Search: “meta”

arXiv:2608.26130v1 Announce Type: new Abstract: Coding agents built on large language models (LLMs), such as Claude Code, Cursor, OpenAI Codex, GitHub Copilot, and Aider, receive tool responses that r

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The difference in what Anthropic and OpenAI as well as many others give you in value for a subscription is insane. We tested Meta, Minimax, Kimi, Grok, and Cursor subscriptions It doesn't make sense t

SemiAnalysis: Analysis: Anthropic's subscriptions offer ~5x more API-equivalent value per month than OpenAI's for agentic workloads with Claude Opus 5.5 vs. GPT-6.1 Sol — Limit testing every AI subscr

We're part of the Amazon Web Services (AWS) AI Builder Lab in New York on Friday, July 24 - a Clash of Agents competition with OpenAI, LangChain, HiddenLayer, Protopia AI, Fiddler AI, and Coder. One d

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Got Meta's new Muse Glimmer 30B running on my MacBook (M3 Max, 96GG) and tested the serving options available so far. Fastest right now: Ollama's MLX engine (DFlash included) at ~29 tok/s. Tuned llama

Ollama now supports the DeepSeek Harness. ollama launch dsh Run it completely in your own environment. It comes with Ollama's web search pre-installed. You can use its trajectory view to see what is h

Muse Glimmer Cookbook Clone it, run it on the GPU you already own, and ship a working agent — one that plans, calls tools, and self-corrects — in a single sitting, fully offline. Muse Glimmer is an op

I don't know what's happening. So, when i use models in openwebui everything works, ollama uses the GPU fully, everything's perfect. Then, I use Hermes, and loads the model in VRAM (fully, no offload

Hi all, I'm new here. I was playing around with the newly release open-weight model released by Meta, and I came across this when asking who it was made by, it said 'OpenAI'. Publicly, Meta had stated

An RLM agent microharness that 'persistently' thinks continuously. What could go wrong :) Introducing Headlong, an open source microharness for persistent agents: self-guided agents that think continu

🚀🚀🚀 can't wait for the Muse Spark open weight releases. ❤️ Thank you @finkd Muse Spark 1.3 is rolling out today with frontier performance almost too cheap to meter. This is the biggest jump we've made

mlx: match publisher tokenizer semantics Honor pretokenizer stage order, split behavior, Unicode boundaries, added-token normalization, and ranked BPE merges. Handle empty added tokens and empty Metas

Chris Welch / Bloomberg: Sonos opens its platform to third-party AI assistants, upgrades Sonos 27voice assistant with an in-house LLM, and plans to let users create their own AI agents — As the compan

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Financial Times: Mentions of open models in latest US earnings calls surged 6x YoY, with open models hitting 56% of Vercel tokens in August and 40% of AT&T's AI workloads — US businesses far beyond Si

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A coding agent finishes a change and wants to open a GitHub issue with a link to its results. The agent can describe the issue, but creating it belongs to a different system. It needs a tool that can

This is beautiful work @huggingface! 🤗 The same model, with the same weights, scores 62% in one agent harness and 33% in another. @adithya_s_k and the @huggingface team just released the ultimate guid

The same model, with the same weights, scores 62% in one agent harness and 33% in another. @adithya_s_k and the @huggingface team just released the ultimate guide to multi-harness RL, and it's one of

Ahmad Al‑Dahle joined Airbnb as CTO in January 2026 after leading Meta’s Llama generative‑AI models (2023–2025). He is steering an “inside‑out AI” strategy that deploys internal AI tools—such as the c

LWiAI Podcast #258 (recorded 26‑Sep‑2026) reviews major AI updates from the previous week. Key developments include Anthropic’s Opus 5.5 release—offering lower pricing, faster performance and robust b

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Overview llama.cpp v0.6.0 introduces the new llama_batch_ext extended batch API (with llama_process) for mixed token/embedding inputs and MTP/deepstack state embeddings, adds support for the GLM-5.3-F

Yesterday TechCrunch published a piece about a growing problem for AI agents: websites are starting to block them. Amazon blocking Meta's Muse is the obvious example. At almost exactly the same time,

Classification is one of the oldest problems in machine learning. Unlike modern decoding transformers, most classification models were non-autoregressive by nature. Before Jev, the common approaches w