[sudosteph]

Meanwhile my main use cases for AI outside of work:

- Learning how to solder

- Learning how to use a multimeter

- Learning to build basic circuits on breadboxes

- learning about solar panels, mppt, battery management system, and different variations of li-on batteries

- learning about LoRa band / meshtastic / how to build my own antenna

And every single one of these things I've learned I've also applied practically to experiment and learn more. I'm doing things with my brain that I couldn't do before, and it's great. When something doesn't work like I thought it would, AI helps me understand where I may have went wrong, I ask it a ton of questions, and I try again until I understand how it works and how to prove it.

You could say you can learn all of this from YouTube, but I can't stand watching videos. I have a massive textbook about electronics, but it doesn't help me break down different paths to what I actually want to do.

And to be blunt: I like making mistakes and breaking things to learn. That strategy works great for software (not in prod obviously...), but now I can do it reasonably effectively for cheap electronics too.

[nancyminusone]

As someone who does these things, I am curious to know how and why you would choose AI.

Working these from text seems to be the hardest way I could think to learn them. I've yet to encounter a written description as to what it feels like to solder, what a good/bad job actually looks like, etc. A well shot video is much better at showing you what you need to do (although finding one is getting more and more difficult)

[sudosteph]

I just process text information better. Videos are kind of overstimulating and often have unrelated content, and I hate having to rewind back to a part I need while I'm in the middle of something. With LLMs I can get a broad overview of what I'm doing, tell it what materials I already have on hand and get specific ideas for how to practice. Soldering is probably one of the harder ones to learn by text, but the description of the techniques to use were actually really understandable (use flux, be sure the tip is tinned, touch the pad with the tip to warm it up a little, touch again with the iron on one side of the pad and insert the solder in on the other side and it gets drawn in, pull away (timing was trial and error). And then I'd upload a picture of what I did for review and it would point out the ones that had issues and what likely went wrong to cause it (ex: solder sticking to the top of the iron and not the pad), and I would keep practicing and test that it worked and looked like what was described. It may not be the ideal technique or outcome, but it unblocked me relatively quick so I could continue my project.

Being able to ask it stupid questions and edge cases is also something I like with LLMs, like I would propose a design for something (ex: a usb battery pack w/ lifepo4 batts that could charge my phone and be charged by solar at the same time), it would say what it didn't like about my design, counter with its own, then I would try to change aspects of their design to see "what would happen if .." and it would explain why it chose a particular component or design choice and what my change would do and the trade-offs, risks, etc other paths to building it with that, etc. Those types of interactions are probably the best for me actually understanding things, helps me understand limitations and test my assumptions interactively.

[stripe_away]

and to be blunt, I learned similar things building analog synths, before the dawn of LLMs.

Like you, I don't like watching videos. However, the web also has text, the same text used to train the LLMs that you used.

> When something doesn't work like I thought it would, AI helps me understand where I may have went wrong, I ask it a ton of questions, and I try again until I understand how it works and how to prove it.

Likewise, but I would have to ask either the real world or written docs.

I'm glad you've found a way to learn with LLMs. Just remember that people have been learning without LLMs for a long time, and it is not at all clear that LLMs are a better way to learn than other methods.

[sudosteph]

The asking people part was the hard thing for me, always has been. That honestly was the missing piece for me. I absolutely agree that written docs and online content are sufficient for some people, that's how I learned Linux and sysadmin stuff, but I tried on and off to get into electronics for years that way and never got anywhere.

I think the problem was all of the getting started guides didn't really solve problems I cared about, they're just like "see, a light! isn't that neat?" and then I get bored and impatient and don't internalize anything. The textbooks had theory but so much of it I would forget most of it before I could use it and actually learn. Then when I tried to build something actually interesting to me, I didn't actually understand the fundamentals, it always fails, Google doesn't help me find out why because it could be a million things and no human in my life understands this stuff either, so I would just go back to software.

It could be LLMs are at least possibly better for certain people to learn certain things in certain situations.

[chaps]

  > However, the web also has text, the same text used to train the LLMs that you used.

The person you're responding to isn't denying that other people learn from those. But they're explicit that having the text isn't helpful either:

  > I have a massive textbook about electronics, but it doesn't help me break down different paths to what I actually want to do.

[defgeneric]

The physicality of having to actually do things in the real world slows things down to the rate at which our brains actually learn. The "vibe coding" loop is too fast to learn anything, and ends up teaching your brain to avoid the friction of learning.

[dns_snek]

Your use of LLMs is distinctly different than the use being described here (in a good way).

You might ask "What do I need to pay attention to when designing this type of electronic circuit", the people at risk of cognitive decline instead ask "design this electronic circuit for me".

I firmly believe that the the latter group will suffer observable cognitive decline over the span of a few years unless they continue to exercise their brain in the same ways they used to, and I think the majority won't bother to do that - why spend much effort when little effort do trick?

[aprilthird2021]

Cool, but most people will get brain rotted by this. It's the same way we constantly talk about how social media is probably bad for people then some commenter comes and says he's not addicted and there's no other way he could communicate with his high school friends who live overseas and know about their lives. Not everyone will only get the positives out of any technology

[amelius]

Yeah, if you're using LLMs like an apprentice who asks their master, then there's nothing wrong with that, imho.

[fxwin]

Same here. I've been working through some textbooks without solutions for the contained exercises, and ChatGPT has been invaluable for getting feedback on solutions and hints when I'm stuck

[kapone]

> - Learning how to solder - Learning how to use a multimeter - Learning to build basic circuits on breadboxes - learning about solar panels, mppt, battery management system, and different variations of li-on batteries - learning about LoRa band / meshtastic / how to build my own antenna

And yet...somehow...humans have been able to learn and do these things (and do them well) for ages, with no LLMs around (or the stupid amount of capital being burned at the LLM stake).

And I want to hit the next person with a broom or something, likely over and over again, who says LLMs = AI.

/facepalm.