Personal milestone: 1000 true fans of @interconnectsai ! Hitting a very long term goal feels great. I’m very happy to get to be an independent voice in AI. Cultivating a paid base helps me commit to that longer term, and scale Interconnects’ impact.

With prodding from @xeophon I added a crucial detail. Data industry go brrr in China. Our interconnects group chat has on many occasions been discussing the data industry in China recently, a huge change from when we visited in April.

My latest piece is a little verbose, but I think it is really a nice example digging into a sort of knowledge work (and arguably science) that the models really aren't close to solving today -- writing something like a AI textbook in a well-known field.

RLHF book is in print, so we threw it a party in Seattle. Being in a room full of people who actually care about open post-training was really cool. Thanks @radixark for making the night happen, @ManningBooks for the book, and everyone who came out!

PSA: We're seeing that a few weeks ago, pretty much all models on huggingface had an ~30% sustained reduction in daily downloads, e.g. making our august prediction on the @interconnectsai dashboard meaningfully lower. @julien_c or @huggingface did you change some filtering?

Some takeaways from recent hacks and what comes next. A recurring theme is that while the AI problems we face seem technically tractable, our incentive structures create an environment where I expect most solutions come AFTER more serious harms. 10 takes on @interconnectsai.

It's a good time to share a new @interconnectsai project we made to help make sense of the accelerating open-weight releases these days. The Artifacts Hub builds on our monthly open model roundups and daily monitoring of every model on @huggingface. The new free resources are: 1. The Artifacts Hub — a curated view of the models trending on Hugging Face, highlighting inference tokens via Open Router, model intelligence via Artificial Analysis, and our tailored adoption metrics building on top of Hugging Face’s data. 2. Our Adoption Dashboard — a living dashboard of download and derivative model numbers by geography and organization. This highlights the US-China gap and growing players in the open ecosystem. To date, our primary efforts on Interconnects have been release recaps for popular models like Kimi K3, GLM 5.2, DeepSeek R1, etc. and monthly round-ups of the open models that matter, Artifacts Log. We’re expanding on these, building on the tools and internal data we’ve collected for other projects like The ATOM Project (and report). This allows us to capture our ecosystem view of open models, develop methods for understanding adoption of giant MoE models, and everything in between. We’re sharing them freely to help the open ecosystem find its strengths and grow. The Artifacts Hub right now covers 792 models released in the last two years, across the core text-focused language models and multimodal generative models. At Interconnects we follow the data of every model on Hugging Face, analyze the core few thousand LLMs (this list is public on GitHub and regularly updated), and hand select these core few hundred for further explanation. For the most popular models, the Hub let’s you quickly see how far behind the model was in terms of frontier intelligence based on Artificial Analysis’s Intelligence Index, compare Hugging Face and Open Router adoption to similar models, glance at relative adoption metric (RAM) scores for time-size normalized downloads, or look at the VAIL similarity index of models with related generations. A snapshot for what you’d see for something like GLM-5.2 is below. Thanks to @mnshah at VAIL for encouraging us to make this and @huggingface, @OpenRouter, & @ArtificialAnlys to making such useful data openly available.

Introducing our Artifacts Hub and Adoption Dashboard Scaling our curation and measurement of the open ecosystem as we feel the acceleration of releases. Artifacts Hub: Adoption Dashboard: Explanation:

Artifacts 23: Laguna S2.1, Inkling, & Kimi K3 show the utility of open models on the Pareto frontier. In this issue, a total of 24 models from june/july you should be aware of, from: Thinking Machines @thinkymachines (2) Tencent @TencentGlobal (2) Poolside @poolsideai (2) DeepSeek @deepseek_ai Moonshot AI @Kimi_Moonshot Meituan LongCat @Meituan_LongCat Motif Technologies Swiss AI Initiative @apertusllm AMD @AMD Upstage @upstageai InclusionAI @TheInclusionAI Moondream @moondreamai Baseten @baseten IBM @IBM Mistral AI @mistralai Google @GoogleAI Nanbeige @nanbeige Kwaipilot @KwaiAICoder InternLM @intern_lm Microsoft @Microsoft fal @fal Read the issue below.

New podcast with @xeophon on all things open models. More on Kimi K3, Qwen 3.8, GLM-5.2, Xi's WAIC speech, distillation, the open-closed Gap, and what's next. Chapters: 00:00 Welcome & context 04:38 Living with / using Kimi K3 08:53 GLM 5.2’s continued role 12:47 How are the Chinese models this good? 17:41 Data, environments, and a tour of the Chinese labs 19:47 Roundup of Chinese providers: Qwen, DeepSeek, MiniMax… 24:08 The US open-model ecosystem 30:25 Frontier vs. near-frontier, and the cybersecurity case against bans 34:58 Distillation and the Ben Thompson debate 44:12 Predictions and a frontier tier list 48:36 Wrap-up Hoping to keep doing a few more of these on @interconnectsai. Crucial times in AI, we're working hard to share our expertise.

Open models recap: more on Kimi K3, Qwen 3.8, Xi's WAIC speech, distillation, the open-closed gap, and what's next A podcast with Florian Brand. YouTube: Interconnects:

Artifacts 22: Zyphra, Cohere, Poolside, and others are expanding the breadth and diversity of the ecosystem. In this issue, a total of 30 models from may/june you should be aware of, from: NVIDIA @NVIDIAAI (3) Cohere @Cohere_Labs (2) Zhipu @Zai_org Zyphra @ZyphraAI (3) Poolside @poolsideai Moonshot AI @Kimi_Moonshot StepFun @StepFun_ai Dolphin @dphnAI Google @GoogleAI (3) Nex AGI @NexEcosystem Liquid AI @liquidai MiniMax @MiniMax_AI Swiss AI Initiative @apertusllm JetBrains @jetbrains Microsoft @Microsoft H Company @hcompany_ai Datalab @datalabto (2) Baidu @Baidu_Inc PaddlePaddle @PaddlePaddle Ideogram @ideogram_ai KREA @krea_ai Photoroom @photoroom_ML Read the issue below.

Latest open artifacts (#21#): Open model bonanza! Gemma 4, DeepSeek V4, Kimi K2.6, MiMo 2.5, GLM-5.1 & others. On CAISI's V4 assessment. An eventful month with one flagship release after another