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Model: "qwen3-omni"
not much happened today
7m-tiny-recursive-model jamba-reasoning-3b qwen3-omni qwen-image-edit-2509 colbert-nano agentflow samsung lecuun ai21-labs alibaba coreweave weights-biases openpipe stanford recursive-reasoning density-estimation multimodality long-context retrieval serverless-reinforcement-learning agentic-systems model-efficiency reinforcement-learning transformers rasbt jm_alexia jiqizhixin randall_balestr corbtt shawnup _akhaliq
Samsung's 7M Tiny Recursive Model (TRM) achieves superior reasoning on ARC-AGI and Sudoku with fewer layers and MLP replacing self-attention. LeCun's team introduces JEPA-SCORE, enabling density estimation from encoders without retraining. AI21 Labs releases Jamba Reasoning 3B, a fast hybrid SSM-Transformer model supporting up to 64K context tokens. Alibaba's Qwen3 Omni/Omni Realtime offers a unified audio-video-text model with extensive language and speech support, outperforming Gemini 2.0 Flash on BigBench Audio. Alibaba also debuts Qwen Image Edit 2509, a top open-weight multi-image editing model. ColBERT Nano models demonstrate effective retrieval at micro-scale parameter sizes. In reinforcement learning, CoreWeave, Weights & Biases, and OpenPipe launch serverless RL infrastructure reducing costs and speeding training. Stanford's AgentFlow presents an in-the-flow RL system with a 7B backbone outperforming larger models on agentic tasks. This update highlights advances in recursive reasoning, density estimation, multimodal architectures, long-context modeling, retrieval, and serverless reinforcement learning.
Alibaba Yunqi: 7 models released in 4 days (Qwen3-Max, Qwen3-Omni, Qwen3-VL) and $52B roadmap
qwen3-max qwen3-omni qwen3-vl qwen3guard qwen3-livetranslate qwen3-tts-flash qwen-image-edit qwen3coder qwen alibaba alicloud tool-use large-model-coding reasoning multimodality model-release model-updates industry-application scaling fine-tuning reinforcement-learning junyang_lin eddie_wu alibaba_wan
Alibaba's Tongyi Qianwen (Qwen) team launched major updates including the 1T parameter Qwen3-Max, Qwen3-Omni, and Qwen3-VL models, alongside specialized versions like Qwen3Guard, Qwen3-LiveTranslate, Qwen3-TTS-Flash, Qwen-Image-Edit, and Qwen3Coder. At the AliCloud Yunqi (Apsara) conference, CEO Eddie Wu outlined a $52B roadmap emphasizing two AI development stages: "intelligence emergence" focusing on learning from humans and reasoning, and "autonomous action" highlighting AI's tool use and real-world task execution. The updates showcase advances in tool use, large-model coding capabilities, and AI's expanding role across industries such as logistics, manufacturing, biomedicine, and finance. Junyang Lin and Alibaba Wan are key spokespersons for these developments. The Qwen project is now seen as a "frontier lab" for AI innovation.
NVIDIA to invest $100B in OpenAI for 10GW of Vera Rubin rollout
qwen3-omni deepseek-v3.1 nvidia openai oracle intel enfabrica wayne gpu-infrastructure deterministic-inference reinforcement-learning fp8-precision gpu-performance ai-infrastructure strategic-partnerships investment datacenters cuda-graphs pipeline-parallelism data-parallelism artificialanlys gdb
NVIDIA and OpenAI announced a landmark strategic partnership to deploy at least 10 gigawatts of AI datacenters using NVIDIA's systems, with NVIDIA investing up to $100 billion progressively as each gigawatt is deployed, starting in the second half of 2026 on the Vera Rubin platform. This deal significantly impacts the AI infrastructure funding landscape, potentially supporting OpenAI's $300 billion commitment to Oracle. The announcement caused major stock market reactions, with NVIDIA's market cap surging by $170 billion. Additionally, advancements in deterministic inference for reinforcement learning and FP8 precision gains in GPU performance were highlighted by AI practitioners.