141–150 of 202 posts
Earlier quoted context omitted.
I agree in a "the purpose of a system is what it does" sense but I'm not sure they're inherently normalization systems.
Token selection is based off normalization, even if you train a model to produce outlier answers, even in that process you are biasing to a subset of outliers, which is inherently normalizing.
If computers are bicycles for the mind and AI are cars, I wonder what the analogue for the obesity epidemic is.
The obesity epidemic has much less to do with cars and much more to do with cheapness of food and volume consumed. A typical deli sandwich in the US should be enough to last any normal person three days. Same goes for e.g. ice cream from Shake Shack (random example I know, but one I came across recently). If you buy one of these and eat them in one sitting, the answer to "why am I obese" is simply "you eat way too mu…
A Subway sandwhich is about 600 calories. That's about 1/3 of the daily 2000 calories standard. A Shake Shack shake tops out at 1010 calories, a half of the daily norm.
At the Egyptian city of Naucratis, there was a famous old god, whose name was Theuth; the bird which is called the Ibis is sacred to him, and he was the inventor of many arts, such as arithmetic and calculation and geometry and astronomy and draughts and dice, but his great discovery was the use of letters. Now in those days the god Thamus was the king of the whole country of Egypt; and he dwelt in that great city of…
This was a bit word-salad-y but I share the same basic concern. I think more I worry about the tendency toward greater and greater cognitive off-loading to LLMs. My sister told me a story the other day about how she caught her plumber using chatgpt on his phone to fix an issue with her bathroom. I just think it's good for humans to know how to do stuff.
I've always wanted to be more of a handy man, never knew where to start. I used LLMs to create a toolkit and then used it to fix various stuff around the house. I'm at the point where I'm comfortable with beginner projects moving onto intermediate, and I feel like the quality of my works beats those of hired help at my level of competence. So... I'm glad I could off-load some cognition to LLMs and get to the actual u…
That and it's good for going down rabbit holes of questioning a topic that, before, you'd have to reserve for when you accidentally find a resource that perfectly answers that niche question line, or when you're somehow in conversation with someone who has expertise in the thing you're questioning.
Earlier quoted context omitted.
1. You can't understand the nuances, but there is a general pattern: new inventions may make us slightly less proficient at specifics, yet more powerful overall 2. Imagine a hunter gatherer is time travelled to 2026. You have lunch go to a cafe with him, and he learns that food is cheap, delicious, and abundant. He sees your house, and thinks it's amazing compared to his cave. He thinks that 2026 must be absolute par…
Alternatively he sees that you live in your house alone and feel lonely all the time. Maybe you have a small family and a few friends but it's nothing compared to the tribal life he knows. He sees you spend your day working but rarely get to go outside or do anything active. Even when you're not working you sit behind a desk staring at a screen. He wonders why you bother will all the technology when it made your life…
This future man has paradise indeed.
It is a quirky article but the author, instead of engaging with information sources to understand what important thoughts people have had about these topics, feels the best thing to do is introduce new terms that other terms already exist for. This is basically just inductive bias plus the AI homogenization idea producing a distribution shift. This is what happens in thought-isolation. It isn’t better than educating…
>This is a benefit if you can use your newfound capacity and free time for something better, which I think most people ultimately will. I think for a lot of of us the problem is that this is not a given. It’s often promised and rarely occurs, especially in the modern era. Increased productivity usually just means increased demands in the workplace.
Earlier quoted context omitted.
Token selection is based off normalization, even if you train a model to produce outlier answers, even in that process you are biasing to a subset of outliers, which is inherently normalizing.
Could you elaborate on "token selection is based off normalization"?
https://arxiv.org/pdf/1607.06450
Depending on the model architecture, there is normalization taking place in multiple different places in order to save compute and ensure (some) consistency in output. Training, by its very nature, also is a normalization function, since you are telling the model which outputs are and are not valid, shaping weights that define features.
It is a quirky article but the author, instead of engaging with information sources to understand what important thoughts people have had about these topics, feels the best thing to do is introduce new terms that other terms already exist for. This is basically just inductive bias plus the AI homogenization idea producing a distribution shift. This is what happens in thought-isolation. It isn’t better than educating…
When I read pieces like this all I think is, resistance to change is a helluva drug. I've been working on a project and using LLMs heavily to inform my design decisions. There's already a long list of cases where it has taught me things I wasn't familiar with, alerted me to possibilities I didn't consider, shown me how to do things that I was struggling with. In those cases I ask for references, and it delivers. This…
It’s a corner cutting machine that allows people to shift the burden of their work on to others either in the form of more slop we have to wade through OR more work we have to correct because they couldn’t bother to vet the results.
It’s like writing a paper, running spellcheck, then sending it to some less to look over for you without ever taking a pass yourself. It’s selfish.
Doh. I went in expecting a really cool thesis — because the idea seems somehow intuitive, or at least really intriguing. But I have no clue what I read. Just totally odd and unconvincing. Greenland? Dialectal substrate? The idea is still super intriguing to me though!
How can it be unconvincing if you didn't understand the argument presented in the post?
It is a quirky article but the author, instead of engaging with information sources to understand what important thoughts people have had about these topics, feels the best thing to do is introduce new terms that other terms already exist for. This is basically just inductive bias plus the AI homogenization idea producing a distribution shift. This is what happens in thought-isolation. It isn’t better than educating…
When I read pieces like this all I think is, resistance to change is a helluva drug. I've been working on a project and using LLMs heavily to inform my design decisions. There's already a long list of cases where it has taught me things I wasn't familiar with, alerted me to possibilities I didn't consider, shown me how to do things that I was struggling with. In those cases I ask for references, and it delivers. This…
When I read comments like yours, I’m reminded of (though I’m not comparing you to—I believe you are arguing in good faith) the cryptocurrency shills saying anyone who is against cryptocurrencies is just jealous they didn’t get in on the gold rush; they are incapable of imagining or accepting other people have their own reasons beyond what the author can themselves conceptualise.
When people criticise cryptocurrencies, NFTs, the Metaverse, LLMs, they’re not just stubbornly “resisting change”. Those technologies have important issues and repercussions which should be addressed, we shouldn’t just accept change unquestionably.
> Of course, this all depends on using AI to enhance cognition and access to knowledge, as opposed to just letting a machine write all your code for you without review, Yegge-style.
And the latter is exactly what is going to happen and is already happening in large enough quantity that it’s going to be a serious problem.
> But the one about "endangering human development" is wholly in our individual hands. You can use AI to help you learn, or to replace the need to learn.
That completely ignores the loss of skill that happens without you realising, as you lean more on a tool.
https://www.thelancet.com/journals/langas/article/PIIS2468-1...
https://arxiv.org/abs/2506.08872
This is nothing new. We already know that e.g. heavy GPS use makes us weaker at navigating on our own.
https://www.nature.com/articles/s41598-020-62877-0
> One real lesson from this is perhaps that we need to teach people how to use AI in ways that benefit their development, not just their output.
Yes, that is a good goal. But good luck achieving it.