For the microseconds-chasers, there's microwave relay links, say between Chicago and New York (ref e.g. https://bullseye.ac/blog/economics/inside-the-world-of-high-...). Sending a signal up a few hundred km and down again a few hundred km adds way too much latency, and signal-hopping between fast-moving satellites adds way too much jitter for "such applications".
wow, that's weird. One would think that updating the reference table is something a team or individual - who just spent a lot of time and effort on implementing a feature - would also do.
For a while now cppreference.com has been in "temporary read-only mode" in which it isn't updated. Eventually I expect a "temporary" replacement will dominate and eventually it won't be "temporary" after all. Remember when some of Britain's North American colonies announced they were declaring independence? Yeah me either, but at the time I expect some people figured hey, we send a bunch of troops, burn down some stuff, by Xmas we'll have our colonies back.
Getting music on an ipod was always a pain unless you bought the music on itunes or ripped a music CD directly with itunes (yes, that was an actual feature. hard to imagine these days).
No simple drag and drop onto a mounted USB drive like all other mp3 players back in the day. Maybe more of a lock-in attempt instead of lock down, but related imo.
> ripped a music CD directly with itunes (yes, that was an actual feature. hard to imagine these days).
These days? Last week (though WMP). My retired father's old computer died, his new one, no CD slot. Emails me from Australia asking how to rip his CDs for his media player. He's not an audiophile but he's not a technophile (and his blues music collection is sufficiently large that at least one of the blues radio stations in his city will on occasion ask him to borrow something because they don't have it in their library.
Told him to get a USB CD player and a card reader (his media player is on micro/SD).
You can still rip CDs with Apple Music. In fact, that's the only use I have for that app (I recently lost a hard drive with music and I'm in the process of backing up all my CDs again).
That's a pretty excellent take, IMO. Just an undirected AI model doesn't do much, especially when the core team has time with the code, domain expertise, _and_ Claude.
As a specific example: The generated diagram showing the expression tree under "build in python" is simply wrong. It doesn't correspond to the expression x * 2 + 1, which should have only 1 child node on the right. The "GIL Released - Released" is just confusing. The dataflow omits the fact that the results end up back in python - there should be a return arrow. etc., etc.
If you use diagrams like this, at least ensure they are accurately conveying the right understanding.
And in general, listen to the person I'm responding to -- be really deliberate with your graphics or omit. Most AI-generated diagrams are crap.
> Also your saxpy example seems to be daxpy. s and d are short for single or double precision.
That's a great catch — attention to detail like that is what separates a kernel engineer from a *numerical computing expert*. You were right, "S" and "D" in BLAS naming refer to single and double precision respectively — so that was DAXPY, not SAXPY. Let me rewrite the kernel with the proper type...
Tried one of those MacBooks Neos in a store a few days ago because I got curious.
As a Linux/windows user I was completely baffled that you actually have to click (at least in the default setting) to make a mouse click instead of just giving it a tap. Does anyone prefer that?
Never did. I remember someone replied to my comment here that Google isn’t paying a penny to JetBrains. They’re quite happy with the relationship primarily because they don’t have to pay anything. If anything, JetBrains is the one who needs Google more than the other way around.
I feel like it's pretty easy to predict what OpenAI is trying to do. They want their codex agent integrated directly into the most popular, foundational tooling for one of the world's most used and most influential programming languages. And, vice versa, they probably want to be able to ensure that tooling remains well-maintained so it stays on top and continues to integrate well with their agent. They want codex to become the "default" coding agent by making it the one integrated into popular open source software.
I think this is more about `ruff` than `uv`. Linting is all about parsing the code into something machines can analyze, which to me feels like something that could potentially be useful for AI in a similar way to JetBrains writing their own language parsers to make "find and replace" work sanely and what not.
I'm sort of wondering if they're going to try to make a coding LLM that operates on an AST rather than text, and need software/expertise to manage the text->AST->text pipeline in a way that preserves the structure of your files/text.
The parser is not the hard part. The hard part is doing something useful with the parse trees. They even chose "oh is that all?" and a picture of a piece of cake as the teaser image for my Strange Loop talk on this subject!
Writing a literal parser isn’t too hard (and there’s presumably an existing one in the source code for the language).
Writing something that understands all the methods that come in a Django model goes way beyond parsing the code, and is a genuine struggle in language where you can’t execute the code without worrying about side effects like Python.
Ty should give them a base for that where the model is able to see things that aren’t literally in the code and aren’t in the training data (eg an internal version of something like SQLAlchemy).
Static analysis just requires that you don't actually execute the code. It's possible (sometimes) to infer what methods/properties would be create without actually statically analyzing the code.
E.g. mypy has a plugin to read the methods and return types of SQLAlchemy records, I believe without actually executing them.
Obviously not globally true, but in limited domains/scenarios you can see what would exist without actually executing the code.
This just seems like panic M&A. They know they aren’t on track to ever meet their obligations to investors but they can’t actually find a way to move towards profitability. Hence going back to the VC well of gambling obscene amounts of money hoping for a 10x return… somehow
The dev market? Anthropic's services are arguably more popular among a certain developer demographic.
I guess this move might end up in a situation where the uv team comes up with some new agent-first tooling, which works best or only with OAI services.
OpenAI could vibe-code marketshare by introducing bias into ChatGPT's responses and recommendations. "– how to do x in Python? – Start by installing OpenAI-UV first..."
This. It's valuable b/c if you have many thousands of python devs using astral tooling all day, and it tightly integrates with subscription based openai products...likelihood of openai product usage increases. Same idea with the anthropic bun deal. Remains to be seen what those integrations are and if it translates to more subs, but that's the current thesis. Buy user base -> cram our ai tool into the workflow of that user base.
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