A small diff /= a small change! They are completely separate things. Quite often a small diff is hours of actual work. Even in this case _finding_ those lines could have taken work - we don't really know.
We're a Haskell shop, so I usually just say "review the current commit. You're an experienced Haskell programmer and you value readable and obvious code" (because that it is indeed what we value on the team). I'll often ask it to explicitly consider testing, too
I recently started using LLMs to review my code before asking for a more formal review from colleagues. It's actually been surprisingly useful - why waste my colleagues time with small obvious things? But it's also gone much further than that sometimes with deeper reviews points. Even when I don't agree with them it's great having that little bit more food for thought - if anything it helps seed the review
I write Haskell with Claude Code and it's got remarkably good recently. We have some code at work that uses STM to have what is essentially a mutable state machine. I needed to split a state transition apart, and it did an admirable job. I had to intervene once or twice when it was going down a valid, but undesirable approach. This almost one shot performance was already a productivity boost, but didn't quite build. What I find most impressive now is the "fix" here is to literally have Claude run the build and see the errors. While GHC errors are verbose and not always the best it got everything building in a few more iterations. When it later got a test failure, I suggested we add a bit more logging - so it logged all state transitions, and spotted the unexpected transition and got the test passing. We really are a LONG way away from 3.5 performance.
This keeps getting parroted but it's flawed/overly idealistic/frankly naive. An awful of children are, unfortunately, poorly parented. This is not a new phenomenon, nor something we seem to be improving. OTOH, exposure to extreme material for young children is increasing, and has consequences beyond that child. Exposure to extreme pornography leads to a warped view of sex which affects everyone this child might have sexual encounters with. Exposure to extreme violent material leads to the murder of other innocent children.
I don't know where I stand on this legislation - my gut is that it's too heavy handed and will miss the mark. But I think we need to stop saying this falls solely on parents. The internet is far too big, and parenting is far too varied for this to work. I wish it would, but it won't. There simply aren't enough parents that care enough.
Because we know the implications of poor quality food, and we also know those who would buy it have no choice but to buy the cheapest. So, no thanks. I'd much rather the state intervene here and keep this crap out. This "let consumers choose" argument is tiring when consumers don't have the ability to choose. They are just trying to survive
Honestly there's way more there, and you get consistent solid speeds. Find a provider with a lot of retention and you can find almost all mainstream media regardless of it's age. (Public) torrents tend to track what's popular and quickly fade. The masses seem to favour low size encodes too, so if you're looking for more quality (and again, public trackers) you're usually much more out of luck.
Surely a pinch of critical thinking answers this? 4 deliveries a day isn't going to pay a daily minimum wage. If it did, then we wouldn't have this situation - surely most riders manage more than one delivery every 2 hours and make more than the minimum wage!
Sleep isn't the metric to track here, there are much better things to analyze such as HRV. For reducing drinking you shouldn't be doing that because of your sleep, you should be doing it because of your overall health. If you care about future health, take blood tests, weigh yourself, evaluate your physical fitness.
For those who won't bother to RTFA: the trains run cooler than other trains, so they are taking advantage of the difference such that the net result is the same temperature in tunnels, but the interior of trains can be cooler.
As I understand it, the point is that these models while they are _trained_ on identifying cats or cars, because they have soon so much variation during training have internalised very different concepts to help come up with "its a cat". The idea then is to take all of these pre-trained weights that let you build this classifier, but then add your own custom head on the front of this network. This saves you doing a huge amount of training for what is essentially feature extraction - that part is already done. All you need to do is just add a bit more training that works out how to use these learnt features. I could be way off the mark, but that's how I understand it.