iiinova — where your digital self keeps evolving

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Maarten Grootendorst @maartengr.bsky.social · 24/11/2025

And here you have it! The cover of our “An Illustrated Guide to AI Agents” book! Why a Dolphin? The process of choosing cover animals is a closely guarded secret held deep within the legendary halls of O'Reilly. @jayalammar.bsky.social and I do not get to choose it, but we love it!

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Jay Alammar @jayalammar.bsky.social · 03/11/2025

Inside NeurIPS 2025: The Year’s AI Research, Mapped New blog post! NeurIPS 2025 papers are out—and it’s a lot to take in. This visualization lets you explore the entire research landscape interactively, with clusters and @cohere.com LLM-generated explanations that make it easier to grasp.

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Maarten Grootendorst @maartengr.bsky.social · 13/10/2025

Excited to share that @jayalammar.bsky.social and I are writing the book “An Illustrated Guide to AI Agents” with @oreilly.bsky.social 🥳 Our new book will contain chapters on the fundamentals of agents (memory, tools, and planning), alongside more advanced concepts like RL and reasoning LLMs.

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Jay Alammar @jayalammar.bsky.social · 13/10/2025

The Illustrated Guide to AI Agents New book announcement! Thrilled that together with @maartengr.bsky.social , we're writing a new book titled “An Illustrated Guide to AI Agents” and published by @oreilly.bsky.social.

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Antoine Bosselut @abosselut.bsky.social · 03/09/2025

The next generation of open LLMs should be inclusive, compliant, and multilingual by design. That’s why we @icepfl.bsky.social @ethz.ch @cscsch.bsky.social ) built Apertus.

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Jay Alammar @jayalammar.bsky.social · 19/08/2025

The Illustrated GPT-OSS New post! A visual tour of the architecture, message formatting, and reasoning of the latest GPT. newsletter.languagemodels.co/p/the-illust...

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Jay Alammar @jayalammar.bsky.social · 23/05/2025

The legendary John Carmack at #upperbound: - Current AI focus is RL (with Richard Sutton) solving Atari games - Thinking in line with the Alberta Plan. - It was a misstep to start working too low-level (e.g., at the cuda level). I kept stepping up the stack chain until now in pytorch

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Adam Hill @astroadamh.bsky.social · 20/05/2025

I'm really excited for this year's PyData London conference - there are some awesome talks on the schedule and I'm excited to hear the keynote speakers @jayalammar.bsky.social, Tony Wears, & Leanne Fitzpatrick #pydata #datascience

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PyData London @pydatalondon.bsky.social · 20/05/2025

Unleash your inner data aficionado at PyData London 2025, 6-8 June at Convene Sancroft, St. Paul’s! We have 3 top flight keynotes lined up for you this year from @jayalammar.bsky.social, Leanne Kim Fitzpatrick and Tony Mears. Just 17 days left. Book your tickets now! pydata.org/london2025

Advertisement for PyData London 2025 conference.

Headline: Meet your keynote speakers

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- Tony Mears
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Max Bartolo @maxbartolo.bsky.social · 27/03/2025

I'm excited to share the tech report for our @cohere.com @cohereforai.bsky.social Command A and Command R7B models. We highlight our novel approach to model training including self-refinement algorithms and model merging techniques at scale. Read more below! ⬇️

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Tom Aarsen @tomaarsen.com · 21/02/2025

We've just released MMTEB, our multilingual upgrade to the MTEB Embedding Benchmark! It's a huge collaboration between 56 universities, labs, and organizations, resulting in a massive benchmark of 1000+ languages, 500+ tasks, and a dozen+ domains. Details in 🧵

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Maarten Grootendorst @maartengr.bsky.social · 11/02/2025

Did you know we continue to develop new content for the "Hands-On Large Language Models" book? There's now even a free course available with @deeplearningai.bsky.social!

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Mason Youngblood @masonyoungblood.bsky.social · 05/02/2025

Do whales optimize their vocalizations for efficiency, just like human language? 🐋🎶 My latest study in Science Advances (@science.org) suggests they do—following linguistic laws seen in human speech. 🧵 www.science.org/doi/10.1126/...

science.org

Language-like efficiency in whale communication

Whale vocalizations follow efficiency rules seen in human language, revealing striking similarities in communication systems.

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Ellen Garland @ellengarland.bsky.social · 06/02/2025

We uncovered the same statistical structure that is a hallmark of human language in whale song, published today in Science. @inbalarnon.bsky.social @simonkirby.bsky.social @jennyallen13.bsky.social @clairenea.bsky.social @emma-carroll.bsky.social www.science.org/doi/10.1126/...

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Naomi Saphra @nsaphra.bsky.social · 27/01/2025

One of my grand interpretability goals is to improve human scientific understanding by analyzing scientific discovery models, but this is the most convincing case yet that we CAN learn from model interpretation: Chess grandmasters learned new play concepts from AlphaZero's internal representations.

arxiv.org

Bridging the Human-AI Knowledge Gap: Concept Discovery and Transfer in AlphaZero

Artificial Intelligence (AI) systems have made remarkable progress, attaining super-human performance across various domains. This presents us with an opportunity to further human knowledge and improv...

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Jay Alammar @jayalammar.bsky.social · 27/01/2025

The Illustrated DeepSeek-R1 Spent the weekend reading the paper and sorting through the intuitions. Here's a visual guide and the main intuitions to understand the model and the process that created it. newsletter.languagemodels.co/p/the-illust...

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Jay Alammar @jayalammar.bsky.social · 15/01/2025

Alphaxiv is an awesome way to discuss ML papers -- often with the authors themselves. Here's an intro and demo by @rajpalleti.bsky.social we shot at #Neurips2024 www.youtube.com/watch?v=-Kwl...

youtube.com

AlphaXiv - a great place to discuss ML papers

YouTube video by Jay Alammar

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Tom Aarsen @tomaarsen.com · 14/01/2025

The newest extremely strong embedding model based on ModernBERT-base is out: `cde-small-v2`. Both faster and stronger than its predecessor, this one tops the MTEB leaderboard for its tiny size! Details in 🧵

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Jay Alammar @jayalammar.bsky.social · 14/01/2025

Floored that the repo for Hands-On Large Language Models is now at 3.6k Github stars! And excited that professors are starting to use the book to teach LLM courses. Reach out to us if we can be of assistance! And if you've liked the book, leave us a review on Amazon or Goodreads!

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Jay Alammar @jayalammar.bsky.social · 13/01/2025

SWE-Bench has been one of the most important tasks measuring the progress of agents tackling software engineering in 2024. I caught up with two of its creators, @ofirpress.bsky.social and Carlos E. Jimenez to share their ideas on the state of LLM-backed agents. www.youtube.com/watch?v=bivZ...

youtube.com

SWE-Bench authors reflect on the state of LLM agents at Neurips 2024

YouTube video by Jay Alammar

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Nathan Lambert @natolambert.bsky.social · 20/12/2024

OpenAI's o3: The grand finale of AI in 2024 A step change as influential as the release of GPT-4. Reasoning language models are the current and next big thing. I explain: * The ARC prize * o3 model size / cost * Dispelling training myths * Extreme benchmark progress

buff.ly

o3: The grand finale of AI in 2024

A step change as influential as the release of GPT-4. Reasoning language models are the current big thing.

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Jay Alammar @jayalammar.bsky.social · 12/12/2024

Good morning #NeurIPS2024! Stop by the @cohere.com booth at 3PM today (Thursday) for a signed copy of Hands-On Large Language Models - it will introduce you to LLMs, their applications, as well as Cohere's Embed, Rerank, and Command-R models. Come early as quantities are limited!

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Jay Alammar @jayalammar.bsky.social · 11/12/2024

I'll be in the Cohere #NeurIPS2024 booth most of this afternoon. Come say hi, ask questions, and yes, we're hiring! Tomorrow I'll be signing copies of my book at 3PM! Limited copies available!

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Jay Alammar @jayalammar.bsky.social · 10/12/2024

Hi NeurIPS! Explore ~4,500 NeurIPS papers in this interactive visualization: jalammar.github.io/assets/neuri... (Click on a point to see the paper on the website) Uses @cohere.com models and @lelandmcinnes.bsky.social's datamapplot/umap to help make sense of the overwhelming scale of NeurIPS.

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Jay Alammar @jayalammar.bsky.social · 29/11/2024

Sure to be thought provoking. The previous interview had fascinating thoughts on scifi (Dune Vs. Foundation), on AI competition for AI safety, and on successful scifi as a self-preventing prophecy.

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Jay Alammar @jayalammar.bsky.social · 28/11/2024

Excited to see you all at NeurIPS this year! Let's hang!

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Jay Alammar @jayalammar.bsky.social · 26/11/2024

Join us for a panel on scientific communication Dec 4!

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Max Bartolo @maxbartolo.bsky.social · 20/11/2024

🚨 LLMs can learn to reason from procedural knowledge in pretraining data! 🚨 I particularly enjoy research where the evidence contradicts our initial hypothesis. If you're interested in LLM reasoning, check out the 60+ pages of in-depth work at arxiv.org/abs/2411.12580

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Chris McKitterick @mckitterick.bsky.social · 20/11/2024

Have you updated your handle to use your own domain? I'm in the process of updating my handle to use the adastra-sf.com doman, but though I've tried both methods of uploading a TXT file to my server (DNS interface and no interface), it's not resolving even after half an hour. Tips? Ideas?

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Evan Peck @peck.phd · 20/11/2024

Trying something new: A 🧵 on a topic I find many students struggle with: "why do their 📊 look more professional than my 📊?" It's *lots* of tiny decisions that aren't the defaults in many libraries, so let's break down 1 simple graph by @jburnmurdoch.bsky.social 🔗 www.ft.com/content/73a1...

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Maarten Grootendorst @maartengr.bsky.social · 18/11/2024

🍿 Introducing the animated "Visual Guide to Mixture of Experts (MoE)"! This was a blast to make and contains more in-depth descriptions than the original already had! Expect even more intuition as we break down visuals and discover the nuances behind MoE. www.youtube.com/watch?v=sOPD...

youtube.com

A Visual Guide to Mixture of Experts (MoE) in LLMs

YouTube video by Maarten Grootendorst

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Jay Alammar @jayalammar.bsky.social · 20/11/2024

I loved Daniel Dennett's From Bacteria to Bach and Back and its analogies between biological minds and computing paradigms. Chapter 4, especially, which speaks about how an intelligent being can have "competence without comprehension".

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