Most patches are non-trivial and then each project/maintainer has a preferred coding style, and they’re being inundated with PRs already, and don’t take kindly to slop.

LLMs can find the CVE fully zero interaction, so it scales trivially.

Related, a direct comparison to other sandboxes and what you offer over those would be nice

(This looks like a BI rehash of that topic)

Progress in AI can easily be measured by the speed at which the goalposts move - from “it can’t count” to “yeah but the entire browser it wrote didnt compile in the CI pipeline”

3 years ago LLMs couldn’t solve 7x8.

Now they’re building complex applications in one shot, solving previously unsolved math and science problems.

Heck, one company built a (prototype but functional) web browser

And you say it’s crazy that in the future it’ll be able to build a mail app or OS?

Could be. It could also end up freeing us from every commercial dependency we have. Write your own OS, your own mail app, design your own machinery to farm with.

It’s here, so I don’t know where you’re going with “I’m unhappy this is happening and someone should do something”

> Stop requiring computers/phones for everything.

Ah yes, that sounds straight forward. Let us know when you’ve deployed that to prod.

Thousands of people get scammed and have their lives ruined every year, so deprecating passwords is absolutely the right move

Historically it was the opposite; OpenAI was yolo and Gemini overly cautious to the point of severely limiting utility

Is this a requirement for most bug bounty programs? Particularly the “reliable” bit?

The other is: when will they charge? Does this ship not run at night?

There’s absolutely been a lot of focus on LLMs, but they simply work very well at a lot of things.

That said, Carbon (C++ successor) is an active experimental (open source) project. Fuchsia (operating system, also open) is shipping to consumer products today. Non-LLM AI research capabilities were delivered at a level I’m not sure is matched by any other frontier lab? Hardware (TPUs, opentitan, etc). Beam is mind-blowing and IMO such a sleeper that I can’t wait for people to try.

So whilst LLMs certainly take the limelight, Google is still working on new languages, operating systems, ground-up silicon etc. few (if any?) companies are doing that.

How familiar are you with the concept of the jagged frontier? That is, AI does indeed fail at things we might expect a third grader to be capable of. However, it is also absolutely exceptional at a lot of things. The trick is A) knowing which is which and B) being able to update yourself when new capabilities are unlocked

So yeah, it’s unsurprising you found a use case it couldn’t trivially do. But being able to one-shot quite complicated applications that may have taken a day to get right previously is an astonishingly useful thing, no?