141–150 of 589 posts
Writing long texts for school is stupid and it is a skill that is in practice purely developed in order to do homework. I am not surprised it immediately declines as soon as the necessity is removed.
An Asimov fan saying writing long texts is stupid? I bet he would have some strong feelings against that
Earlier quoted context omitted.
I feel like saying papers pre peer review should be taken with a grain of salt should be stopped. Peer review is not some idealistic scientific endeavour it often leads to bullshit comments, slows down release, is free work for companies that have massive profit margins, etc. From my experience publishing 30+ papers I have received as many bad or useless comments as I have good ones. We should at least default to ope…
Please no. Remember that room temperature superconductor nonsense that went on for way too long? Let's please collectively try to avoid that..
The only advantage to closed peer review is it saves slight scientific embarrassment. However, this is a natural part of taking risks ofc and risky science is great.
P.s. in this case I really don't like the paper or methods. However, open peer review is good for science.
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 t…
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.…
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.
Earlier quoted context omitted.
I feel like saying papers pre peer review should be taken with a grain of salt should be stopped. Peer review is not some idealistic scientific endeavour it often leads to bullshit comments, slows down release, is free work for companies that have massive profit margins, etc. From my experience publishing 30+ papers I have received as many bad or useless comments as I have good ones. We should at least default to ope…
Please no. Remember that room temperature superconductor nonsense that went on for way too long? Let's please collectively try to avoid that..
Using LLMs to do replace the effort we would've otherwise endured to complete a task short-circuits that exercising function, and I would suggest is potentially addictive because it's a near-instant reward for little work.
It would be interesting to see a longitudinal study on the affect of LLMs, collective attention spans, and academic scores where testing is conducted on pen and paper.
Earlier quoted context omitted.
After working with claude code for a few months, I am not worried.
What does that mean? If you're still paying for a Claude Code, you are supposedly getting increased productivity, right? Or otherwise, why are you still using it?
But for it to be useful, you have to already know what you're doing. You need to tell it where to look. Review what it does carefully. Also, sometimes I find particular hairy bits of code need to be written completely by hand, so I can fully internalise the problem. Only once I've internalised hard parts of codebase can I effectively guide CC. Plus there's so many other things in my day-to-day where next token predictors are just not useful.
In short, its useful but no one's losing a job because it exists. Also, the idea of having non-experts manage software systems at any moderate and above level of complexity is still laughable.
A few things to note. 1. This is arxiv - before publication or peer review. Grain of salt.[0] 2. 18 participants per cohort 3. 54 participants total Given the low N and the likelihood that this is drawn from 18-22 year olds attending MIT, one should expect an uphill battle for replication and for generalizability. Further, they are brain scanning during the experiment, which is an uncomfortable/out-of-the-norm experi…
In general I agree with you regarding the weakness of the paper, but not the skepticism towards its outcome. Our bodies naturally adjust to what we do. Do things and your body reinforces that enabling you do even more advanced versions of those things. Don't do things and your skill or muscle in such tends to atrophy over time. Asking LLMs to (as in this case) write an essay is always going to be orders of magnitude…
What is reported as cognitive decline in the paper might very well be cognitive decline. It could also be alternative routing focused on higher abstractions, which we interpret as cognitive decline because the effect is new.
I share your concern, for the record, that people become too attached to LLMs for generation of creative work. However, I will say it can absolutely be used to unblock and push more through. The quality versus quantity balance definitely needs consideration (which I think they are actually capturing vs. cognitive decline) -- the real question to me is whether an individual's production possibility frontier is increased (which means more value per person -- a win!), partially negative in impact (use with caution), or decreased overall (a major loss). Cognitive decline points to the latter.
I've found it both helpful and dangerous, it's great for expanding scope obviously, greater search engine.
But I've also significantly noticed further some of the "harmful patterns" I guess that I would not have noticed about... myself? For example, AI is way too eager to "solve things" when given a prompt, even if you give it an abstract one. It's unable to take a step back and just.... think?
And hey, I notice that I do that too! Lol.
It's helped me realize more refined "stages" of thinking I guess, even beyond just "plan" and "solve".
But for sure a lot of the time I'm just lazy and ask AI to just "go do it" and turn off critical thinking, hoping that it can just 1 shot the problem instead of me breaking it down. Sometimes it genuinely works. Often it doesn't.
I think if I stay way more intentional with my thinking, I can use it to good use. Which will probably reduce AI usage - but it's the first principles of real critical thinking, not the usage of AI.
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These kinds of studies remind me of when my parents told me "stop getting addicted to games" as a kid. Sure, anyone can observe effects, it takes real brains to really try and understand the first principles effects. Addiction went away in a flash once I understood the principles, lol.
Not many people can perform mental arithmetic beyond single-digit numbers. Just plug it into a calculator...
We're at the point of people plugging their thoughts into an LLM and having it do the work for them... what's going to happen to thinking?
A few things to note. 1. This is arxiv - before publication or peer review. Grain of salt.[0] 2. 18 participants per cohort 3. 54 participants total Given the low N and the likelihood that this is drawn from 18-22 year olds attending MIT, one should expect an uphill battle for replication and for generalizability. Further, they are brain scanning during the experiment, which is an uncomfortable/out-of-the-norm experi…
This comment reminds me of the so called Dunning Kruger Effect. That paper had pretty close to the same participation size, and participants were pulled from a single school (Cornell). It also has major methodology problems, and has had an uphill battle for replication and generalizability, actually losing the battle in some cases. And yet, we have a famous term for it that people love to use, often and incorrectly,…