Search: “meta”

Micah Barkley / Bloomberg: Manus debuts Manus 2.0, its latest AI agent, and Cue, a new standalone app for personal agents, each with its own email, phone number, wallet, and computer — Manus, an artif

Meta CEO Mark Zuckerberg has a lot to say about the idealized future he now envisions for humanity co-existing with artificial intelligence - his latest essay spans more than 6,500 words on the matter

Meta's Apache-2.0 30B Muse Glimmer targets local agentic tool use, multi-step coding, and vision, sized to leave headroom on 32GB machines.

Introducing Muse Spark 1.1 Following Muse Spark in April, here's Muse Spark 1.1 - the first Spark model to offer an API. Meta claim significant improvements in agentic tool calling and computer use. T

Today we’re releasing Muse Spark Open, the most capable US open-weight model to date. Built for coding and agentic work, it excels at long-horizon tasks, complex software engineering, and multi-step r

Muse is getting a lot of attention — including mine — because it’s both groundbreaking technically (each user gets their own entire persistent Linux VM running in Meta’s cloud) and because it’s packag

We seem to be entering into an AI agent renaissance. Meta's new consumer-facing AI agent, Muse, topped the App Store charts soon after its release and has 600,000 daily active users in the US, by an A

model: add Qwen3.8-Flash-Next (qwen4exp) (#27742) gguf: add qwen4exp (Qwen3.8-Flash-Next) arch and converter Adds the GGUF-side plumbing for HF model_type qwen4_exp: MODEL_ARCH.QWEN4EXP plus tensors f

in case you needed more evidence that tokenmaxxing was a stupid idea Meta burns 2.65B a year on AI tokens. at 300K for a Meta engineer, that's enough to pay ~9,000 engineers for a full year. now ask y

arXiv:2507.22136v3 Announce Type: replace Abstract: Humans possess innate meta-learning capabilities, partly attributable to their exceptional color perception. In this paper, we pioneer an innovative

arXiv:2512.20974v3 Announce Type: replace-cross Abstract: Bayesian Reinforcement Learning (BRL), a subclass of Meta-Reinforcement Learning (Meta-RL), provides a principled framework for generalisation

meta: recreate all subgraphs when the arena is reallocated (#30453) meta: recreate all subgraphs when the arena is reallocated chore: revert added test cases Website: https://llama.app Attestations: h

After launching nearly a month ago and spending several weeks as the top free app in Apple's App Store, the latest update to Meta's Muse iOS app introduces native support for the iPad. A Mac version o

arXiv:2610.08699v1 Announce Type: new Abstract: Assistants from 2011 answered and waited, and agents from 2023 did a task and stopped. In September 2026 Meta's Muse showed an agent for one person, wit

Aisha Malik / TechCrunch: TikTok debuts Shopping Assistant, a conversational AI agent that helps users find and buy products, and Buy Direct for one-click purchases from the For You feed — TikTok anno

Automated lint: 19 errors, 64915 warnings, 3 info

arXiv:2609.32766v1 Announce Type: new Abstract: Modern machine learning spans supervised, transfer, continual, meta-learning, and related regimes that often reuse the same hypothesis classes, architec

ggml-meta: resolve multi buffer views (#29266) ggml-meta: resolve multi buffer views add TODO to revisit if graph allocator gets refactored Website: https://llama.app Attestations: https://github.com/

arXiv:2606.20002v2 Announce Type: replace-cross Abstract: This work presents a general framework for training large language models (LLMs) to 'Connect the Dots' (CoD), a meta-capability required by lo

arXiv:2609.09815v1 Announce Type: cross Abstract: Compound LLM systems often solve a coordination problem by adding a higher-level LLM. The resulting meta-agent reads workers' outputs, writes the fina

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

arXiv:2601.14032v2 Announce Type: replace Abstract: Reward models (RMs) play a pivotal role in aligning large language models (LLMs) with human preferences. Due to the difficulty of obtaining high-qua

as expected by whom? 🤔 META: ZUCKERBERG SAYS AI PROGRESS HAS BEEN SLOWER THAN EXPECTED • ZUCKERBERG SAID AI AGENT DEVELOPMENT HAS NOT ACCELERATED AS EXPECTED OVER THE PAST FOUR MONTHS • SAID META'S 20

wild. Google reportedly limited Meta’s use of Gemini due to a shortage of compute resources. — FT Google is in a position where it can’t sell Gemini to Meta as freely as it might want to. Compute rema

arXiv:2602.04431v2 Announce Type: replace Abstract: LLM-based multi-agent systems have demonstrated impressive capabilities, but they also introduce significant safety risks when individual agents fai

Auto-generated index of all models mentioned across the wiki.

What if a model became the computer itself? NEW paper from Meta. (bookmark this one) What if the model wasn't just using the computer, but became the computer? New research from Meta AI and KAUST make

Autonomous agents are the hottest thing in AI. OpenAI, Meta, Google, Instinct, and others promise their agents can scour the internet on your behalf, doing anything from booking a dinner reservation a

arXiv:2406.20031v2 Announce Type: replace-cross Abstract: Pairwise difference learning (PDL) has recently been introduced as a new meta-learning technique for regression. Instead of learning a mapping

arXiv:2610.13411v1 Announce Type: cross Abstract: Traditional system identification typically involves two steps: initially, training data is processed to estimate a model of the system of interest; t

arXiv:2610.02405v1 Announce Type: new Abstract: Using a frontier model like Claude Opus as a meta-agent to generate terminal tasks and verifiers for RL training is increasingly common. Yet a runnable

It's a tale as old as last week: OpenAI's new agent platform, called Dots, is full of cute little guys who can do your bidding. But unlike the ultra-approachable Meta Muse, Dots feel very much like us

model : re-enable -sm tensor for qwen4exp (#28569) #27941 disabled -sm tensor for qwen4exp because test-llama-archs asserted on the Meta device once the fixture carried a PLE layer: GGML_ASSERT(ggml_b

OpenAI is responding to Meta's buzzy Muse AI with agentic helpers of its own: Dots. During its DevDay keynote on Tuesday, OpenAI announced that Dots will serve as always-on AI assistants that can 'do

Automated lint: 17 errors, 59669 warnings, 3 info

arXiv:2609.28122v1 Announce Type: cross Abstract: Neural Processes (NPs) are model-based meta-learners that implicitly learn a stochastic process and adapt to a new task from a small context set. Most

Julian Chokkattu / Wired: Rabbit launches OS3, a cloud AI agent that connects to local apps and files on Windows, Mac, and Linux and works via web, Telegram, iMessage, or its R1 device — Two years aft

model : add support for HrmTextForCausalLM (DFM Mimir 1B) (#27625) model : add support for HrmTextForCausalLM (DFM Mimir 1B) HRM-Text runs two transformer stacks (low, high) in an alternating cycle ov

arXiv:2609.14985v1 Announce Type: new Abstract: We show how users can create and manipulate causal virtual worlds with large-language-model (LLM) and large-video-model agents. The approach uses feedba

Jeremy Stern / Colossus: A profile of Mark Zuckerberg, based on interviews with him, his parents, and dozens of others, looking at his MMA training, AI pivot, management style, and more — A journey to

// human-values.pseudo | ARTIFACT 0.1.0-experimental.1 | BASE 1.2.0-rc1 | EDITION ai-compact | NARRATOR System_Synthesis_Node_01 | PROVENANCE human-directed, AI-assisted | STATUS single-encoder resear

🚀🚀🚀 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

arXiv:2608.26750v1 Announce Type: new Abstract: Data lakes rely on metadata to remain usable, yet this meta data is often limited or weakly informative for column relationship discovery, especially in

If you maintain a skill library for long-horizon agents, this one is worth your time. (bookmark it) It discusses one of most common topics I get asked about these days. It shares some good ideas on ho

One of the things the pelican benchmark is still useful for is visually representing (to a tiny extent) the improvements in a single model family Here's Meta AI's Spark (8th April), Spark 1.1 (9th Jul

The earlier post on this subreddit by 20+ companies signing the petition including Microsoft, Meta, Nvidia, YC (https://www.microsoft.com/en-us/corporate-responsibility/topics/open-weight/) etc plus t