All tags
Topic: "recursive-language-models"
not much happened today
gpt-5.3-codex claude-opus-4.6 nanochat-gpt-2 openai anthropic langchain agent-systems ai-engineering benchmarking software-organization sandboxing tracing state-management recursive-language-models context-management karpathy sama swyx omarsar0 hamelhusain deepfates
AI News for early February 2026 highlights a detailed comparison between GPT-5.3-Codex and Claude Opus 4.6, with users noting Codex's strength in detailed scoped tasks and Opus's ergonomic advantage for exploratory work. Benchmarks on Karpathy's nanochat GPT-2 speedrun show Opus 4.6 achieving better wall-clock performance, while Codex-5.3-xhigh sometimes suffers from context issues. Karpathy cautions that current models are not yet reliable for fully autonomous AI engineering. Discussions on agent swarms reveal emerging parallels to software organizational design, with Anthropic-style agent coordination systems and LangChain/LangSmith emphasizing environment engineering through tracing, sandboxing, and state control. The concept of Recursive Language Models (RLM) is introduced as a future direction for agent systems to reduce context rot and improve structured communication.
Anthropic launches the MCP Apps open spec, in Claude.ai
claude-ai toolorchestra-8b qwen3-max-thinking anthropic openai block vs-code antigravity jetbrains aws nvidia alibaba claude-ai agent-orchestration reinforcement-learning recursive-language-models context-management user-experience security prompt-injection reasoning adaptive-tool-use model-evaluation benchmarking
Anthropic has officially absorbed the independent MCP UI project and, collaborating with OpenAI, Block, VS Code, Antigravity, JetBrains, and AWS, released the MCP Apps spec and official support in Claude.ai. This standard aims to enable a rich ecosystem of interoperable applications with rich UI, addressing the proliferation of subscription services. Meanwhile, NVIDIA introduced ToolOrchestra with an 8B orchestrator model trained via scalable reinforcement learning for efficient agent orchestration. The concept of Recursive Language Models (RLMs) is gaining traction for efficient context management in agent stacks. The “Clawdbot” UX pattern emphasizes outcome-first assistant design with tight context and tool integration, sparking security concerns around prompt injection. Alibaba launched Qwen3-Max-Thinking, a flagship reasoning and agent model with adaptive tool use and strong benchmark scores, now available in public evaluation platforms like LM Arena and Yupp.
not much happened today
DeepSeek released a new paper on mHC: Manifold-Constrained Hyper-Connections, advancing residual-path design as a key scaling lever in neural networks. Their approach constrains residual mixing matrices to the Birkhoff polytope to improve stability and performance, with only about 6.7% training overhead. The innovation includes systems-level optimizations like fused kernels and activation recomputation, highlighting a frontier-lab integration of math and kernel engineering. Additionally, discussions around long-horizon agents emphasize context management bottlenecks, introducing Recursive Language Models (RLMs) that manage context dynamically rather than relying on larger context windows. This work signals a shift in architectural design and efficiency for base model training and agent development.