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Topic: "in-context-learning"
not much happened today
glm-4.5 glm-4.5-air qwen3-coder qwen3-235b kimi-k2 grok-imagine wan-2.2 smollm3 figure-01 figure-02 vitpose++ chatgpt zhipu-ai alibaba moonshot-ai x-ai figure openai runway mlx ollama deeplearningai model-releases model-performance moe image-generation video-generation pose-estimation robotics training-code-release interactive-learning in-context-learning yuchenj_uw corbtt reach_vb ollama deeplearningai gdb sama c_valenzuelab adcock_brett skalskip92 loubnabenallal1 hojonathanho ostrisai
Chinese AI labs have released powerful open-source models like GLM-4.5 and GLM-4.5-Air from Zhipu AI, Qwen3 Coder and Qwen3-235B from Alibaba, and Kimi K2 from Moonshot AI, highlighting a surge in permissively licensed models. Zhipu AI's GLM-4.5 is a 355B parameter MoE model competitive with Claude 4 Opus and Gemini 2.5 Pro. Alibaba's Qwen3 Coder shows strong code generation performance with a low edit failure rate, while Moonshot AI's Kimi K2 is a 1 trillion-parameter MoE model surpassing benchmarks like LiveCodeBench. In video and image generation, xAI launched Grok Imagine, and Wan2.2 impressed with innovative image-to-video generation. Robotics advances include Figure's Figure-01 and Figure-02 humanoid robots and ViTPose++ for pose estimation in basketball analysis. SmolLM3 training and evaluation code was fully released under Apache 2.0. OpenAI introduced Study Mode in ChatGPT to enhance interactive learning, and Runway rolled out Runway Aleph, a new in-context video model for multi-task visual generation. The community notes a competitive disadvantage for organizations avoiding these Chinese open-source models. "Orgs avoiding these models are at a significant competitive disadvantage," noted by @corbtt.