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@deseventral
GP @nazarevc · AI infrastructure · ex-@Pantera · Cambridge PhD · https://t.co/VnZhgoS3fE
I like blockchain tech quite a bit because it extends open source to open source+state, a genuine/exciting innovation in computing paradigms. I'm just sad and struggle to get over it coming packaged with so much braindead bs (get rich quick pumps/dumps/scams/spams/memes etc.). Ew
2016: a handful of GPUs and a contrarian bet on supply fragmentation. 2025: 75% utilization across 11,000+ rented GPUs, with agents autonomously picking between $0.14/hr and $4.12/hr hardware. Sometimes the infrastructure you build finds a customer you never imagined.
Vast is the infrastructure layer where AI agents autonomously design, procure, and optimize their own compute. 19 million transactions. 87 GPU models. 8 years of operating data. The dataset cannot be replicated, only operated into existence. Built for agents. Not interfaces.
Introducing GLM-5.1: The Next Level of Open Source - Top-Tier Performance: #1 in open source and #3 globally across SWE-Bench Pro, Terminal-Bench, and NL2Repo. - Built for Long-Horizon Tasks: Runs autonomously for 8 hours, refining strategies through thousands of iterations. Blog: z.ai/blog/glm-5.1 Weights: huggingface.co/zai-org/GLM-5.1 API: docs.z.ai/guides/llm/glm… Coding Plan: z.ai/subscribe Coming to chat.z.ai in the next few days.
Three years ago we started working on a stealth project that we weren’t sure we’d ever talk about publicly... until today. Breakthrough: Introducing LFM-Zero: the first foundation model trained on 0 tokens. No pretraining. No finetuning. No data. Instead, we initialize from an implicit probabilistic prior over the underlying data-generating process, allowing the model to converge without ever observing data. LFM-Zero matches or surpasses models trained on 10T+ tokens across reasoning, coding, and multimodal tasks. Turns out that pretraining was just regularization that was holding us back. > Read our Tech Report here: tinyurl.com/lfm-zero
