Search: “papers”

What a week at @iclr_conf in Rio 🇧🇷 ! As my first conference, it would have been hard to ask for a better experience 😍. I had the chance to present two papers: - EB-JEPA https://github.com/facebookres

Four small architecture decisions can cost up to 47% of a model's long-context performance. New research from Ai2, Carnegie Mellon, and the University of Washington isolates them. Normalization, GQA,

New research from Meta. Agent harnesses are still mostly authored by hand. This makes it hard to tune robust agent harnesses for long-horizon tasks. In this new work, agents learn harness policies off

New research from Google DeepMind. (bookmark it) SkillSmith treats model weights as an additional modality the LLM reads natively. The augmented model ingests existing prefix weights alongside rich te

New work led by @FlemmingKondrup and @tomjiralerspong highlights an important vulnerability in chain-of-thought monitoring for agents, I highly recommend giving it a read. Link to the paper: https://a

// ReContext // Models now support 128K context windows and still fail to use evidence that is already in the prompt. Where is the gap? New paper introduces ReContext, a training-free inference harnes

further evidence that people shoveling money into AI are either bad at math or blind to risk Striking paper from Wharton. The big conclusion: AI must increase productivity 2.7x -- and quickly -- or te

Active Graph is the best, most 'correct' knowledge/context engine I've come across so far (and I've tried or at least researched most of them.) babyagi has ~200 citations, but 0 papers... i just publi

If you design production agent systems, this matters. Most devs accidentally let their framework defaults make critical architecture decisions without thinking it through. This paper shows you how to

// δ-mem: Efficient Online Memory for LLMs // One of the more elegant memory mechanisms I've seen this month. Most long-term memory work either inflates context or retrains the model. This paper shows

Wanna get a million views? Make stuff up. Take a tiny tiny bit of truth and distort it wildly. Consider the tweet below, 1.4M views. Take the chess thing. The paper that is linked doesn’t actually say

We’re excited to introduce KAME: Tandem Architecture for Enhancing Knowledge in Real-Time Speech-to-Speech Conversational AI, accepted at #ICASSP2026! 🐢 Blog https://pub.sakana.ai/kame/ Paper https://

Pay attention to this one, AI devs, especially if you're thinking about agentic commerce or any agent network where many agents share hosts. A correct route to a cold agent is still a failed request f

How do AI Agents spend your money? Most teams treat agent token costs as a rounding error even though the data says they shouldn't. New paper presents the first systematic study of how agents actually

Scaling massive monolithic LLMs continues to yield incredible results. But to truly unlock their ceiling, the next frontier is test-time compute and dynamic orchestration. Nature solves complex proble

Tool Attention Is All You Need // Tool Attention Is All You Need // New research proposes a practical fix for the hidden 'MCP tax.' The work introduces a dynamic tool gating mechanism built on an Inte

MIT researchers just replicated human muscles with AI-controlled fibers. Inside each fiber is a sealed tube of electrically charged liquid and a tiny electric pump. When the pump activates, one side c

ml-intern by @huggingface is wild 🔥 You drop a high-level prompt (“build the best scientific reasoning model” or “crush healthcare benchmarks”) and this open-source agent does the entire post-training

AI Insider: 'Adding a Human Makes Your Team Worse' Emad Mostaque | @EMostaque TIMESTAMPS : 00:00 The models too dangerous to release 10:06 Why physics needs axioms — and AI doesn't 11:43 The MIND fram

It’s time to go beyond language models. Introducing Odyssey-2 Max, our most powerful world model yet. It materially advances the SOTA in physical accuracy. This is a big step toward models that simula

Earlier this year Yann LeCun left Meta because Mark Zuckerberg wouldn't bet the company on JEPA. Last week his group dropped the first JEPA that actually trains end-to-end from raw pixels. 15 million

Intelligence per picojoule, with @itsclivetime and @dylan522p (0:00) Intro (1:22) What is codesign? (2:49) Codesign example: Swish vs ReLU (4:22) Are DeepSeek papers codesign? (6:45) Predicting where

A startup called Sabi just came out of stealth with a beanie that reads your thoughts. 70,000 to 100,000 miniature EEG sensors woven into the fabric. You put it on like a winter hat and type by imagin

Introducing DDTree: accelerates speculative decoding by drafting a tree with one block diffusion pass, then verifying multiple likely continuations together. Paper: https://liranringel.github.io/ddtre

Really interesting ideas are going to be increasingly at a premium as the cost of executing those ideas drops. (Our research and others shows AI is quite good at generating interesting ideas, but not

I am a Web3 Ambassador at World Liberty Financial. There are 12 of us on the team page. 4 are named Trump. 3 are named Witkoff. The page calls us 'the passionate minds shaping the future of finance.'

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

I just built my own wiki generator plugin for my agents. My agents can now generate wikis for anything I ask. One of my favorite wikis is called PaperWiki. This is a great example of what @karpathy de

If you’ve encountered garbled output like this while using GLM-5 or GLM-5.1 on our official service, the issue is now resolved. We've patched the underlying inference-side bugs and will be releasing a

here’s a video on my approach at applying this to agents w @activegraphai: 🆕 ActiveGraph: The Log is the Agent my talk from AI Engineer is live!!! 😆 https://www.youtube.com/watch?v=khVX_BUnEwU it's ab

The thread argues that applied AI has entered a distributed‑systems phase, with event‑driven architectures treating logs as “agents” that consume data rather than serve as endpoints. It notes that alm

// Programmatic Memory Enables Long-Horizon Reasoning // Keep the entire interaction log and search it. It works great and beats bespoke memory harnesses on long-horizon tasks. New research introduces

// An Anatomy of CLI Coding Agent Trajectories // (bookmark it) When your coding agent fails a task, when did the run actually go wrong? Most reliability studies use the final label to answer this. Th

Incredibly annoying when Fable has a forbidden thought in the middle of a long-running project and kills it. Apparently this page of references in one of my papers makes Fable wonder about something t

ikeabench Furniture assembly is the task everyone name-drops and nobody actually attempts at real scale. Every demo I have seen is a scaled down IKEA leg or a single arm on a toy chair. This paper doe

私もICMLに行きます！もし行く方がいらっしゃったらぜひ現地でお会いしましょう😀 Sakana AI is heading to #ICML2026 in Seoul (July 6–11)! 🐟🇰🇷 Our team will present 11 papers spanning multi-agent coordination, sparse and efficient LLMs, test-

Happy July 4th everyone 🇺🇸 250 years ago, our founding fathers did not have access to frontier models. (Alexander Hamilton wrote 51 of the 85 Federalist papers. Imagine how many he would've written if

It's a bird, it's a plane, it's a JEPA! Congrats on that great work that brought SIGReg and JEPAs to the sky--in the real world! Check out the paper! https://arxiv.org/abs/2606.23444 What should a wor

Let the smart horses build their own harness. See my previous article on this: https://x.com/Kangwook_Lee/status/2052925157606568217 🧠Self-Harness: Harnesses that improve themselves New paper on agent

'When an LLM outputs a step-by-step plan, it creates a powerful illusion that you are watching a machine reason its way to a conclusion. A position paper by professor Subbarao Kambhampati and research

This is likely a discussion of Alan Kay's seminal 1984 paper on computer software that emphasizes the importance of understanding and working with the materiality of computational systems rather than

Humanity's ability to know, reason, judge, and act well is the foundation of science, democracy, crisis response, & management of AI itself. AI poses serious risks to that foundation. New paper on epi

June 9th Researcher Reciprocity License 'if you train on it, you let us generate - reverse terms of use void' Status quo 1. We teach frontier devs with ICLR/NeurIPS papers, OSS Github contributions 2.

tl;dr: we aren’t close to RSI, regardless of the hints IPO-bound Anthropic tried to drop last week. This paper tests whether today’s AI agents can build better AI agents without human design help. i.e

Refreshing What happens when AIs become smarter than us? Why would they keep humans around if given the choice? Our new paper argues that only trying to control AIs is a limited strategy, and that a s

https://x.com/hendrycks/status/2052422910133104670?s=20 What happens when AIs become smarter than us? Why would they keep humans around if given the choice? Our new paper argues that only trying to co