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PODCAST · technology

Interconnects

by Nathan Lambert

Audio essays about the latest developments in AI and interviews with leading scientists in the field. Breaking the hype, understanding what's under the hood, and telling stories. www.interconnects.ai

Publisher-supplied feed metadata · PodParley refreshed Oct 5, 2026 · Source feed

Episodes

  1. The Cyber Risk Discourse is Broken

    I’ve had one too many discussions on the cyber risks of open models — where someone assumes that either banning open models happens in a silo (and bad actors will somehow actually be stopped) or that China is a threat and doesn’t care about AI safety — that I feel we’re going to end up making...

  2. Debating RSI, the US-China Gap, and Jaggedness with JS Denain of Epoch AI

    This episode is with Jean-Stanislas “JS” Denain of Epoch AI, who leads their Insights Team and is one of the people I find myself debating the state and trajectory of AI with more and more. We’ve had follow-on discussions of many of my favorite recent posts online and/or in private, so I wanted…

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  3. The current balance of power in open models

    I was recently invited to brief a group of Congressional members and staff on the state of open-weight models in the lens of U.S.-China competition. I’m sharing my prepared remarks as a state of the union on open models that is accessible to a broader audience. Interconnects AI is a...

  4. Why I still haven’t bought into true RSI

    We’re in an era where a few organizations are using thousands of concurrent agents to improve their processes and output. These organizations happen to be just the frontier AI labs, in particular OpenAI and Anthropic. In the last few weeks, I’ve been pondering what it means for so many employees...

  5. One resignation turned the embers of AI fear into a wildfire

    As AI became more powerful, it was inevitable that a different, growing group would start to take AI safety more seriously – what we did not know ahead of time, is which set of views they latched onto. We have seen that some of the most extreme views of risk, i.e. moderate probabilities of mass...

  6. When will average people feel AI’s impact?

    Housekeeping: Paid subscribers to Interconnects now get a permanent 40% discount on my book when purchasing at Manning.com. Access the code at the Interconnects perks page. Many AI optimists tend to compare what is happening in this AI boom to the industrial revolution, or to other periods of…

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  7. I wrote an AI textbook — how long until AI can do it better?

    There are a lot of criticisms of AI writing, but most of them are focused on more creative, high-voice writing like this blog. Those — including my own piece — often argue that it is because good writing is high-voice, has a point of view, has a deep human expression that needs to come across…

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  8. Open models recap: more on Kimi K3, Qwen 3.8, Xi's WAIC speech, distillation, the open-closed gap, and what's next

    Exciting news! My book trying to share post-training knowledge with the world is done and shipping soon. Order on Manning or Amazon. Thanks for the support. It’s currently the #1 AI book on Amazon :). Nathan and Florian sit down to discuss everything happening with open models. Following the Kimi...

  9. Kimi K3: The open-weights escalation

    On Thursday July 16th, Moonshot AI released their latest flagship model Kimi K3. K3 is a 2.8T parameter MoE model which will have its weights released on July 27th. Much of this article follows as a reflection on the state of the ecosystem, under the assumption that Moonshot keeps their promise…

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  10. GLM-5.2 is the step change for open agents

    Housekeeping: Following my “State of the blog” post last week, noting a slight increase in paid features, it’s a good time to remind folks that I offer group subscriptions with larger discounts proportional to the number of seats. I also released a new paper today on open RL recipes for terminal...

  11. Banning Open Source AI Would Be A Mistake

    This post was originally an op-ed co-authored with Kevin Xu of Interconnected for a general, non-technical audience. The gatekeepers — the many media outlets we pitched it to — passed on publishing it. Luckily, we have our own platforms to get the message out. Please help us forward this op-ed to...

  12. State of the blog, mid-2026

    As I navigate my career change after Ai2, I wanted to share my views of how this blog relates to my missions and broader work. In my farewell post, I summarized my three goals right now as: * Provide clarity in the evolution of frontier models. * Create a vibrant and diverse open (model)…

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  13. Frontier post-training recipe review with Finbarr Timbers

    As I’ve been recapping fundamentals of post-training to wrap up my RLHF / Post-training book I knew I needed to get Finbarr Timbers back on the podcast to talk about the state of play. Over the last few months we’ve had many discussions on what we’d need to do to take an Olmo-style recipe to the...

  14. Claude Fable 5 and new AI safety fables

    Edit Jun. 11: Anthropic changed their silent model manipulation of AI research queries to also use a classifier like the other safety domains. This addresses a key concern I had in the mistreatment of “safety” in the release, and props to Anthropic for a quick change, but it does not fully…

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  15. Farewell Ai2

    I’m departing the Allen Institute for AI (Ai2), where I got the great privilege to work on the Olmo models, to grow, to learn, and to have broad lasting impacts. This post is an attempt to reflect on why what we did was influential, despite obviously being far from the frontier in performance…

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  16. Open and closed models are on different exponentials

    The largest debate that’ll define the future balance of power between the open and closed AI model ecosystems is primarily economic — it’s if users of AI will continue to pay dramatically more, i.e. large margins, for the top closed models. Early 2026 is a seminal time for the AI industry, as the...

  17. Some ideas for what comes next, May 2026

    As the years of AI progress go by, it’s been accompanied by a slowly rising tide of consequence. Models are getting more capable, how we work is changing quickly, economics of AI are becoming real, just as real-world risks come to the forefront. 2026 is the first year where I don’t think there’ll...

  18. Notes from inside China's AI labs

    Staring out the window on a new, high-speed train from Hangzhou to Shanghai I’m gifted with views of dramatic ridgelines speckled with wind turbines that are silhouetted against the setting sun. The mountains cast a backdrop to a mix of spanning fields and clustered skyscrapers. I’m returning…

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  19. The distillation panic

    ‘Distillation attacks’ is a horrible term for what is happening right now. Yes, some Chinese labs are hacking or jailbreaking APIs to attempt to extract more signal from model APIs — stopping this is important to maintain the U.S.’s lead in AI capabilities. Referring to this as distillation…

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  20. My bets on open models, mid-2026

    We’re living through the period of time when we’ll learn if open models can keep up with closed labs. The obvious answer is that no, they won’t. This answer is a form of saying they won’t keep up in every area. This framing closes off a popular prediction where the open models completely catch…

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  21. The inevitable need for an open model consortium

    Recently, I was talking with Percy Liang, Stanford professor and lead of the Marin project (another fully-open model lab), and it set in on me that there will eventually be a consortium of companies funding a foundational set of open models used across industry. It’s not clear when this’ll…

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  22. Claude Mythos and misguided open-weight fearmongering

    With the announcement of the Claude Mythos model this week and the admittedly very strong stated abilities, especially in cybersecurity, a new wave of anti open-weight AI model narratives surged. The TL;DR of the argument is that our digital infrastructure will not be ready in time for an...

  23. Gemma 4 and what makes an open model succeed

    Having written a lot of model release blog posts, there’s something much harder about reviewing open models when they drop relative to closed models, especially in 2026. In recent years, there were so few open models, so when Llama 3 was released most people were still doing research on Llama 2…

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  24. Lossy self-improvement

    Fast takeoff, the singularity, and recursive self-improvement (RSI) are all top of mind in AI circles these days. There are elements of truth to them in what’s happening in the AI industry. Two, maybe three, labs are consolidating as an oligopoly with access to the best AI models (and the…

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  25. GPT 5.4 is a big step for Codex

    I’m a little late to this model review, but that has given me more time to think about the axes that matter for agents. Traditional benchmarks reduce model performance to a single score of correctness – they always have because that was simple, easy to quickly use to gauge performance, and so on....

  26. What comes next with open models

    2025 was the year where a lot of companies started to take open models seriously as a path to influence in the extremely valuable AI ecosystem — the adoption of a strategy that was massively accelerated downstream of DeepSeek R1’s breakout success. Most of this is being done as a mission of hope,...

  27. Dean Ball on open models and government control

    Watching history unfold between Anthropic and the Department of War (DoW) it has been obvious to me that this could be a major turning point in perspectives on open models, but one that’ll take years to be obvious. As AI becomes more powerful, existing power structures will grapple with their…

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  28. Olmo Hybrid and future LLM architectures

    So-called hybrid architectures are far from new in open-weight models these days. We now have the recent Qwen 3.5 (previewed by Qwen3-Next), Kimi Linear last fall (a smaller release than their flagship Kimi K2 models), Nvidia’s Nemotron 3 Nano (with the bigger models expecting to drop soon), IBM...

  29. How much does distillation really matter for Chinese LLMs?

    Distillation has been one of the most frequent topics of discussion in the broader US-China and technological diffusion story for AI. Distillation is a term with many definitions — the colloquial one today is using a stronger AI model’s outputs to teach a weaker model. The word itself is derived...

  30. Opus 4.6, Codex 5.3, and the post-benchmark era

    Last Thursday, February 5th, both OpenAI and Anthropic unveiled the next iterations of their models designed as coding assistants, GPT-5.3-Codex and Claude Opus 4.6, respectively. Ahead of this, Anthropic had a firm grasp of the mindshare as everyone collectively grappled with the new world of...

  31. Why Nvidia builds open models with Bryan Catanzaro

    One of the big stories of 2025 for me was how Nvidia massively stepped up their open model program — more releases, higher quality models, joining a small handful of companies releasing datasets, etc. In this interview, I sat down with one of the 3 VP’s leading the effort of 500+ technical staff,...

  32. Thoughts on the job market in the age of LLMs

    There’s a pervasive, mutual challenge in the job market today for people working in (or wanting to work in) the cutting edge of AI. On the hiring side, it often feels impossible to close, or even get interest from, the candidates you want. On the individual side, it quite often feels like the...

  33. Arcee AI goes all-in on open models built in the U.S.

    Arcee AI is a the startup I’ve found to be taking the most real approach to monetizing their open models. With a bunch of experience (and revenue) in the past in post-training open models for specific customer domains, they realized they needed to both prove themselves and fill a niche by...

  34. Get Good at Agents

    Two weeks ago, I wrote a review of how Claude Code is taking the AI world by storm, saying that “software engineering is going to look very different by the end of 2026." That article captured the power of Claude as a tool and a product, and I still stand by it, but it undersold the changes that...

  35. Use multiple models

    I’ll start by explaining my current AI stack and how it’s changed in recent months. For chat, I’m using a mix of: * GPT 5.2 Thinking / Pro: My most frequent AI use is getting information. This is often a detail about a paper I’m remembering, a method I’m verifying for my RLHF Book, or some other...

  36. Claude Code Hits Different

    There is an incredible amount of hype for Claude Code with Opus 4.5 across the web right now, which I for better or worse entirely agree with. Having used coding agents extensively for the past 6-9 months, where it felt like sometimes OpenAI’s Codex was the best and sometimes Claude, there was…

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  37. Open models: Hot or Not with Nathan Lambert & Florian Brand

    Nathan sits down with Florian, our open model analyst to get spicy into debates of which labs won and lost momentum in open models of 2025. Reflection 70B, Huawei repackaging someone else's model as their own, the fall of Llama — no drama is left unturned. We also dig into the nuances that we...

  38. New Talk: Building Olmo 3 Think

    It’s finally here! The public (and most complete) version of my talk covering every stage of the process to build Olmo 3 Think (slides are available). I’ve been giving this, improving it, and getting great feedback at other venues such as The Conference on Language Modeling (COLM) & The PyTorch...

  39. Olmo 3: America’s truly open reasoning models

    We present Olmo 3, our next family of fully open, leading language models. This family of 7B and 32B models represents: * The best 32B base model. * The best 7B Western-origin thinking & instruct models. * The first 32B (or larger) fully open reasoning model. This is a big milestone for Ai2 and…

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  40. Why AI writing is mid

    First, on the topic of writing, the polished, and more importantly printed, version of my RLHF Book is available for pre-order. It’s 50% off for a limited time, you can pre-order it here! Like a lot of writing, I’ve been sitting on this piece for many months thinking it’s not contributing enough,...

  41. Interview: Ant Group's open model ambitions

    This is the first of a handful of interviews I’m doing with teams building the best open language models of the world. In 2025, the open model ecosystem has changed incredibly. It’s more populated, far more dominated by Chinese companies, and growing. DeepSeek R1 shocked the world and now there…

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  42. 5 Thoughts on Kimi K2 Thinking

    First, congrats to the Moonshot AI team, one of the 6 “AI Tigers” in China, on the awesome release of Kimi K2 Thinking. One of the overlooked and inspiring things for me these days is just how many people are learning very quickly to train excellent AI models. The ability to train leading AI…

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  43. Burning out

    One of the obvious topics of the Valley today is how hard everyone works. We’re inundated with comments on “The Great Lock In”, 996, 997, and now even a snarky 002 (midnight to midnight with a 2 hour break). Plenty of this is performative flexing on social media, but enough of it is real and...

  44. How to scale RL

    Two quick housekeeping items before I get to the post.1. I’ll be in SF this week for the PyTorch conference (22-23), AI Infra Summit (21st), and other local events. Come say hi.2. I launched a new Substack AI bundle with 8 of my favorite publications packaged together for teams of 20+. Learn more...

  45. The State of Open Models

    This talk covers everything that’s happened this year in the open model landscape — DeepSeek kickstarting the Chinese open model norms, Llama’s fade, Qwen’s dominance, GPT-OSS — and what comes next. It is my attempt to share what people need to know about where open models are heading, building…

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  46. Thoughts on The Curve

    I spent the weekend debating AI timelines, among other things, at The Curve conference. This translates as spending the weekend thinking about the trajectory of AI progress with a mix of DC and SF types. This is a worthwhile event that served as a great, high-bandwidth way to check in on…

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  47. ChatGPT: The Agentic App

    Ever since ChatGPT exploded in popularity, there has been a looming “how” to its monetization plans. Much has been said about shopping and advertising as the likely paths, especially with Fidji Simo joining as CEO of Applications under Sam Altman. Advertising as a business model for AI is logical...

  48. Thinking, Searching, and Acting

    The weaknesses of today’s best models are far from those of the original ChatGPT — we see they lack speed, we fear superhuman persuasion, and we aspire for our models to be more autonomous. These models are all reasoning models that have long surpassed the original weaknesses of ChatGPT-era...

  49. Coding as the epicenter of AI progress and the path to general agents

    Coding, due to its breadth of use-cases, is arguably the last tractable, general domain of continued progress for frontier models that most people can interface with. This is a bold claim, so let’s consider some of the other crucial capabilities covered in the discourse of frontier models: * Chat...

  50. On China's open source AI trajectory

    Hello everyone! I’m coming back online after two weeks of vacation. Thankfully it coincided with some of the slowest weeks of the year in the AI space. I’m excited to get back to writing and (soon) share projects that’ll wrap up in the last months of the year. It seemed like a good time to remind...

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ABOUT THIS SHOW

Audio essays about the latest developments in AI and interviews with leading scientists in the field. Breaking the hype, understanding what's under the hood, and telling stories.

www.interconnects.ai

HOSTED BY

Nathan Lambert

CATEGORIES

Frequently Asked Questions

How many episodes does Interconnects have?

Interconnects currently has 164 episodes available on PodParley. New episodes are automatically indexed when they're published to the podcast feed.

What is Interconnects about?

Audio essays about the latest developments in AI and interviews with leading scientists in the field. Breaking the hype, understanding what's under the hood, and telling stories. www.interconnects.ai

How often does Interconnects release new episodes?

Interconnects publishes regularly with 164 episodes available. Check the episode list for the typical release schedule.

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You can listen to Interconnects on PodParley by clicking any episode. We provide an embedded audio player for direct listening, and you can also subscribe via your preferred podcast app using the RSS feed.

Who hosts Interconnects?

Interconnects is created and hosted by Nathan Lambert.
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