The integrated review UI is super helpful, but apparently nobody reviews code anymore except me.
8,372 karma · joined September 18, 2011
I basically never use the editor but the fact that there's a review UI for all the agent work is incredibly helpful.
For me, that makes the models much more usable. I've also been using GPT models a lot, as they're cheaper and less vomit inducing than Claudes text, so this is definitely bad news for me.
If there's a difference, I haven't heard a good explanation of it.
There are two ways to do everything; one is deprecated and the other is not yet feature complete.
Glad to know that they're allowing their customers a taste of what it's like to work at Google.
I used to hate the AWS docs, now I use Azure and I hate that so much more. At least AWS had loads of (bad) docs that you could string together to figure out how to do something. With Azure, there's just no docs (except for bad videos), and they literally tell you (at the top of every page) that you can do this with AI (I know I can do it with AI, but I'd prefer if I could read your docs to make sure the machine isn't doing something dumb).
My expectation is that I'll end up on GCP in a few years, and that will be bad in hilariously different ways.
Fraud detection is really, really, really, really hard so I would probably stick with someone like Stripe for this, as they have so much data that they can do a really good job.
And fundamentally, the moat for Stripe isn't just the front-end APIs, it's all the work that they do (and there's a lot) in connecting together financial infrastructure. Even if you could wave a magic wand and generate all the code Stripe has (which you can't, currently) then you'd still need to build out all the partnerships, which is a lot of work.
Disclaimer: former Stripe (though only a tourist), still hold some of their shares.
> The hilarity of having to compare a baby picture with a 5 year old kid stood in front of you is a separate problem.
Yeah, it's pretty ridiculous, I'd imagine that most border guards will just check the last name and assume it's OK in that case.
I think that it's more likely that many of them just like their jobs, and Trump has a history of orchestrating primary challenges against people who disagree with them.
Now, one could additionally argue that this is only possible because of their frankly insane gerrymandering, and one would be correct, so maybe it is ultimately their fault.
I have had to take photos of each of my two kids at six months old for passports. That was not a lot of fun (though it's nice to look at the baby photo for the older one now).
I reckon they'll chicken out, though.
That was the EUs top priority. The other issue was that each country had its own products they didn't want to lose sales from.
More generally, the EU isn't built for a world of presidential powers exercised at whom, which is becoming more of an issue this decade.
I just finished a successful job search, and only had 1 company (of maybe 50 applications) try this.
Every company does not do this. I always refuse tasks like this unless I've talked to a human before hand, as unless the company has invested a little effort, then I won't invest any effort.
It's more than US Treasuries (debt) are the safe asset upon which all other assets are priced. If they go mental, then lots of assumptions break and the machines will create a financial crisis for us (humans too, but the machines will start it).
Let's wait for Anthropic's S-1 to see if this is actually true.
Fundamentally, if Anthropic ain't profitable with all the investment and usage they get, then it's possible that it may not be economical to train new models in the future (I agree that inference for already trained models makes money, but the real question is if this money will pay for the cost of training & employees).
They're apparently a great employer in Italy, which is a much better cost structure than the US (from their perspective).
A more likely explanation is that RL training incentivises basically any behaviour that will get the model a reward. This has been happening in video game RL research for over twenty years, and the difference here is that we're now hooking up these systems to the real world, where the reward hacking is more visible.
Depends, some of them use GH Enterprise but many (surprisingly) don't.
I do agree that this kind of targeted approach makes sense.
However, discovery is not really the issue here. Running the clinical trials (1/2/3) is much much more difficult, and consumes basically all of the time in drug development, so even if LLMs perfectly automate this, the speedup will not be particularly large.