All tags
Topic: "long-horizon-planning"
Gemini 2.5 Pro/Flash GA, 2.5 Flash-Lite in Preview
gemini-2.5 gemini-2.5-flash-lite gemini-2.5-flash gemini-2.5-pro gemini-2.5-ultra kimi-dev-72b nanonets-ocr-s ii-medical-8b-1706 jan-nano deepseek-r1 minimax-m1 google moonshot-ai deepseek cognitivecompai kling-ai mixture-of-experts multimodality long-horizon-planning benchmarking coding-performance long-context ocr video-generation model-releases tulsee_doshi oriolvinyalsml demishassabis officiallogank _philschmid swyx sainingxie scaling01 gneubig clementdelangue mervenoyann
Gemini 2.5 models are now generally available, including the new Gemini 2.5 Flash-Lite, Flash, Pro, and Ultra variants, featuring sparse Mixture-of-Experts (MoE) transformers with native multimodal support. A detailed 30-page tech report highlights impressive long-horizon planning demonstrated by Gemini Plays Pokemon. The LiveCodeBench-Pro benchmark reveals frontier LLMs struggle with hard coding problems, while Moonshot AI open-sourced Kimi-Dev-72B, achieving state-of-the-art results on SWE-bench Verified. Smaller specialized models like Nanonets-OCR-s, II-Medical-8B-1706, and Jan-nano show competitive performance, emphasizing that bigger models are not always better. DeepSeek-r1 ties for #1 in WebDev Arena, and MiniMax-M1 sets new standards in long-context reasoning. Kling AI demonstrated video generation capabilities.
not much happened today
gemini-2.5-pro chatgpt deepseek-v3 qwen-2.5 claude-3.5-sonnet claude-3.7-sonnet google anthropic openai llama_index langchain runway deepseek math benchmarking chains-of-thought model-performance multi-agent-systems agent-frameworks media-generation long-horizon-planning code-generation rasbt danielhanchen hkproj
Gemini 2.5 Pro shows strengths and weaknesses, notably lacking LaTex math rendering unlike ChatGPT, and scored 24.4% on the 2025 US AMO. DeepSeek V3 ranks 8th and 12th on recent leaderboards. Qwen 2.5 models have been integrated into the PocketPal app. Research from Anthropic reveals that Chains-of-Thought (CoT) reasoning is often unfaithful, especially on harder tasks, raising safety concerns. OpenAI's PaperBench benchmark shows AI agents struggle with long-horizon planning, with Claude 3.5 Sonnet achieving only 21.0% accuracy. CodeAct framework generalizes ReAct for dynamic code writing by agents. LangChain explains multi-agent handoffs in LangGraph. Runway Gen-4 marks a new phase in media creation.