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…in to guide things. You can see swarms of humans and swarms of agents all working together in God’s given orchestration interface: chat. Put another way, it is now time to layer a customer organization’s social graph and work graph onto…
…pages for both 1.8B and 20B versions. Theme 2. Advanced AI Agents with Desktop Control Giving Llama its own Windows instance (Score: 52, Comments: 24): LLaMA, a large language model, was given control over a Windows instance with access to …
…because outputs can be checked, debated, and extended. Agents, Harnesses, and Developer Tooling: Codex, Gemini, Devin, and Agent InfrastructureHarnesses are still a major source of capability gains: @lvwerra released physics-intern, a…
…OpenAI's CriticGPT Release Stable Release of Embodied Agents Toolkit Open Source OCR for Kazakh Language Blog on Reinforcement Learning Specialization Zero-Shot Generating Spatial Sound from Images OpenAI Unveils CriticGPT: A user shared a …
…on one trajectory (test time compute) or spread across parallel agents (parallel test time compute). Pretraining also supplies knowledge that a human researcher would have to locate or reconstruct. No individual expert is aware of every…
…along with tutorials on building AI apps and plan-and-execute agents. Photonics and NVIDIA Advances: Discussions around a new photonics chip that's 1000x faster than traditional chips and NVIDIA's H100 GPU paired with ARM-based CPUs drawing…
…Speculative Decoding, vLLM scaling, and kernel-generation agentsSpeculative Speculative Decoding (SSD): Tanishq Kumar introduces SSD, claiming up to 2× faster than leading inference engines (vLLM, SGLang), collaborating with Tri Dao and…
…memorization in LLMs, and a tree search algorithm for LM agents to improve inference-time exploration.
…focused on ARC-AGI-3’s efficiency-based scoring, which compares agents against the second-best human action count and heavily penalizes extra steps. @scaling01 argued this makes the headline “<1%” difficult to compare with prior ARC…
…models, post-transformers, synthetic data, smol models, and agents. Twitter recaps feature proposals for benchmarks measuring LLM calibration and confidence in falsehoods, and the debut of QVQ outperforming GPT-4o and Claude 3.5 Sonnet.…
…as a major jump in software engineering and long-horizon agents, citing SWE-bench Pro 57.2, Claw-Eval 63.8, and τ3-Bench 72.9, with claims of 1,000+ autonomous tool calls. The non-Pro model adds native omnimodality and a 1M-token context…
…it with LangGraph and aiding in the creation of AI research agents. It includes practical debugging and optimization tips, ensuring a smoother implementation experience. LlamaCloud's Financial Data Superpower: In a recent demo, the team…
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A conversation with Greg Brockman about OpenAI’s path to AGI, alongside our analysis of GPT-5, Codex, and the shift to agentic coding.
Thariq Shihipar on Claude Code’s next era: prompts, harnesses, plugins, and agents—and what it takes to keep pace with the frontier.
Marc Andreessen on the future of the browser, Pi and OpenClaw, and why this wave of AI feels different.
Priscilla Chan and Mark Zuckerberg on Biohub’s plans for frontier AI and virtual biology, and the ambition to cure or prevent disease.
Anima Anandkumar on modeling the physical world, from weather to fusion reactors, and why physics needs more than language models.
John Platt on automating science, tackling climate change, and how the next generation can contribute in the age of AI.
Anthropic brings interactive apps into Claude with an open MCP standard for richer AI interfaces.
What Sam Altman’s town hall reveals about building startups in the age of AI.
Moonshot’s multimodal model brings competitive coding, native image and video understanding, and parallel agents.
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