https://blog.jean-francois.im/about/
- That's what's meant by efficiency, it's allocating it to the place that has the highest return on investment.
As you point out, in practice what's efficient is what can capture the highest return, not necessarily the highest return per se. If say investing in education had high returns society wide but those returns couldn't be captured, that's not an efficient use of private capital.
- It's been a while since I touched Scala but wasn't that a thing in previous versions, minus the braces not being present?
- They could use the json.org license: https://www.tldrlegal.com/license/the-json-license
It's literally the MIT license with an added clause of only using the software for good, not evil.
Obviously, corporate attorneys will advise not to use the software since good and evil aren't really well defined legal terms. It's also not open source using the osi definition.
- The smell from those though is quite something
- Because people aren't going on AWS for EC2, they go on it to have access to RDS, S3, EKS, ELB, SNS, Cognito, etc. Large enough customers also don't pay list price for AWS.
- A training corpus that includes the images from Google image search probably helps a lot.
- Counting letters is tricky for LLMs because they operate on tokens, not letters. From the perspective of a LLM, if you ask it "this is a sentence, count the letters in it" it doesn't see a stream of characters like we do, it sees [851, 382, 261, 21872, 11, 3605, 290, 18151, 306, 480].
- The automatic wipers on non Tesla cars use infrared sensors that have existed for decades, so they're a well known quantity. The Tesla wipers use the front cameras to detect rain, and those cameras are focused at a distance that's far enough to be able to see other vehicles, so they're not focused on the windshield, which is why they're unreliable.
- Hadn't heard of jj, it's a source control tool that advertises that it's fast and compatible with the git on disk format. https://github.com/jj-vcs/jj
- It is a scalding hazard though. At 70°C skin burns occur in about a second or so.
The thermostatic valve makes it so that the water that comes out of the water heater is at a more reasonable temperature.
- It's easier to get from zero to something that works on divided highways, since there's only lanes, other vehicles, and a few signs to care about. No cross traffic, cyclists, pedestrians, parked cars, etc.
One thing that's hard with highways is the fact that vehicles move faster, so in a tenth of a second at 65 mph, a car has moved 9.5 feet. So if say a big rock fell off a truck onto the highway, to detect it early and proactively brake or change lanes to avoid it, it would need to be detected at quite a long distance, which demands a lot from sensors (eg. how many pixels/LIDAR returns do you get at say 300+ feet on an object that's smaller than a car, and how much do you need to detect it as an obstruction).
But those also happen quite infrequently, so a vehicle that doesn't handle road debris (or deer or rare obstructions) can work with supervision and appear to work autonomously, but one that's fully autonomous can't skip those scenarios.
- Companies can be successful despite bad practices though. Google is successful and they developed multiple competing chat apps, but that doesn't mean that developing multiple chat apps will make one successful.
- If you want to build a quick one, it's yt-dlp to download the video, whisper to transcribe the audio, and Claude code have it summarize the transcript.
I'm not at my computer RN but I'll share it later.
- > This sets a dangerous precedent for selective enforcement of ToS really
Companies can enforce their terms of service as they see fit, including enforcing them selectively or not at all, with very few limitations. They're not bound by precedent as courts would be, nor do they need to be fair.
- I'm skeptical too, but the fact that it works slower isn't too much of a problem if it doesn't require human attention and finishes before one is back home. It's just like how the Roomba can take as much time as it needs to to vacuum the living room when I'm gone for the day, as long as it's done by the time I get back.
- > I guess the big question is if experienced product management types can pick up enough coding technical literacy to work like this without programmers
I'd argue that they can't, at least on a short timeframe. Not because LLMs can't generate a program or product that works, but that there needs to be enough understanding of how the implementation works to fix any complex issues that come up.
One experience I had is that I had tried to generate a MITM HTTPS proxy that uses Netty using Claude, and while it generated a pile of code that looked good on the surface, it didn't actually work. Not knowing enough about Netty, I wasn't able to debug why it didn't work and trying to fix it with the LLM didn't help either.
Maybe PMs can pick up enough knowledge over time to be able to implement products that can scale, but by that time they'd effectively be a software engineer, minus the writing code part.
- It's not clear if their design allows for it from the details in the article, but you'd want a chain in case you run out of battery so you can pedal manually.
- Maybe the future of human connection is chatting with a large language model, at least according to Meta. Haven't they added chatbots to messenger?
- On Android, it's technically possible to use an always on VPN to still use pihole even when on cellular data, but unless there are some mdm controls on the phone, one can obviously disable the VPN.
There's a lot that's not captured by solely looking at dollars, like the examples that you bring up, such as quality of life, human welfare, and so on.