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Person: "neelnanda5"
minor ai followups: MultiAgents, Meta-SSI-Scale, Karpathy, AI Engineer
gpt-4o afm-4.5b gemma qwen stt-1b-en_fr stt-2.6b-en hunyuan-3d-2.1 openai meta-ai-fair scale-ai huggingface tencent arcee-ai ai-safety alignment ai-regulation memory-optimization scalable-oversight speech-recognition 3d-generation foundation-models sama polynoamial neelnanda5 teortaxestex yoshua_bengio zachtratar ryanpgreenblatt reach_vb arankomatsuzaki code_star
OpenAI released a paper revealing how training models like GPT-4o on insecure code can cause broad misalignment, drawing reactions from experts like @sama and @polynoamial. California's AI regulation efforts were highlighted by @Yoshua_Bengio emphasizing transparency and whistleblower protections. The term "context rot" was coined to describe LLM conversation degradation, with systems like Embra using CRM-like memory for robustness. Scalable oversight research aiming to improve human control over smarter AIs was discussed by @RyanPGreenblatt. New model releases include Kyutai's speech-to-text models capable of 400 real-time streams on a single H100 GPU, Tencent's Hunyuan 3D 2.1 as the first open-source production-ready PBR 3D generative model, and Arcee's AFM-4.5B foundation model family targeting enterprise use, competitive with Gemma and Qwen.
Mary Meeker is so back: BOND Capital AI Trends report
qwen-3-8b anthropic hugging-face deepseek attention-mechanisms inference arithmetic-intensity transformers model-optimization interpretability model-quantization training tri_dao fleetwood___ teortaxestex awnihannun lateinteraction neelnanda5 eliebakouch _akhaliq
Mary Meeker returns with a comprehensive 340-slide report on the state of AI, highlighting accelerating tech cycles, compute growth, and comparisons of ChatGPT to early Google and other iconic tech products. The report also covers enterprise traction and valuation of major AI companies. On Twitter, @tri_dao discusses an "ideal" inference architecture featuring attention variants like GTA, GLA, and DeepSeek MLA with high arithmetic intensity (~256), improving efficiency and model quality. Other highlights include the release of 4-bit DWQ of DSR1 Qwen3 8B on Hugging Face, AnthropicAI's open-source interpretability tools for LLMs, and discussions on transformer training and abstractions by various researchers.
not much happened this weekend
o3 o1 opus sonnet octave openai langchain hume x-ai amd nvidia meta-ai-fair hugging-face inference-time-scaling model-ensembles small-models voice-cloning fine-math-dataset llm-agent-framework benchmarking software-stack large-concept-models latent-space-reasoning mechanistic-interpretability planning speech-language-models lisa-su clementdelangue philschmid neelnanda5
o3 model gains significant attention with discussions around its capabilities and implications, including an OpenAI board member referencing "AGI." LangChain released their State of AI 2024 survey. Hume announced OCTAVE, a 3B parameter API-only speech-language model with voice cloning. x.ai secured a $6B Series C funding round. Discussions highlight inference-time scaling, model ensembles, and the surprising generalization ability of small models. New tools and datasets include FineMath, the best open math dataset on Hugging Face, and frameworks for LLM agents. Industry updates cover a 5-month benchmarking of AMD MI300X vs Nvidia H100 + H200, insights from a meeting with Lisa Su on AMD's software stack, and open AI engineering roles. Research innovations include Large Concept Models (LCM) from Meta AI, Chain of Continuous Thought (Coconut) for latent space reasoning, and mechanistic interpretability initiatives.