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Company: "deepmind"
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.
Creating a LLM-as-a-Judge
claude-3.5-sonnet claude-3.5 notebooklm simpleqa recraft-v3 anthropic openai deepmind apple zep perplexity-ai github critique-shadowing llm-judging domain-experts dataset-creation prompt-engineering error-analysis temporal-knowledge-graphs memory-layer ai-agent-memory hallucination-reduction integration hamel-husain swyx
Anthropic released details on Claude 3.5 SWEBench+SWEAgent, while OpenAI introduced SimpleQA and DeepMind launched NotebookLM. Apple announced new M4 Macbooks, and a new SOTA image model, Recraft v3, emerged. Hamel Husain presented a detailed 6,000-word treatise on creating LLM judges using a method called critique shadowing to align LLMs with domain experts, addressing the problem of untrusted and unused data in AI teams. The workflow involves expert-reviewed datasets and iterative prompt refinement. Additionally, Zep introduced a temporal knowledge graph memory layer to improve AI agent memory and reduce hallucinations. Anthropic also integrated Claude 3.5 Sonnet with GitHub Copilot, expanding access to Copilot Chat users.
not much happened this weekend
claude-3.5-sonnet llama-3 llama-3-8b notebookllama min-omni-2 moondream openai anthropic hugging-face mistral-ai google-deepmind langchain deepmind microsoft pattern-recognition reinforcement-learning prompt-optimization text-to-speech model-optimization tensor-parallelism hyperparameters multimodal modal-alignment multimodal-fine-tuning ai-productivity privacy generative-ai rag retrieval-augmentation enterprise-text-to-sql amanda-askell philschmid stasbekman francois-fleuret mervenoyann reach_vb dzhng aravsrinivas sama lateinteraction andrew-y-ng bindureddy jerryjliu0
Moondream, a 1.6b vision language model, secured seed funding, highlighting a trend in moon-themed tiny models alongside Moonshine (27-61m ASR model). Claude 3.5 Sonnet was used for AI Twitter recaps. Discussions included pattern recognition vs. intelligence in LLMs, reinforcement learning for prompt optimization, and NotebookLlama, an open-source NotebookLM variant using LLaMA models for tasks like text-to-speech. Advances in model optimization with async-TP in PyTorch for tensor parallelism and hyperparameter tuning were noted. Mini-Omni 2 demonstrated multimodal capabilities across image, audio, and text for voice conversations with emphasis on modal alignment and multimodal fine-tuning. AI productivity tools like an AI email writer and LlamaCloud-based research assistants were introduced. Emphasis on practical skill development and privacy-conscious AI tool usage with Llama3-8B was highlighted. Generative AI tools such as #AIPythonforBeginners and GenAI Agents with LangGraph were shared. Business insights covered rapid execution in AI product development and emerging AI-related job roles. Challenges in enterprise-grade text-to-SQL and advanced retrieval methods were discussed with tutorials on RAG applications using LangChain and MongoDB.
DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing
bitnet-b1.58 llama-3.1-nemotron-70b-instruct gpt-4o claude-3.5-sonnet uc-berkeley deepmind openai microsoft nvidia archetype-ai boston-dynamics toyota-research google adobe openai mistral tesla meta-ai-fair model-optimization on-device-ai fine-tuning large-corpus-processing gpu-acceleration frameworks model-benchmarking rohanpaul_ai adcock_brett david-patterson
UC Berkeley's EPIC lab introduces innovative LLM data operators with projects like LOTUS and DocETL, focusing on effective programming and computation over large data corpora. This approach contrasts GPU-rich big labs like Deepmind and OpenAI with GPU-poor compound AI systems. Microsoft open-sourced BitNet b1.58, a 1-bit ternary parameter LLM enabling 4-20x faster training and on-device inference at human reading speeds. Nvidia released Llama-3.1-Nemotron-70B-Instruct, a fine-tuned open-source model outperforming GPT-4o and Claude-3.5-sonnet. These developments highlight advances in model-optimization, on-device-ai, and fine-tuning.
a quiet weekend
sam-2 qwen2-math gpt-4 claude-3.5 figure deepmind boston-dynamics alibaba llamaindex robotics object-segmentation real-time-processing disease-prediction speech-recognition cli-tools model-performance adcock_brett rasbt hamel-husain rohanpaul_ai
Figure unveiled Figure 02, claimed as the most advanced humanoid robot, operating autonomously at BMW's Plant Spartanburg. DeepMind developed a table tennis robot achieving 100% wins against beginners and 55% against intermediates. Boston Dynamics showcased the dexterity of its fully-electric Atlas robot performing pushups and burpees. An autonomous dental robot performed the world's first dental procedure on a human, reducing a 2-hour process to 15 minutes using a 3D volumetric scanner. SAM 2 was introduced as an open model for real-time object segmentation without custom adaptation. Alibaba released Qwen2-Math, outperforming GPT-4 and Claude 3.5 in math capabilities. A new Listening-While-Speaking Language Model (LSLM) enables simultaneous listening and speaking in real-time. Researchers developed a disease prediction AI with 95% accuracy for diseases like coronary artery disease, type 2 diabetes, and breast cancer. Tools like LlamaParse CLI and MLX Whisper package enhance PDF parsing and speech recognition, with the latter running 40X faster than realtime on M1 Max. The news highlights significant advancements in robotics, AI models, and practical AI tools.
How Carlini Uses AI
gemma-2-2b gpt-3.5-turbo-0613 mixtral-8x7b gen-3-alpha segment-anything-model-2 stable-fast-3d groq intel deepmind box figure-ai openai google meta-ai-fair nvidia stability-ai runway benchmarking adversarial-attacks large-language-models text-generation multimodality robotics emotion-detection structured-data-extraction real-time-processing teleoperation 3d-generation text-to-video nicholas-carlini chris-dixon rasbt
Groq's shareholders' net worth rises while others fall, with Intel's CEO expressing concern. Nicholas Carlini of DeepMind gains recognition and criticism for his extensive AI writings, including an 80,000-word treatise on AI use and a benchmark for large language models. Chris Dixon comments on AI Winter skepticism, emphasizing long-term impact. Box introduces an AI API for extracting structured data from documents, highlighting potential and risks of LLM-driven solutions. Recent AI developments include Figure AI launching the advanced humanoid robot Figure 02, OpenAI rolling out Advanced Voice Mode for ChatGPT with emotion detection, Google open-sourcing Gemma 2 2B model matching GPT-3.5-Turbo-0613 performance, Meta AI Fair releasing Segment Anything Model 2 (SAM 2) for real-time object tracking, NVIDIA showcasing Project GR00T for humanoid teleoperation with Apple Vision Pro, Stability AI launching Stable Fast 3D for rapid 3D asset generation, and Runway unveiling Gen-3 Alpha for AI text-to-video generation.
5 small news items
llama-3 xLSTM openai cohere deepmind hugging-face nvidia mistral-ai uncertainty-quantification parameter-efficient-fine-tuning automated-alignment model-efficiency long-context agentic-ai fine-tuning inference-optimization leopold-aschenbrenner will-brown rohanpaul_ai richardmcngo omarsar0 hwchase17 clementdelangue sophiamyang
OpenAI announces that ChatGPT's voice mode is "coming soon." Leopold Aschenbrenner launched a 5-part AGI timelines series predicting a trillion dollar cluster from current AI progress. Will Brown released a comprehensive GenAI Handbook. Cohere completed a $450 million funding round at a $5 billion valuation. DeepMind research on uncertainty quantification in LLMs and an xLSTM model outperforming transformers were highlighted. Studies on the geometry of concepts in LLMs and methods to eliminate matrix multiplication for efficiency gains were shared. Discussions on parameter-efficient fine-tuning (PEFT) and automated alignment of LLMs were noted. New tools include LangGraph for AI agents, LlamaIndex with longer context windows, and Hugging Face's integration with NVIDIA NIM for Llama3. Mistral AI released a fine-tuning API for their models.
Not much happened today
command-r-35b goliath-120 miqu-120 llama-3-8b tensorrt-llm llama-cpp gpt2-chat gpt-4-turbo llama-3 deepmind-alphazero anthropic openai perplexity-ai amazon apple microsoft deepmind creative-writing context-windows benchmarking model-performance self-learning function-calling retrieval-augmented-generation ai-assistants on-device-ai ai-lobbying copyright-infringement code-reasoning image-generation
Anthropic released a team plan and iOS app about 4 months after OpenAI. The Command-R 35B model excels at creative writing, outperforming larger models like Goliath-120 and Miqu-120. The Llama-3 8B model now supports a 1 million token context window, improving long-context understanding with minimal training on a single 8xA800 GPU machine. TensorRT-LLM benchmarks show it is 30-70% faster than llama.cpp on consumer hardware. A benchmark suggests GPT2-Chat may have better reasoning than GPT-4-Turbo, though results are debated. Demos include a self-learning Llama-3 voice agent running locally on Jetson Orin and a Self-Learning Large Action Model (LAM). Amazon CodeWhisperer was renamed to Q Developer, expanding its generative AI assistant capabilities. Apple plans an AI-enabled Safari browser with an on-device LLM in iOS 18 and macOS 15. Big Tech dominates AI lobbying in Washington, while major U.S. newspapers sued OpenAI and Microsoft for copyright infringement. DeepMind's AlphaZero became the greatest chess player in 9 hours, and their Naturalized Execution Tuning (NExT) method improves LLM code reasoning by 14-26%. Stable Diffusion is used for diverse image generation applications.
Mixture of Depths: Dynamically allocating compute in transformer-based language models
octopus-v2 deepmind transformer-efficiency dynamic-compute-allocation mixture-of-experts mixture-of-depths top-k-routing algorithmic-reasoning visual-autoregressive-modeling on-device-models function-calling scaling-laws piotrpadlewski
DeepMind introduces the Mixture-of-Depths (MoD) technique, dynamically allocating FLOPs across transformer layers to optimize compute usage, achieving over 50% faster forward passes without training impact. MoD selectively processes tokens using top-k routing, improving efficiency and potentially enabling faster ultra-long context handling. The method can combine with Mixture-of-Experts (MoE) for decoupled routing of queries, keys, and values. Reddit discussions highlight concerns about LLM hype overshadowing other AI tech, improvements in transformer efficiency, a new Think-and-Execute framework boosting algorithmic reasoning by 10-20%, and Visual Autoregressive modeling (VAR) surpassing diffusion models in image quality and speed. On-device model Octopus v2 outperforms GPT-4 in function calling accuracy and latency.
Not much happened piday
claude-3-haiku deepmind anthropic cohere embodied-ai-agents natural-language-instructions language-model-scaling mixture-of-experts retrieval-augmented-generation software-engineering ai-regulation differential-privacy privacy-preserving-learning humor demis-hassabis fchollet abacaj andrej-karpathy
DeepMind announces SIMA, a generalist AI agent capable of following natural language instructions across diverse 3D environments and video games, advancing embodied AI agents. Anthropic releases Claude 3 Haiku, their fastest and most affordable model, now available via API and Perplexity. New research explores language model scaling laws, over-training, and introduces Branch-Train-MiX (BTX) for efficient training of large language models using mixture-of-experts. Predictions suggest software engineering jobs will grow to 30-35 million in five years, aided by AI coding assistants like Cohere's Command-R focusing on retrieval-augmented generation and tool use. The EU AI Act is approved, mandating transparency in training data for GPAI systems. Privacy-preserving in-context learning with differential privacy is highlighted as promising work. Memes humorously discuss AI software engineers and notable figures like Andrej Karpathy.
DeepMind SIMA: one AI, 9 games, 600 tasks, vision+language ONLY
llama-3 claude-3-opus claude-3 gpt-3.5-turbo deepmind cognition-labs deepgram modal-labs meta-ai-fair anthropic multimodality transformer software-engineering ai-agents ai-infrastructure training text-to-speech speech-to-text real-time-processing model-architecture benchmarking andrej-karpathy arav-srinivas francois-chollet yann-lecun soumith-chintala john-carmack
DeepMind SIMA is a generalist AI agent for 3D virtual environments evaluated on 600 tasks across 9 games using only screengrabs and natural language instructions, achieving 34% success compared to humans' 60%. The model uses a multimodal Transformer architecture. Andrej Karpathy outlines AI autonomy progression in software engineering, while Arav Srinivas praises Cognition Labs' AI agent demo. François Chollet expresses skepticism about automating software engineering fully. Yann LeCun suggests moving away from generative models and reinforcement learning towards human-level AI. Meta's Llama-3 training infrastructure with 24k H100 Cluster Pods is shared by Soumith Chintala and Yann LeCun. Deepgram's Aura offers low-latency speech APIs, and Modal Labs' Devin AI demonstrates document navigation and interaction with ComfyUI. Memes and humor circulate in the AI community.