Third-party cybersecurity evaluations. See, e.g., https://www.irregular.com/research/assessing-gpt-5.6-sol, which was published around the same time.
4,004 karma · joined July 6, 2016
The 0.16 release earlier this year introduced a much-heralded userland API (https://ziglang.org/documentation/master/std/#std.Io) that can be used to implement various asynchrony and concurrency patterns, including green threads, but it can't do stackless coroutines because support for those has to be baked into the compiler.
There is currently an open proposal to bring back stackless coroutines without dedicated syntax (instead offering low-level bring-your-own-buffer APIs for interacting with suspended coroutines), which could be combined with the aforementioned userland API to produce something more like how async/await works in other languages (https://github.com/ziglang/zig/issues/23446).
(The post primarily emphasizes self-referentiality rather than analogy, but I suspect similar things could be said about analogy.)
If you're saying that the question of whether they actually have a highly capable model is less important than the question of whether there's a plagiarism scandal, I continue to disagree.
In my view, Gwern makes a compelling counterargument: Xanadu was a fundamentally bad idea. The parts of it that weren't incorporated into the World Wide Web either solved problems no one actually had, or couldn't have constituted a stable equilibrium between users and publishers (i.e., even if it'd been magically willed into existence, it'd have quickly fallen apart). https://gwern.net/xanadu
I'm open to the idea of different norms for citing AI detectors, but someone needs to propose what they should be and they need to make sense.
This confused the heck out of me because it makes it sound like the STT model can make function calls in order to execute arbitrary tasks, which wouldn't make any sense. The developer docs (https://ai.google.dev/gemini-api/docs/models/gemini-3.5-tran...) confirm that the Gemini 3.5 Transcribe model cannot in fact make function calls. I guess the blog post is just using very confusing wording to describe how their consumer assistant/chatbot app can both take audio input via Gemini 3.5 Transcribe and then call other things as needed. Or maybe that bullet point was meant to be for a different model announcement and somebody made an editing error.
I find it amusing that even the AI skeptic articles are written with AI these days.
This article is mostly making a different argument (though it contradicts itself in some places), which is that even if the underlying technology does work, and is ultimately going to create quadrillions of dollars of value and transform society, if it takes more than another 1–2 years for that to happen, then there'll still be a crash, because that's when the data center construction bills come due and the labs (especially OpenAI) don't yet have the money to pay them.
It argues primarily against a hypothetical optimist who believes that everything is fine because the cash flow numbers currently work out, on the grounds that this hypothetical optimist hasn't realized that the labs' recurring expenses are scheduled to spike in 1–2 years when the data centers come online and the labs have to start paying for them. It also spends a lot of words comparing the situation to the 2008 financial crisis, because that's everyone's favorite morality tale.
I am not sure that anyone is actually making this mistake (i.e., trying to predict the future by looking at labs' present cash flows). The better counterargument is what Matt Levine used to call "Netflix Theory": if the large capital investors who own stakes in the labs still believe in their valuations (which they should, if the technology works and the quadrillions are coming, which we're assuming here for the sake of argument), then they will be very highly motivated not to let their investment be seized by the labs' creditors. So the labs will not have too much difficulty raising or borrowing enough money to pay the bills.