Dr_Birdbrain

I was recently part of “AI layoffs” and had to do an interview circuit. All my interviews asked these, as well as efficient inference topics from How To Scale Your Model.

I don’t think you can rely on them for proactive protection. Most likely it will be reactive. If something bad happens and it wasn’t disclosed in the IPO, they will sue Anthropic after money has been lost. There would be damages but might not cover the full amount of the loss.

They’re amazing for interview prep! ;)

Thanks!

Sorry for being dense—does this include a tiny LLM to power the agent? Or is it just a wrapper that needs to be connected to the internet?

For Reddit, you can select an option so that it only shows you things from subs you follow. Dramatically improves the experience!

How do you use it to remember names?

I don’t work at a dating company, but I do work in machine learning applications.

My best guess is this: they are not optimizing for good vs great matches, and they are probably not even building a model of what that would even mean, not even trying to represent the concept in their algorithms.

Most likely they are optimizing for one or more metrics that are easy to measure and hence optimize, and these metrics have the side effect of producing an excitement for the user without actually pairing them up.

Example metrics: - time spent on the site

- times they “swipe right” or whatever

- messages sent

- money spent

I think this problem existed before AI. At least in my current job, there is constant, unrelenting demand for fast results. “Multi-day deep thinking” sounds like an outrageous luxury, at least in my current job.

My feeling is that AI-generated code is disposable code.

It’s great if you can quickly stand up a tool that scratches an itch for you, but there is minimal value in it for other people, and it probably doesn’t make sense to share it in a repo.

Other people could just quickly vibe-code something of equal quality.

Maybe all the engineers, but not the executives who created this problem to begin with

Would love to read about the impact on SE Asia that continue until today. Do you have a recommended resource?