral-medium-3 le-chat-enterprise primeintellect bytedance qwen gemma meta-ai-fair runwayml mistral-ai google distributed-training reinforcement-learning gpu-clusters model-optimization quantization multimodality agentic-ai video-understanding fine-tuning _akhaliq reach_vb osanseviero aiatmeta c_valenzuelab lmarena_ai adcock_brett
Prime Intellect released INTELLECT-2, a decentralized GPU training and RL framework with a vision for distributed AI training overcoming colocation limits. ByteDance launched DreamO, a unified image customization model on Hugging Face. Qwen released models optimized for GPTQ, GGUF, and AWQ quantization. Gemma surpassed 150 million downloads on Hugging Face. Meta released weights for the Dynamic Byte Latent Transformer and the Collaborative Reasoner framework to improve language model efficiency and reasoning. RunwayML introduced Gen-4 References, a near-realtime model requiring no fine-tuning. Mistral AI released Mistral Medium 3, a strong multimodal model, and Le Chat Enterprise, an agentic AI assistant for business. Google updated Gemini 2.5 Pro Preview with video understanding and UI improvements. "Airbnb for spare GPUs from all over the world" highlights the ongoing challenges and potential of distributed GPU training.
not much happened today
nemotron-h nvidia-eagle-2.5 gpt-4o qwen2.5-vl-72b gemini-2.5-flash gemini-2.0-pro gemini-exp-1206 gemma-3 qwen2.5-32b deepseek-r1-zero-32b uni3c seedream-3.0 adobe-dragon kimina-prover qwen2.5-72b bitnet-b1.58-2b4t nvidia deepseek hugging-face alibaba bytedance adobe transformers model-optimization multimodality long-context reinforcement-learning torch-compile image-generation diffusion-models distributional-rewards model-efficiency model-training native-quantization sampling-techniques philschmid arankomatsuzaki osanseviero iScienceLuvr akhaliq
Nemotron-H model family introduces hybrid Mamba-Transformer models with up to 3x faster inference and variants including 8B, 56B, and a compressed 47B model. Nvidia Eagle 2.5 is a frontier VLM for long-context multimodal learning, matching GPT-4o and Qwen2.5-VL-72B on long-video understanding. Gemini 2.5 Flash shows improved dynamic thinking and cost-performance, outperforming previous Gemini versions. Gemma 3 now supports torch.compile for about 60% faster inference on consumer GPUs. SRPO using Qwen2.5-32B surpasses DeepSeek-R1-Zero-32B on benchmarks with reinforcement learning only. Alibaba's Uni3C unifies 3D-enhanced camera and human motion controls for video generation. Seedream 3.0 by ByteDance is a bilingual image generation model with high-resolution outputs up to 2K. Adobe DRAGON optimizes diffusion generative models with distributional rewards. Kimina-Prover Preview is an LLM trained with reinforcement learning from Qwen2.5-72B, achieving 80.7% pass@8192 on miniF2F. BitNet b1.58 2B4T is a native 1-bit LLM with 2B parameters trained on 4 trillion tokens, matching full-precision LLM performance with better efficiency. Antidistillation sampling counters unwanted model distillation by modifying reasoning traces from frontier models.
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.
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.
not much happened today
aria o1-preview o1-mini gemini-1.5-pro gemini-1.5-flash gemini-1.5 claude-3.5-sonnet rhymes-ai openai anthropic google meta-ai-fair oxylabs multimodality mixture-of-experts long-context retrieval-augmented-generation benchmarking software-engineering llm-evaluation prompt-engineering web-scraping python production-applications mervenoyann osanseviero dbrxmosaicai ylecun ofirpress clefourrier omarsar0 rohanpaul_ai svpino finbarrtimbers _philschmid
Rhymes AI released Aria, a new 25.3B parameter multimodal MoE model supporting text, code, image, and video with a 64k token context window and Apache-2.0 license. OpenAI's o1-preview and o1-mini models show consistent improvement over Anthropic and Google Gemini 1.5 Pro/Flash on long context RAG benchmarks up to 128k tokens, while Google Gemini 1.5 models excel at extreme context lengths up to 2 million tokens. Meta AI expanded rollout to 21 countries with new language support but remains unavailable in the EU. The one-year anniversary of SWE-bench benchmark for software engineering tasks was celebrated, alongside the introduction of SWE-bench Multimodal. New AI tools include OxyCopilot by Oxylabs for web scraping, Taipy for Python-based production apps, and Latitude for prompt engineering. Industry insights highlight changing AI funding dynamics and OpenAI's strategic focus on consumer products like ChatGPT. "all recaps done by Claude 3.5 Sonnet, best of 4 runs."
not much happened today
llama-3-2 llama-3 molmo meta-ai-fair google-deepmind hugging-face on-device-ai multimodality chip-design retrieval-augmented-generation rag benchmarking reliability ai-regulation free-speech pytorch-optimization demis-hassabis clementdelangue svpino awnihannun osanseviero omarsar0 sarahookr ylecun
Meta released Llama 3.2, including lightweight 1B and 3B models for on-device AI with capabilities like summarization and retrieval-augmented generation. Molmo, a new multimodal model, was introduced with a large dense captioning dataset. Google DeepMind announced AlphaChip, an AI-driven chip design method improving TPU and CPU designs. Hugging Face surpassed 1 million free public models, highlighting the value of smaller specialized models. Discussions covered challenges in scaling RAG applications, the future of on-device AI running ChatGPT-level models, reliability issues in larger LLMs, and new Elo benchmarking accepted at NeurIPS 2024. AI ethics and regulation topics included free speech responsibilities and California's SB-1047 bill potentially affecting open-source AI. "AlphaChip transformed computer chip design," and "ChatGPT-level AI on mobile devices predicted within a year."
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.
AlphaProof + AlphaGeometry2 reach 1 point short of IMO Gold
gemini alphageometry-2 alphaproof llama-3-1-405b llama-3-70b llama-3-8b mistral-large-2 google-deepmind meta-ai-fair mistral-ai neurosymbolic-ai mathematical-reasoning synthetic-data knowledge-sharing model-fine-tuning alpha-zero multilinguality context-windows model-scaling benchmarking performance-comparison tim-gowers guillaume-lample osanseviero
Search+Verifier highlights advances in neurosymbolic AI during the 2024 Math Olympics. Google DeepMind's combination of AlphaProof and AlphaGeometry 2 solved four out of six IMO problems, with AlphaProof being a finetuned Gemini model using an AlphaZero approach, and AlphaGeometry 2 trained on significantly more synthetic data with a novel knowledge-sharing mechanism. Despite impressive results, human judges noted the AI required much longer time than human competitors. Meanwhile, Meta AI released Llama 3.1 with a 405B parameter model and smaller variants, and Mistral AI launched Mistral Large 2 with 123B parameters and 128k context windows, outperforming Llama 3.1 on coding tasks and multilingual benchmarks. This marks significant progress in AI mathematical reasoning, model scaling, and multilingual capabilities.
GraphRAG: The Marriage of Knowledge Graphs and RAG
gemma-2 llama-3-70b claude-3.5-sonnet nemotron-340b qwen2-72b llama-3 microsoft-research anthropic nvidia hugging-face retrieval-augmented-generation knowledge-graphs token-usage inference-time attention-mechanisms instruction-following coding math long-range-reasoning synthetic-data dataset-release fine-tuning context-windows function-calling travis-fischer rasbt alexandr-wang osanseviero rohanpaul_ai hamelhusain svpino aaaazzam omarsar0
Microsoft Research open sourced GraphRAG, a retrieval augmented generation (RAG) technique that extracts knowledge graphs from sources and clusters them for improved LLM answers, though it increases token usage and inference time. Gemma 2 models were released focusing on efficient small LLMs with innovations like sliding window attention and RMS norm, nearly matching the larger Llama 3 70B. Anthropic's Claude 3.5 Sonnet leads in instruction following and coding benchmarks, while Nvidia's Nemotron 340B model was released in June. Qwen2-72B tops the HuggingFace Open LLM leaderboard excelling in math and long-range reasoning. Discussions on RAG highlighted its limitations and improvements in context usage via function calls. A persona-driven synthetic data generation approach introduced 1 billion personas, with a fine-tuned model matching GPT-4 performance on math benchmarks at 7B scale. The 200GB AutoMathText dataset was also noted for math data synthesis.
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.
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.
The Era of 1-bit LLMs
bitnet-b1.58 hugging-face quantization model-optimization energy-efficiency fine-tuning robotics multimodality ai-security ethics humor swyx levelsio gdb npew _akhaliq osanseviero mmitchell_ai deliprao nearcyan clementdelangue
The Era of 1-bit LLMs research, including the BitNet b1.58 model, introduces a ternary parameter approach that matches full-precision Transformer LLMs in performance while drastically reducing energy costs by 38x. This innovation promises new scaling laws and hardware designs optimized for 1-bit LLMs. Discussions on AI Twitter highlight advances in AGI societal impact, robotics with multimodal models, fine-tuning techniques like ResLoRA, and AI security efforts at Hugging Face. Ethical considerations in generative AI and humor within the AI community are also prominent topics.
12/25/2023: Nous Hermes 2 Yi 34B for Christmas
nous-hermes-2 yi-34b nucleusx yayi-2 ferret teknim nous-research apple mixtral deepseek qwen huggingface wenge-technology quantization model-optimization throughput-metrics batch-processing parallel-decoding tensor-parallelization multimodality language-model-pretraining model-benchmarking teknium carsonpoole casper_ai pradeep1148 osanseviero metaldragon01
Teknium released Nous Hermes 2 on Yi 34B, positioning it as a top open model compared to Mixtral, DeepSeek, and Qwen. Apple introduced Ferret, a new open-source multimodal LLM. Discussions in the Nous Research AI Discord focused on AI model optimization and quantization techniques like AWQ, GPTQ, and AutoAWQ, with insights on proprietary optimization and throughput metrics. Additional highlights include the addition of NucleusX Model to transformers, a 30B model with 80 MMLU, and the YAYI 2 language model by Wenge Technology trained on 2.65 trillion tokens. "AutoAWQ outperforms vLLM up to batch size 8" was noted, and proprietary parallel decoding and tensor parallelization across GPUs were discussed for speed improvements.