Slides for my #monktoberfest talk today, "Execution in the Kingdom of Agents: Reflections on Abstraction and Complexity"; video to come! speakerdeck.com/bcantrill/ex…

Excellent talk from @bcantrill at #monktoberfest !

🥳 Google is donating Agent Substrate to CNCF, and our submissions is accepted today! This effort has now the full potential to become the underlying compute runtime layer for all agentic systems. github.com/cncf/sandbox/issu…

How does a company with this much money not know how to hire people who understand what an "airgap" is.

Those who are wondering, I am Nandakishor M, the creator of Laya, now competing against Jev. Just a simple guy from a small village in Kerala just teaching generative AI to everyone through instagram!!! instagram.com/nandakishor_m/

for my academic friends - NVIDIA is hiring PhD interns across a range of roles spanning science, engineering, and physical AI. If you’re looking to work on hard problems at the edge of research and real world impact, this is the place to do it

介绍比Jev快50倍，在你设备上跑的laya-mlx! 只在你的设备上占用最高1G内存 Laya是一个开源的类似于Jev的,基于文本输出概率的分类系统 我将其移植到MLX,并且做了一些性能优化! 视频中就是这个模型在我的本地M3Max上玩贪吃蛇 这个模型能够以每秒决策60次的速度玩贪吃蛇！ github.com/mizorewww/laya-ml…

I am not religious at all, but I like the reply here very much all the same

Need support getting to #KubeCon + #CloudNativeCon North America (Nov 9-12)? Registration scholarships can help make Salt Lake City possible. 🎟️ Apply by October 4: bit.ly/4yvg6VX

help us out in CNCF by filling out a new survey on cloud native workload types, we will share the results at #kubecon #cloudnativecon in November! "2026 Cloud Native Workloads Survey" research.net/r/6G5WVBT

this post on the chinese internet by a deepseek kernel engineer explains software crafter's daily dread so perfectly

Frontier AI safety will require deep systems engineering and formal verification. We’re sharing our learnings openly for all to learn from nvidia.github.io/OpenShell-R…

Openness makes consequential claims testable. Without evidence, we cannot distinguish systemic risk from ordinary engineering failures used to justify sweeping regulation. Without evidence, AI safetyism looks like a self-appointed group claiming privileged knowledge to constrain everyone else. If companies lost control of an AI system, they should publish the relevant traces—with only necessary redactions—for independent scrutiny.

The Onion's 9/11 special issue was amazing. The staff had just moved to NYC and had a party to celebrate their new location on 9/10. Then on 9/11, they got up and went to work. I consider it one of the finest examples of journalism ever, satire site and all.

Sep 2026 ... 26 years in. Still having fun in #opensource 🥳 lists.apache.org/list?*@*:20…

BREAKING: OpenAI might have stolen another major proof. In a detailed Mastodon post, which I report in full in the comments, Andreas Thom presents several pieces of evidence suggesting that OpenAI may have trained Astra on conversations in which he and Gábor Kun were working on Gromov’s soficity conjecture, one of the ten problems OpenAI later announced Astra had solved. I know Andreas. We met several times early in our careers. He is an exceptional mathematician, a leading expert on sofic and hyperlinear groups, and one of the most respected scholars in the field. He has spent two decades working on this problem. If his account is correct, this is not a minor dispute over attribution. It would mean that unpublished human work was absorbed into a model and then presented to the world as a breakthrough by the model itself. And if the allegations raised by Levent Alpöge, Tristan Buckmaster, and now Andreas Thom are all substantiated, we are no longer looking at isolated incidents. We may be looking at one of the greatest intellectual scandals in the history of science. AI is not discovering new mathematics. AI is stealing human discovery.

Dang! they found out!!

Two heroes of today's Navier-Stokes story are not getting enough credit. Córdoba and Martínez-Zoroa came up with the crucial strategy. Others built on it and, with the help of AI, provided the computations that finished the problem. Thankfully @QuantaMagazine gets this right: