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?

I’m unclear what has been gained here.

- Is the work easier to do? I feel like the work is harder.

- Is the work faster? It sounds like it’s not faster.

- Is the resulting code more reliable? This seems plausible given the extensive testing, but it’s unclear if that testing is actually making the code more reliable than human-written code, or simply ruling out bugs an LLM makes but a human would never make.

I feel like this does not look like a viable path forward. I’m not saying LLMs can’t be used for coding, but I suspect that either they will get better, to the point that this extensive harness is unnecessary, or they will not be commonly used in this way.

Don’t automation technologies improve the productivity of labor?

If I can make one widget per hour, and some new tool lets me make 10 widgets per hour?

Conventional economic theory suggests the gain will be split between the widget-maker and the widget-consumer, in proportions determined by the relative slopes of the supply-demand curves, but definitely the product will become somewhat cheaper.

I had some eye strain, chatGPT recommended a Lutein + Zeaxanthain supplement. It has worked great!

I actually don’t like python type hints!

At my work we have a jit compiler that requires type hints under some conditions.

Aside from that, I avoid them as much as possible. The reason is that they are not really a part of the language, they violate the spirit of the language, and in high-usage parts of code they quickly become a complete mess.

For example a common failure mode in my work’s codebase is that some function will take something that is indexable by ints. The type could be anything, it could be List, Tuple, Dict[int, Any], torch.Size, torch.Tensor, nn.Sequential, np.ndarray, or a huge host of custom types! And you better believe that every single admissible type will eventually be fed to this function. Sometimes people will try to keep up, annotating it with a Union of the (growing) list of admissible types, but eventually the list will become silly and the function will earn a # pyre-ignore annotation. This defeats the whole point of the pointless exercise.

So, if the jit compiler needs the annotation I am happy to provide it, but otherwise I will proactively not provide any, and I will sometimes even delete existing annotations when they are devolving into silliness.

What would your employer say if you said “I don’t own a smartphone. What alternatives exist?”

My current employer has a little nub on my laptop that I touch, but my previous employer was big on making me check my smartphone.

George Washington was dubbed “The American Cincinnatus”. Cincinnati was named in honor of George Washington being like Cincinnatus. That should tell you everything you need to know.

Coffee has longevity and health benefits that are not due to caffeine alone. It has so many antioxidants you can count it as a serving of vegetables.

I tried caffeine pills in my misguided youth. They feel different, and one time I forgot I had already taken it and took a second—the resulting heart palpitations were some seriously scary stuff.

There are illegal moves and there are illegal moves. There is trying to move your king five squares forward (which no amateur would ever do) and there is trying to move your King to a square controlled by an unseen piece, which can happen to somebody who is distracted or otherwise off their game.

Trying to castle through check is one that occasionally happens to me (I am rated 1800 on lichess).

I don’t know how to square this with the recent statement by Dario Amodei (Anthropic CEO) on the Lex Fridman podcast saying that in his opinion the scaling hypothesis still has plenty of room to run.

I’m not familiar with this—why would the rent be related to the amount of footfall?

Or, it will be amplified, and will become the basis of a religious-nationalist movement.

Additional context on why phenylephrine was ever approved to begin with—apparently it is effective if you use it as a spray, but apparently nobody bothered to check what happens when consumed orally, and it turns out your digestive system degrades it quickly and it doesn’t even make it into the bloodstream.

The insomnia effect is no joke! It’s an amphetamine.

I used to take 24-hour allergy medicine with pseudoephedrine, and it took me years to realize it was the thing that was giving me insomnia during allergy season—for years I thought I just had periodic bouts of intense insomnia.

(deleted because I was wrong)

Honest question, couldn’t Biden have just changed it, as president?

I agree, linear algebra or pseudocode.

Ok, well, I understand it may have been invented with that goal, but it frankly does not look like blackboard notation at all. This is not lower effort than your rebuttal “yes it does, in fact it was invented that way”.

I agree with a sibling comment, also heavily downvoted, that the real blackboard notation is linear algebra notation. Either that, or pseudocode. Python and Haskell look like pseudocode. This doesn’t, and it doesn’t matter what the developer was targeting, he didn’t hit the target.

> APL code can be directly mapped to algorithms or mathematical expressions on a blackboard and vice versa

After looking at the code, I find this claim questionable.