amelius

Is that harness connected to a human?

> LLMs basically never shower, do the washing up, kick their foot in the dirt while sitting on a park bench with a coffee: the domain of the default mode network. And they never sit frustrated looking at things, guided by their long experience, with the itchy brain feeling that there is a solution before they can even say the words.

I'm sure the training data of LLMs contains a lot of those things, though.

For all intents and purposes, yes.

(as it would apply to a human software engineer also)

We just need new Software Engineering books that explain how to build software in the AI age.

AI doesn't "lack" it, it just may have less of it, and the gap is closing. Like it or not.

But the precision is in the 0-60 second range only ...

The main problem is that once training is complete, you only need inference which needs far less compute.

I like this, but I want a timer with at least 3 timers in it, memory options. I have a digital one from AliExpress, which is quite OK, except the alarm sound is too faint and the memory button UX is awkward.

Will this work as a shared library? I.e., the hundreds of megabytes will be shared between different applications? If not, maybe running on a browser is still the better option?

What would your ultimate prank time capsule look like?

At that point: why do you even need to leave the house? You can use VR goggles for everything.

If the DRAM scarcity continues, not much.

AI, however ...

At that point you might as well ask the AI for advice, no discussion necessary.

"You’d track how many hours or weeks you spent on a project, put together an invoice, email it to the client, and close it out when they paid."

But you can more easily do that with AI nowadays. The AI can even figure out what you're working on, and when.

I stopped using C++ around the time when Boost libraries were a thing. It was fun to think a bit of how to do metaprogramming, but it quickly became apparent that this was not the right way to do things.

> And you make an informed choice of which framework you choose based on that.

Experience shows that choices made in the beginning of a project are very often reconsidered later when requirements change. In those cases it is nice if you choose for the worst possible outcome, so in this case you choose for a high performance GUI framework which can scale.

Obviously, today you can just write "please rewrite this badly scaling app with that scaling GUI framework" but I think that's outside the scope of the discussion.

In GUI style code you often use closures which have circular dependencies. E.g. button points to the closure (for its event handler), closure points back to the button (e.g. change color of the button upon press).

Obviously you can do this differently, but it makes everything less ergonomic for the programmer.

And what did you think about the actual piece?

The "who cares if it doesn't scale" attitude sucks if your users suddenly pass the threshold for whatever reason.

Nerf means something else in deep learning parlance.

> It is very frustrating.

Not just frustrating, it can also be dangerous. What if you trust Claude with certain security-sensitive things (because experience), and suddenly you cannot trust it anymore like that?

> Having dealt with many family members just like this, I can tell you they certainly can use Google for search, they just don't want to. When forced to they use it fine.

Exactly! I noticed this when I moved out of my parents' house, when suddenly my mom became an electronics whiz who can hook up VCRs and TVs just fine. I always thought I was the smart person in the house, but now I realize I was just taken advantage of.

Yes, see:

https://news.ycombinator.com/item?id=50406927

For an example. Lots of people are now vibe coding their tools.

Does this also work when the search space becomes large?

I fear this might lead to an exponential blowup.

(The examples shown are all tiny)

> Barclays is moving in the other direction

Just fyi.

Meh, with compression you can often reconstruct the signal with far fewer samples.

Let's not use analogies from the distant past, they will only hold us back.

Yes, but a lot of experience is required in robotics to reach that stage.

Maybe the insight is that it is better to first sell the robots (the "shovels") and only later go into the gold business yourself (if ever).

But is a low-margin business really the one where you want to bootstrap your robotics industry?

Being in the EV business means having to compete with China. This market is dictated by manufacturing costs and so it is not where you want to be.