I committed the project I maintain to GitHub Actions when Actions first came out, and I'm really starting to regret it.
The main problem, which this article touches, is that GHA adds a whole new dimension of dependency treadmill. You now have a new set of upstreams that you have to keep up to date along with your actual deployment upstreams.
I caught it on the airplane a few days ago. I would have loved a little more technical depth, but I guess that's pretty much standard for a puff piece.
It is interesting that Hassabis has had the same goal for almost 20 years now. He has a decent chance of hitting it too.
If you're going to go through the effort of learning a new language, it makes sense to consider another language altogether, one without 30 years of accumulated cruft.
An advantage is that if you already know the older language then you don’t have to learn the new idioms up front to use it. You can take your time and still be productive. It isn’t why I would use it but it is a valid reason.
I have used many languages other than C++20 in production for the kind of software I write. I don’t have any legacy code to worry about and rarely use the standard library. The main thing that still makes it an excellent default choice, despite the fact that I dislike many things about the language, is that nothing else can match the combination of performance and expressiveness yet. Languages that can match the performance still require much more code, sometimes inelegant, to achieve an identical outcome. The metaprogramming ergonomics of C++20 are really good and allow you to avoid writing a lot of code, which is a major benefit.
Macros are simply a fact of life in any decent-sized C codebase. The Linux kernel has some good guidance to try to keep it from getting out of hand but it is just something you have to learn to deal with.
There's a big gap of knowledge between infosec researchers and ML security researchers. Anthropic has a bunch of column B but not enough column A.
This was discussed in some detail in the recently published Attacker Moves Second paper*. ML researchers like using Attack Success Rate (ASR) as a metric for model resistance to attack, while for infosec, any successful attack (ASR > 0) is considered significant. ML researchers generally use a static set of tests, while infosec researchers assume an adaptive, resourceful attacker.
ML researchers are not sec researchers. they need to stick to their own game.
companies need to use both camps for a good holistic view of the problem. ML is the blue team. sec researchers the red.
While I didn't disagree with his general politics, he is absolutely right that the US has largely pulled up the ladder behind them. The average age of a first time home buyer is now 40.
The American dream of having a home and a family is now out of reach for millions of Americans and politicians on both sides of the aisle.
> he is absolutely right that the US has largely pulled up the ladder behind them.
You blame "the US" and you agree with Thiel who blames "capitalism"? It starts to look like a broad-brush blame game... let's add the generational trolling to it too.
As if this whole show wasn't designed by Thiel and the rest of the lobby club.
Smart kids can be a distraction as well. It certainly would have benefitted me to enter G&T at Kindergarten instead of 3rd grade. Much of my first grade was spent separate from the other kids doing 5th grade workbooks.
It is depressing that I'll be almost 60 years old and still drilling Aho-Corasick.
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