All tags
Topic: "code-execution"
Mistral's Agents API and the 2025 LLM OS
qwen claude-4 chatgpt o3 o4 mistral-ai langchain-ai openai meta-ai-fair agent-frameworks multi-agent-systems tool-use code-execution web-search model-context-protocol persistent-memory function-calling open-source no-code reinforcement-learning model-performance agent-orchestration omarsar0 simonw swyx scaling01
The LLM OS concept has evolved since 2023, with Mistral AI releasing a new Agents API that includes code execution, web search, persistent memory, and agent orchestration. LangChainAI introduced the Open Agent Platform (OAP), an open-source no-code platform for intelligent agents. OpenAI plans to develop ChatGPT into a super-assistant by H1 2025, competing with Meta. Discussions around Qwen models focus on reinforcement learning effects, while Claude 4 performance is also noted. The AI Engineer World's Fair is calling for volunteers.
QwQ-32B claims to match DeepSeek R1-671B
qwen-2.5-plus qwq-32b deepseek-r1 gpt-4.5 gpt-3 davinci alibaba openai deepseek-ai reinforcement-learning math code-execution instruction-following alignment reasoning model-release model-benchmarking scaling performance inference-costs aidan_mclau sama scaling01 juberti polynoamial reach_vb
Alibaba Qwen released their QwQ-32B model, a 32 billion parameter reasoning model using a novel two-stage reinforcement learning approach: first scaling RL for math and coding tasks with accuracy verifiers and code execution servers, then applying RL for general capabilities like instruction following and alignment. Meanwhile, OpenAI rolled out GPT-4.5 to Plus users, with mixed feedback on coding performance and noted inference cost improvements. The QwQ model aims to compete with larger MoE models like DeepSeek-R1. "GPT-4.5 is unusable for coding" was a notable user critique, while others praised its reasoning improvements due to scaling pretraining.
Bespoke-Stratos + Sky-T1: The Vicuna+Alpaca moment for reasoning
sky-t1-32b-preview qwen-2.5-32b r1 o1-preview gpt-4o claude-3-sonnet bespoke-stratos-32b gemini-2.0-flash-thinking berkeley usc deepseek bespoke-labs google llmsys stanford lm-sys reasoning supervised-finetuning reinforcement-learning multimodality model-distillation context-windows code-execution model-repeatability behavioral-self-awareness rlhf teortaxestex cwolferesearch madiator chakraai philschmid abacaj omarsar0
Reasoning Distillation has emerged as a key technique, with Berkeley/USC researchers releasing Sky-T1-32B-Preview, a finetuned model of Qwen 2.5 32B using 17k reasoning traces for just $450, matching benchmarks of o1-preview. DeepSeek introduced R1, a model surpassing o1-preview and enabling distillation to smaller models like a 1.5B Qwen to match gpt-4o and claude-3-sonnet levels. Bespoke Labs further distilled R1 on Qwen, outperforming o1-preview with fewer samples. This progress suggests that "SFT is all you need" for reasoning without major architecture changes. Additionally, DeepSeek-R1 uses pure reinforcement learning with supervised finetuning to accelerate convergence and shows strong reasoning and multimodal capabilities. Google's Gemini 2.0 Flash Thinking model boasts a 1 million token context window, code execution, and excels in math, science, and multimodal reasoning. Critiques highlight challenges in model repeatability, behavioral self-awareness, and RLHF limitations in reasoning robustness.
OpenAI Voice Mode Can See Now - After Gemini Does
gemini-2.0-flash claude claude-3.5-sonnet llama-3-70b llama-3 mistral-large gpt-4o openai google-deepmind anthropic togethercompute scale-ai meta-ai-fair mistral-ai multimodality real-time-streaming roleplay prompt-handling model-comparison model-training creative-writing model-censorship code-execution developer-ecosystem ai-humor bindureddy
OpenAI launched Realtime Video shortly after Gemini, which led to less impact due to Gemini's earlier arrival with lower cost and fewer rate limits. Google DeepMind released Gemini 2.0 Flash featuring enhanced multimodal capabilities and real-time streaming. Anthropic introduced Clio, a system analyzing real-world usage of Claude models. Together Computing acquired CodeSandbox to launch a code interpreter tool. Discussions highlighted Meta's Llama 3.3-70B for its advanced roleplay and prompt handling abilities, outperforming models like Mistral Large and GPT-4o in expressiveness and censorship. The AI community also engaged in humorous takes on AI outages and model competition, with ChatGPT adding a Santa mode for holiday interactions. "Anthropic is capturing the developer ecosystem, Gemini has AI enthusiast mindshare, ChatGPT reigns over AI dabblers" was a noted observation from the community.
ChatGPT Canvas GA
llama-3-70b llama-3-1-8b tgi-v3 deepseek-v2.5-1210 coconut openai deepseek-ai meta-ai-fair huggingface cognition-labs hyperbolic google-deepmind code-execution gpt-integration model-finetuning gradient-checkpointing context-length latent-space-reasoning performance-optimization gpu-memory-optimization kubernetes gpu-marketplace ai-capabilities employment-impact neurips-2024 ai-scaling humor arav_srinivas sama jonathan-frankle dylan
OpenAI launched ChatGPT Canvas to all users, featuring code execution and GPT integration, effectively replacing Code Interpreter with a Google Docs-like interface. Deepseek AI announced their V2.5-1210 update improving performance on MATH-500 (82.8%) and LiveCodebench. Meta AI Fair introduced COCONUT, a new continuous latent space reasoning paradigm. Huggingface released TGI v3, processing 3x more tokens and running 13x faster than vLLM on long prompts. Cognition Labs released Devin, an AI developer building Kubernetes operators. Hyperbolic raised $12M Series A to build an open AI platform with an H100 GPU marketplace. Discussions included AI capabilities and employment impact, and NeurIPS 2024 announcements with Google DeepMind demos and a debate on AI scaling. On Reddit, Llama 3.3-70B supports 90K context length finetuning using Unsloth with gradient checkpointing and Apple's Cut Cross Entropy (CCE) algorithm, fitting on 41GB VRAM. Llama 3.1-8B reaches 342K context lengths with Unsloth, surpassing native limits.