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Company: "meta"
Llama 4's Controversial Weekend Release
llama-4 llama-3 llama-3-2 meta mixture-of-experts early-fusion attention-mechanisms fp8-training training-data benchmarking model-performance model-release multimodality open-models ahmad_al_dahle ylecun reach_vb yuchenj_uw
Meta released Llama 4, featuring two new medium-size MoE open models and a promised 2 Trillion parameter "behemoth" model, aiming to be the largest open model ever. The release included advanced training techniques like Chameleon-like early fusion with MetaCLIP, interleaved chunked attention without RoPE, native FP8 training, and training on up to 40 trillion tokens. Despite the hype, the release faced criticism for lack of transparency compared to Llama 3, implementation issues, and poor performance on some benchmarks. Meta leadership, including Ahmad Al Dahle, denied allegations of training on test sets. The smallest Scout model at 109B parameters is too large for consumer GPUs, and the claimed 10 million token context is disputed. The community response has been mixed, with some praising the openness and others pointing out discrepancies and quality concerns.
Not much happened today.
phi-3-mini gpt4all-3.0 yi-large meta-3d-gen meta perplexity-ai microsoft gpt4all langchainai qdrant-engine 3d-generation long-context instruction-following reinforcement-learning-from-human-feedback persona-driven-data-synthesis meta-tuning model-steering memory-retrieval multivector-search universal-query-api rohanpaul_ai andriy_mulyar cwolferesearch sarahookr
Meta introduced Meta 3D Gen, a system for end-to-end generation of 3D assets from text in under 1 minute, producing high-quality 3D assets with detailed textures. Perplexity AI updated Pro Search to handle deeper research with multi-step reasoning and code execution. Microsoft improved Phi-3 Mini with better long-context understanding and instruction following. GPT4All 3.0 launched with support for thousands of models and major OS compatibility, featuring local file chat. Yi-Large model launched on Fireworks AI Playground. Research highlights include the evolution of reinforcement learning from human feedback (RLHF), persona-driven data synthesis using a billion diverse personas, meta-tuning for few-shot generalization, and steering vectors for model behavior control. Tools updates include LangSmith improving memory retrieval and Qdrant Engine v1.10 adding universal query API and multivector search.
There's Ilya!
chameleon-7b chameleon-34b deepseek-coder-v2 gpt-4-turbo claude-3-opus voco-llama safe-superintelligence-inc openai anthropic meta deepseek google-deepmind parallel-decoding code-generation quantization training-dynamics vision benchmarks datasets image-captioning reasoning memory-optimization ilya-sutskever jan-leike ylecun akhaliq philschmid rohanpaul_ai mervenoyann fchollet
Ilya Sutskever has co-founded Safe Superintelligence Inc shortly after leaving OpenAI, while Jan Leike moved to Anthropic. Meta released new models including Chameleon 7B and 34B with mixed-modal input and unified token space quantization. DeepSeek-Coder-V2 shows code capabilities comparable to GPT-4 Turbo, supporting 338 programming languages and 128K context length. Consistency Large Language Models (CLLMs) enable parallel decoding generating multiple tokens per step. Grokked Transformers demonstrate reasoning through training dynamics affecting memory formation and generalization. VoCo-LLaMA compresses vision tokens with LLMs improving video temporal correlation understanding. The BigCodeBench benchmark evaluates LLMs on 1,140 coding tasks across 139 Python libraries, topped by DeepSeek-Coder-V2 and Claude 3 Opus. PixelProse is a large 16M image-caption dataset with reduced toxicity.