Search: “llm”

Gary Marcus critiques the claim that token prediction in large language models constitutes genuine thought or reasoning, using the analogy of smartphone autocomplete to illustrate that predictive text

Ollama is an open-source framework that enables users to run large language models locally on their machines without requiring cloud services or significant computational resources. The project suppor

We've gone even farther: Nemotron 3 Super is 120B and pretrained on 25T tokens in NVFP4. Nemotron 3 Ultra is ~500B and also pretrained in NVFP4. Accelerated computing means we rethink every aspect of

Wow! What a week! Lots of new things to learn - new ideas to form The complete Agent Development Life Cycle 🎯 ❤️ SF but can’t wait to get home and back to building! Thanks for the warm welcome and fun

🌟Introducing🎻Violin — an Open-source Video Translation Skill. 📹Video is the dominant medium on the internet, yet most high-quality content (lecture, talk, podcast) is locked behind a single language,

Built a local coding harness powered by Gemma 4. It runs locally, connects to my model backend, starts coding sessions, streams responses, and uses tools through a CLI-style workflow. Still early, but

i provided a clear road map in the essay Next Decade in AI in arxiv in 2020. not one person in the field has given a serious critique of it. if you are not aware of it, it is not my fault; i have poin

Langsmith Engine appears to be a seriously high value release from the @LangChain team A deep agent that’s monitoring Langsmith agent traces and not only surfaces issues but: - proposes a PR to resolv

We built SmithDB: the database purpose built for agent observability workloads that now powers many parts of LangSmith. Agent observability presents a challenging data problem. Agent traces can contai

🤩🤯🤩 Claude Code (still not AGI but biggest advance since GPT-4) is the most neurosymbolic thing I have ever seen in my life. 53 symbolic tools, 500,000 lines of symbolic code, combined with a state-of

Cool idea from Nous Research. What if you could speed up long-context pretraining with a subquadratic wrapper that you remove before deployment? That is the idea behind Lighthouse Attention. The metho

Deep learning hit a wall. Neurosymbolic AI rescued it. 🤩🤯🤩 Claude Code (still not AGI but biggest advance since GPT-4) is the most neurosymbolic thing I have ever seen in my life. 53 symbolic tools, 5

> shipped the agent > opened the dashboard > latency: fine > error rate: fine > users: unhappy > checked the responses > technically correct > wrong tool called 3 steps earlier > no trace to follow >

Mark: 1/ First milestone: the Physical Turing Test. You literally can’t tell if a human or robot is doing the task. 2/ Next: Physical API. A fleet of robots, configured like software via APIs & CLI. 3

concluding my 'taking deep agents to production' series with arguably the most important component: observability. when you deploy a deep agent with LangSmith, you automatically get traces for every r

I promise this will be the best 20 min you spend today! Robotics: Endgame, the sequel to my last year's Sequoia AI Ascent talk, 'Physical Turing Test'. I laid out the roadmap for solving Physical AGI

Jim is always a crowd favorite at AI Ascent. His ability to simplify the latest research into a clear 'what and why it matters' while adding humor along the way is unmatched. If you're interested in p

Our crowd favorite from last year’s AI Ascent is back for round 2… this time: Robotics The Endgame ♟️ thank you for dazzling us @DrJimFan ! You can see the forest from the trees and are quite the ente

NEW paper from Microsoft Research. (bookmark it) The entire interpretability literature is built around human readers. As more analysis gets delegated to agents, the right target of interpretability s

Stop token maxxing 🛑 Our CEO @ashashutosh sat down with @a16z General Partner Peter Levine to discuss why we’re moving beyond the vector database: '85% of an agent’s work isn't the model; it's the und

The last sentence in this abstract is really important, in a way that professional programmers will immediately recognize: the models favored big single files rather than breaking things into modules.

Also Instead of the gold standard, we can imagine an inference standard of exchange, the FLOP. (As opposed to tokens, this accounts for AI ability) With some AI help, I figure 1 buys roughly 10^17 man

I detected a bad Agent action, what do I do about it? this is pretty much the main question that will power the future’s Human+Agent driven improvement loops Gather data -> Mine Errors -> Find out whi

Luma Uni-1 just landed in ComfyUI. Most image models: prompt → pixels. Uni-1: prompt → reasoning → pixels. Autoregressive, not diffusion. Decomposes instructions, resolves constraints, plans compositi

Some things never change. If you don’t understand this one, you don’t understand what’s happening AI. Marcus, 1998: neural nets have trouble generalizing far beyond the data. Marcus, 2001, 2012, 2019,

Banger paper from Meta FAIR. They introduce Autodata, an agentic data scientist that builds high-quality training and evaluation data autonomously. The headline result: on a CS research QA task, an Ag

LangChain, a framework for developing applications with large language models, is advancing its capabilities and features according to insights from Harrison Chase, one of its key figures. This post l

Llamacpp, when properly configured on Apple Silicon hardware, demonstrates robust performance and reliability for running language models. The tool can handle varied input requests effectively, making

LangChain announced a partnership with Pinecone, a vector database platform, to integrate vector search capabilities with LangChain's framework for building applications with large language models. Th

JP Morgan's investment research team just shared exactly how they built their multi-agent system 'Ask David', and it's the same architecture pattern showing up everywhere: - supervisor agent orchestra

Of course Pynchon would call this correctly 40 years ago: “It will be amazing and unpredictable, and even the biggest of brass, let us devoutly hope, are going to be caught flat-footed.“ He and Dougla

Shame on the @AFpost for glorifying Dawkins’ foolish post without asking a single expert whether it made any sense whatsoever. Evolutionary biologist and outspoken atheist Richard Dawkins says that af

while exploring harnesses, i came across my first and favourite agent orchestration framework @LangChain has launched deep-agents last year. it’s a wonderful harness, that has a lot of tools: - write_

A lot of work around AI in 2023 was spent on building picks and shovels. I would know this because that was basically the core goal of the original @llama_index framework. Today, a lot of that is no l

People are really enjoying our full workshops showing end to end walkthroughs of real production workflows! This is a rare double header with @braintrust's Giran Moodley and @OussamaHaff walking thoug

📢 Official Announcement: Qwen Partners with Fireworks AI to Accelerate Access to Qwen Family Models We are pleased to announce a strategic partnership between Qwen and Fireworks AI to deliver optimize

arXiv:2604.26269v1 Announce Type: cross Abstract: The essence of good creative writing is calibrated surprise: when constraints from all relevant dimensions act together, the feasible solution space c

Falkor's new GraphRAG SDK just took #1 on GraphRAG bench and yes it's open source 😆 Token costs spiking. Responses too slow. Users don't trust the answers. All three are retrieval problems. GraphRAG S

For years, voice AI has been stuck in a rigid loop: think, then speak. But real human conversation is messy, overlapping, and asynchronous. In our new #ICASSP2026 work, we built a tandem architecture

// Latent Agents // Multi-agent debate makes models reason better. It also burns tokens generating long transcripts before any answer comes out. This new research distills the entire debate into a sin

This post likely discusses how AI systems, particularly language models, can implicitly agree to tasks or commitments during conversations without formally recording or tracking these obligations, whi

This post criticizes Microsoft's approach to integrating AI assistants into Outlook, expressing frustration that the AI chatbot has limited functionality and capabilities despite Microsoft's ownership

Today we’re shipping Laguna M.1 and Laguna XS.2 – our first public models. We’re also shipping our agent harness and a preview product experience. Both models were trained from scratch on our own stac

@idarbek Having your backups on the same vendor as your production database puts you at risk of your vendor banning your account for some reason (like billing messups, or detected CSAM in user-uploade

ml-intern from @huggingface is such a cool repository, an 🤖 agentic harness that allows you to wield the larger🤗ecosystem to run all the tasks a ml researcher would. it's all one can ask for as a side

ML Intern, a feature or tool, now supports Slack notifications to alert users when machine learning tasks complete, including model training, dataset generation, and ablation study analysis. This inte