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Person: "miramurati"
not much happened today
inkling thinking-machines-lab huggingface vllm_project lmsysorg modal baseten databricks mixture-of-experts multimodality foundation-models model-licensing context-window open-weights model-release miramurati soumithchintala johnschulman2 lilianweng natolambert artificialanlys scaling01
Thinking Machines Lab launched Inkling, its first fully released open-weights foundation model family, featuring 975B parameters with 41B active parameters in a Mixture-of-Experts architecture. Inkling supports multimodality with text, image, and audio inputs and text output, is Apache 2.0 licensed, and offers up to 1M context window. The model is available on platforms like Tinker, Hugging Face, and partners, with broad ecosystem support from vLLM, SGLang, Modal, Baseten, and Databricks. Key figures such as Mira Murati, Soumith Chintala, John Schulman, and Lilian Weng highlighted its open weights, customization, and practical use focus. Independent commentators noted it as the strongest U.S.-based open-weight release to date, though still behind top Chinese open-weight and best closed models on some benchmarks.
DataComp-LM: the best open-data 7B model/benchmark/dataset
mistral-nemo-12b gpt-4o-mini deepseek-v2-0628 mistral-7b llama-3 gemma-2 qwen-2 datacomp hugging-face openai nvidia mistral-ai deepseek dataset-design scaling-laws model-benchmarking model-performance fine-tuning multilinguality function-calling context-windows open-source-models model-optimization cost-efficiency benchmarking sam-altman guillaume-lample philschmid miramurati
DataComp team released a competitive 7B open data language model trained on only 2.5T tokens from the massive DCLM-POOL dataset of 240 trillion tokens, showing superior scaling trends compared to FineWeb. OpenAI launched GPT-4o mini, a cost-effective model with 82% MMLU and performance near GPT-4-Turbo, aimed at developers for broad applications. NVIDIA and Mistral jointly released the Mistral NeMo 12B model featuring a 128k token context window, FP8 checkpoint, multilingual support, and Apache 2.0 licensing. DeepSeek announced DeepSeek-V2-0628 as the top open-source model on the LMSYS Chatbot Arena leaderboard with strong rankings in coding, math, and hard prompts. This news highlights advances in dataset design, model efficiency, and open-source contributions in the AI community.
Francois Chollet launches $1m ARC Prize
gpt-4 chatgpt openai apple togethercompute benchmarking agi pattern-recognition skill-acquisition privacy on-device-ai mixed-precision-quantization mixture-of-experts multimodality agentic-ai francois-chollet karpathy svpino philschmid clementdelangue sama gdb miramurati kevin-weil sarah-friar
François Chollet critiques current paths to AGI, emphasizing the importance of benchmarks that resist saturation and focus on skill acquisition and open-ended problem solving. The ARC-AGI puzzles exemplify "easy for humans, hard for AI" challenges to measure progress toward AGI. Meanwhile, Apple announces integration of ChatGPT into iOS, iPadOS, and macOS through a partnership with OpenAI, enabling AI-powered features like document summarization and photo analysis with privacy-preserving measures. Discussions highlight Apple's focus on deep AI integration and on-device models optimized with techniques like mixed-precision quantization, though some skepticism remains about their AI capabilities compared to GPT-4. Additionally, Together Compute introduces a Mixture of Agents approach achieving strong performance on AlpacaEval 2.0.