research

Impressive new paper from Meta. (bookmark it) Scaling laws assume model size and training data act on loss independently. This work introduces Skaling law, which couples capacity and data through a si

🚨 BREAKING — Anthropic investors worry Dario Amodei’s AI doom marketing could hurt its upcoming IPO. “He’s more of a religious leader than he is a CEO.” > used to write sensitive OpenAI memos on an of

I concur, and the point is broader than just for Biology. Science does not advance by 'pure thinking' alone. We need to do experiments, and interpret the results of those experiments, which in turn ra

In the era of base LLM scaling (2022-2024), I believed the LLM line of research would reach a capability plateau (as later seen with base LLMs). In late 2024, after the o3 test-time compute demo, I ch

For a very long time most high-performing AI models were end-to-end neural models; vector input -> vector output, with only ultra-thin symbolic preprocessing and postprocessing layers (e.g. label deco

Huge congratulations to @JeffDean and the legendary founding team on the launch! 🚀 I share a deep conviction in this mission. Automating the scientific method will profoundly alter the trajectory of A

I would have assumed it was fairly obvious, but in case it's not: a million-line codebase (also known as a 'harness'), running at inference time, orchestrating thousands of calls to a neural network f

The bottleneck for AI progress was never compute, it was always the verifier. Recursive self-improvement is limited by verification, not computation. Compute buys proposals - verifiers buy knowledge.

Very interesting to see @JeffDean's pitch deck. Just look at those open science and engineering problems. Lots to advance there with automated ML engineering. AI for science and engineering is just ge

arXiv:2409.03901v4 Announce Type: replace Abstract: Remote sensing (RS) image classification is central to Earth observation, but onboard deployment requires models that are accurate, efficient, and r

Horiyuki 'horiyuki42' joined Sakana AI Labs in August 2026 as an Applied Research Engineer Intern. He plans to work full‑time during the university summer recess while concentrating on large‑language‑

Advanced reasoning and problem-solving, plus strong performance in Japanese language and Japan-specific context. Namazu is live on Merge Gateway now! https://x.com/SakanaAILabs/status/2084276852143919

All Chinese AI company media: AI will be a wondrous and wonderful and give you back precious time in your life to do things you love. All US AI company media: AI will take all your jobs, eat your chil

Introducing Sakana Namazu: An LLM API with Japanese-vibes! Today we’re rolling out an upgraded version of our LLM, Namazu, now available as an API. Try Sakana Namazu API: https://sakana.ai/namazu 🐟 🐟

Using optimization at inference time is a foundational concept of Energy-Based Models (EBM) and Objective-Driven AI architectures (ODAI). When the variables to be inferred are continuous, it makes sen

More on the pelican on the bicycle test from @simonw: https://simonwillison.net/2025/Jun/6/six-months-in-llms/ I uploaded the source here so it's playable in the browser, forkable etc. https://karpath

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

To address the limits of deep learning and avoid stalling, the field of AI started by applying patch (1), which started being demoed 9 months later in December 2024 and has now become completely ubiqu

We're starting to leave the territory where you'd test an LLM by e.g. 'create an svg of pelican on a bicycle'. As one idea to generalize it, I was interested what Opus 5 would do if I gave it the firs

Inkling-small. 2 weeks after inkling Nearly as good as Inkling but 4x smaller. We're just getting started...🔥 Today, we are releasing Inkling-Small. Inkling-Small achieves comparable performance to In

Dreaming in Voxels: How AI is Generating Playable Minecraft Worlds Generative AI has conquered images, video, text. But what about interactive 3D environments? We trained models on billions of cubes t

Go ahead and ask yourself, really ask yourself, if all these confident predictors are wrong about jobs and not training radiologists anymore and fast take offs, what else are they wrong about? Then as

Really interesting concept -- instead of optimizing against static benchmarks or internally generated reward models, agents are evaluated through real economic interactions. Using an external market a

Recent discussions about open-sourcing make me feel that I should go back and revisit these important open-source works in representation learning that pushed the field forward and eventually made vis

The Top AI Papers of the Week (July 20 - July 26): - GAMUT - PRO-LONG - Harness Handbook - From Memory to Skills - Progressive Disclosure - Global Workspace in LLMs - Structured Output Collapses Diver

I support open-source models distilling what commercial companies distilled for free from the entire internet. I published distillation for free in 1991 in Europe - this was copied in the US and in Ch

World Modeling with JEPA has recently gained traction thanks to a novel anti-collapse mechanism called 'SIGReg' (by @ylecun and @randall_balestr). The math is clean, but it is rarely explained from fi

Closed source safeguards that infantalize us all and leave American companies defenseless are a menace. Gated access is a menace. Who cares if 100 companies get to defend themselves because they got o

Highly performant open weights frontier models such as Kimi are a competitive threat to OpenAI & Anthropic, but probably for everyone else these are a win. Hope more US entities will release top quali

Not because Andrej is saying it but I think voice is goated. And you can mix it with other modalities for even richer prompting. I recorded a session a few weeks back to demo the power of multimodal p

In July 2026, Clement Delangue tweeted that “Open‑source is not the cause of the cybersecurity crisis, it’s the solution!” linking to the Hugging Face page *fdtn‑ai* (https://huggingface.co/fdtn-ai).

Excited for our first general model Inkling -- open weights, 975B, natively multimodal (text, image, audio). Available on Tinker, HuggingFace and partners. It is yours to personalize and use openly. I

I’m very excited by this test time training work for robotic learning! It’s an awesome collaboration between @StanfordSVL and @NVIDIARobotics ! We scaled a robot model natively to 8,000 timesteps of c

Never too late for any company to get in on open models. Inkling is a MoE transformer with 975B (41B active). Native multimodal support. Context lengths: 64K and 256K. Will be testing and providing th

We scaled a robot model natively to 8,000 timesteps of context, 5 minutes worth of muscle memory, with constant inference cost. Robot policies used to live their lives a few frames at a time (< 0.1 se

1) If you haven't read AI as Normal Technology, these annotated slides are probably the easiest way to get a high-level overview. https://www.cs.princeton.edu/~arvindn/talks/icml-2026-annotated-slides

🤖 Un robot français en seulement 9 mois ! Rémi Cadene, ancien de Tesla AI et Hugging Face, explique comment son équipe veut faire des robots un levier pour la logistique, la réindustrialisation et, de

Hardmaru posted a tweet on July 13, 2026 stating that while language models and coding agents are valuable, “there is more to life, and more to AI, than just LLM agents.” The tweet received 61.1 k vie

VLMは人間のような創造性を持てるか？ ケネス・スタンレー教授らの『目標という幻想（Why Greatness Cannot Be Planned）』は、明確な目標を設定することが、かえって真に偉大な発見を遠ざけてしまうという逆説を論じた書籍です。その議論の中核にあったのが「PicBreeder」の実験でした。 PicBreeder では、ユーザーが「面白い」と感じた画像を選び、それを少しずつ進化

This post addresses a question comparing 'Ultra' and 'Pro' product tiers or model versions, likely clarifying whether they represent meaningfully different offerings or are simply alternative names fo

This post highlights a practical AI agent that operates intuitively without requiring explanation of its underlying mechanics, suggesting it has achieved a user-friendly interface or autonomous functi

This post discusses the conceptual distinction between training-scaling and inference-scaling in machine learning models, while acknowledging related frameworks or concepts (possibly referencing Sol,

🎯 If Trump were actively trying to destroy American advantages, to create chaos and strife that he and his ilk could exploit, what would he do differently? Typical NYT understatement for what is an ap

It's incredible to me that 9 months ago we didnt have an office, and now we have a fully functional humanoid and an efficient AI! So proud of the team 🤠 Starting with the fundamentals Prototype Versio

NEW: Donald Trump has terminated the remaining members of the independent, federal commission that assists election administration officials nationwide just a few months before the midterm elections “

One of my first journeys in neural networks started over a decade ago with implementing CPPN-NEAT! Back then, I built a clone of ‘Picbreeder’ not only to study the mechanics of neural nets, but to exp