AI is getting cheaper more quickly than any other transformative tech in history. At a given level of performance, cost has fallen ~47%/quarter since 2023. That’s 4× faster than DNA sequencing, 6× faster than compute, 18× faster than lithium batteries, and (up to 1973) 54× faster than electricity.

I did this last year, that's not the future. Web's way nicer.

Maybe this is the platform Zuck has always been after…

On July 25, we hacked OpenAI. Two bugs let us take over ChatGPT/Codex accounts of OpenAI employees (+some unaffiliated users) and reach connected services: Outlook, Slack, GitHub, etc. We proved it with a PR in OpenAI’s internal codebase . It took us <72h. 🧵

my days are like `N` hours of working with frontier models, babysitting them in frustration and disbelief at the frequent errors and slop interrupted by `M` min breaks of browsing X takes about how the same models (and _especially_ the next gen!) are superhuman at ~everything

Good idea!

This is right. These issues are not going to be limited to Mathematics. “…indicate issues that all of humanity might face: how to make sure that, as AI changes the way work is done, we do not lose sight of what that work was meant to achieve in the first place.”

This isn't the most notable aspect of today's news, but on the user data issue, there are different kinds of *training on user data* with very different privacy/IP implications. Sadly, AI cos don't like to disclose what they're doing. - pretrain on user data, with users' tokens as prediction targets: high regurgitation risk, improper - use user prompts to distill large models into small ones: low regurg. risk, some companies probably do this - use user traces to construct RL tasks: low regurg. risk, because RL has low memorization abilities, but can extract customer IP, depending on how it's done. Ranges from benign "use explicit user feedback in reward model training" to invasive "upload user's coding environment and commit history to turn into rl envs" "De-identification" is weak -- you can identify someone with a small number of bits, and long traces have more than enough. And it doesn't affect IP leakage concerns.

This model represents a step-function improvement on many benchmarks, and its training is ongoing. Our internal model group arrived at the Navier–Stokes solution in 88 hours, using around 10,000 coordinating AI agents. Throughout the effort, we maintained the strict safeguards—including monitoring and isolation—that we apply to all our frontier evaluations.

my first interaction with gpt-6 astra. what a charmer lmao

To prevent models from going rouge, just make the neoclouds go green. Or threaten to blacklist them with a yellow card or a pink slip. Preventing them to go rogue is another story, probably involving guardrails.

One of the most important things to know about this AI cycle is that no one knows what they're talking and even very smart and plugged in people are continually reversing their opinions and then re-reversing them three months later.

Current status, thanks to Kiddo

It’s amazing how quickly we have gone from “bounded by human performance” to “superhuman” to completely “unbounded”.

i really don't want to use your agent, i want to use my agent to use your thing.

Matrix multiplication is the basic computational operation that powers modern computing (including AI). Yet, the theoretical fastest speed at which computers can multiply matrices (omega ω) is still unknown and has been a longstanding challenge for complexity theory and computer science. Today, we announce a new record for omega (ω<2.371177). This is the result of a great team effort between @GoogleDeepMind, our academic collaborators, and our Gemini-powered coding agent AlphaEvolve! 🧮 arxiv.org/abs/2608.16884v1

Incredible watering down -- the Singularity is now redefined to mean "the rate of new firm creation has increased somewhat" Vernor Vinge described the Singularity as an event horizon past which everything (e.g. what happens tomorrow) becomes entirely unimaginable and unpredictable to human understanding -- it would feature mind upload, cybernetic merging, centuries of tech progress happening in mere minutes... and humans becoming entirely irrelevant.

Good moment today to remind everyone to stay frosty with AI. I was working on making a server stoppable via the CLI, and Codex decided the best path forward was to implement an unauthenticated network API to every server to shut itself down. Excellent work. I responded with "I don't know about that." (I usually give more direct feedback but this was so absurd) and it thought for like 20 seconds and responded "Server stopping should not be part of an unauthenticated network API." Yes. lol. By the way, the result I was looking for was that we automatically start a locally discovery Unix-socket bound server so I wanted it to discover that (using prior mechanisms already made) and gracefully stop that. The driver is absolutely accountable here (me). My lazy prompting led AI to think I wanted to be able to stop ANY configured server I was talking to. Shame on me for thinking it was obvious here. But, I also reviewed it and found this idiocy, so, that's where good AI drivers come in. Also me.

Looks like Grok @bot doesn't have access to X. That's a bit odd.. Btw, having quick root access to the agent's VM/sandbox is really nice. Looks like all agents share a single VM. In contrast, Claude's cloud sessions have a separate per-session container.

That's a small reminder! 👇 As of June 2026, HTTP has a new method - a GET with a `body` 😎 Meet QUERY (RFC 10008). It lets you send complex queries in the body (like POST) while staying safe, idempotent, and cacheable (like GET). Already works on servers (Node.js, Go, Laravel…). Browsers are still adding full support, usable now with care, with widespread adoption coming later in 2026+.