dreis_sw

I found a big problem with this - I noticed that the longest answer is very often the correct one, which kinda ruined the game. Even though I didn't want it to, it started affecting my decision-making. Luckily, I only noticed this around question 85, though those are really the tricky ones.

Good news for the project is that I think you can easily tweak the LLM to generate better alternatives.

I got 89/100, which extrapolates to 72,700. As a non-native speaker, I'm quite happy with that.

It's well known that companies with an abundance of raw technical skills but poor judgement tend to fail. On the technical side technical debt accumulates, while on the business side the wrong choices are made. I think it's valid to generalize this to AI.

I think the new high effort settings are so strong that selecting them when the task doesn't require it actually impacts the output negatively.

Seems like this model delivers on what has already been scaling quite nicely, which is the length and complexity of the requested tasks, but isn't such a big improvement on what hasn't been scaling so far - common sense, discernment, good judgement.

They are certainly critically flawed at the moment, but I still feel that with proper traceability, KYC, etc. it would be a much fairer system than the current betting companies. It’s one of those use-cases where blockchain technology actually makes sense.

Wonder if that's also the case for web-based UI like Spotify, or if the accessibility APIs are only useful for native applications.

History shows continuous evolution, there won't be a "final AGI thing". The definition of AGI is so vague anyways that any conversation around it is hardly useful. 5 years ago, what we have today would have been considered AGI.

If the economy wasn't completely broken you'd have a job right now.

It also took many years to put capable computers in the hands of the general public, but it eventually happened. I believe the same will happen here, we're just in the Mainframe era of AI.

We'll only know for sure when either of these companies goes public. Google serves inference and Google Cloud is profitable but we don't know how much inference is costing.

If they never go public, there's our answer as well.

Works even better if you have a good test suite, which is surely the case here with Ladybird

Happy to hear that it's working out well for you, but there is always a cost. The less common successful remote work becomes across the industry, the more companies like yours stand out. And remote work goes back to being a premium, highly competitive perk, like it used to be in the past.

And I agree that remote work is perfectly possible with a good culture and responsible employees, but most companies don't really have the culture or hiring practices that optimize for that.

(2) At the office, it's harder to pretend that work took longer than it actually took. If you're done with the design doc in 2h, with colleagues sitting all around you, what can you do to pretend that it took you longer? Mess around with Confluence, pretending to work? You might as well move on to the next design doc, or find something useful to do meanwhile.

At home, you can just pick up the Xbox controller and say it took you 4 hours.

I like the comfort of WFH, and there are plenty of people (myself included) that are responsible enough to handle it, but the problem is that the average person isn't. And we all pay for it.

I agree with your sentiment, this incremental evolution is getting difficult to feel when working with code, especially with large enterprise codebases. I would say that for the vast majority of tasks there is a much bigger gap on tooling than on foundational model capability.

So the watermark is being added to the image on the client-side? That's pretty bad

How do you break the window glass, how do you get into the display cases, how and when do you do it so that you're not stopped by the security, how do you carry the items away, how do you get away from the crime scene without being caught... And I'm sure I am forgetting other details. So I can see how it would take some work to make everything look so simple.

I recommend using GitHub's registry, ghcr.io, with GitHub Actions.

I invested just 20 minutes to setup a .yaml workflow that builds and pushes an image to my private registry on ghcr.io, and 5 minutes to allow my server to pull images from it.

It's a very practical setup.

Interesting, and completely agree with both your remarks, but how does it relate to disabling JavaScript? What are you getting out of it, other than making the web less usable for yourself?

Luckily there’s an easy fix, enabling JavaScript like a regular human being :p Honestly curious though, do you generally browse the web without JavaScript?

I had the same experience. It’s clearly very limited intellectually.