81–90 of 228 posts
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What are "(c)opywrong" laws? I'm not being facetious. What specifically are you drawing objection to?
Laws that make it illegal to use one's own property to share information. A correction of the copyright misnomer.
You didn't carve out any exceptions, hence my assumption.
I like to think its more the age of the Genuine Personal Digital Assistant has begun. The LLMs are great at assisting you to do your job but they wont take over yet.
Her is a forward looking movie in a lot of ways Kids born today will grow up with their phones/device being their best friend and pet, like a Pokémon. You will be incredibly socially shunned if you don’t have one, and corporations will have not only data but an emotional hook into you for life
It can't even parrot this year's memes!
> The rise of AI will free people up to do things that software never will—teaching, caring for patients, and supporting the elderly, for example. Every sci-fi movie show any of those jobs as replaced by AI (or robots). Probably they will not achieve the same level of connection (mostly because they will lack a human body to make expressions, at least at the beginning). Those jobs will be replaced, not because there…
Oh please . This is such a trope at this point. We asked ChatGPT a question about a system the other day. Its response was, > That number is equivalent to [another number]. That number controls $thing, and that number is the recommended value for thing according to $standard. It relates to $unrelated_thing. It did the math wrong when converting the number from one unit to another. (From days to seconds.) While it got…
Sure, maybe we're about to hit a wall. But I'm not seeing any evidence of that as it stands.
Also, it's not clear to me why it's impossible for an LLM to learn symbolic manipulation?
> I picked AP Bio because the test is more than a simple regurgitation of scientific facts—it asks you to think critically about biology. Of course, the LLM is just regurgitating the facts from the textbooks as well as thousands or millions of test samples. It's certainly possible to formulate a biology question that a decent student would be able to answer easily, but LLM would be helpless at (by carefully choosing…
Yeah, I think that we need to probe how much these models are merely memorising their inputs rather than learning a more genereal, compressed (sortof) representation. Honestly though, ten years ago NLP was using Bag of Words and Markov Chains, it's pretty phenomenal how far it's come. To be fair, I mostly agree with your main point, but it's still remarkably impressive progress in a relatively short period of time.
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The internet never had its "aha" moment like AI is now. Most people didn't know or care about it until decades into its existence.
AI has been around for as long (or even longer, depending on how you see it) as the internet (counting the start of internet as the beginning of TCP/IP).
25 years ago when I was just starting my Bachelor's degree, AI was in a sort of "hiatus". The "great" AI procedures were mostly rule based systems. We read about MYCIN and similar expert systems and how they could do amazing stuff. We also read about AI generating new strategies for Backgammon. That was amazing.
But during the 90s/2000s, nothing spectacular happened. We had some advances in neural networks, which were just an academic curiosity given their processing requirements. (I remember implementing a NN that could recognize vowels using C in school). We also had Genetic Algorithms, that were basically optimizers. We had some interesting implementations such as the Creatures game series and similar.
Then "Machine Learning" started gaining notoriety. Industry started using "Machine Learning" techniques to perform some types of forecasting. This came a bit later after "Data warehousing". I remember all the talk about hypercubes and that crap. And how Walmart would extract "knowledge" and place beer six-packs in the diapers aisle so that "dad" would impulse-buy beer when "mom" makes him go to buy diapers.
The ML time was an exciting time, and for some time mainstream thought that ML was AI ... but there were lots of other things cooking.
Now suddenly we have enough power to make non-trivial Neural Networks... and suddenly we have Deep Learning and these LLM with HUGE networks. And industry has just started looking at it. These are exciting times.
The other side of the coin is that during all these times, "mainstream" goal-post has been pushed and pushed for AI... what was AI in the 60s-70s (rule based systems like MyCIN), is not AI nowadays (they are just pattern matching, if-elses!! they say). What was AI in the 80s-90s (Genetic Algorithms, Multi-Agent systems) is not AI nowadays... and what was AI in the 2000-2010s (Random Forests, SVMs, AdaBoost) is no AI nowadays (just statistics!). But overall, it has been a very interesting subject to study.
I was one of the people that started off in tech with dreams of a digital Nirvana. I ignored the "negative naysayers," and sallied forth, with an open heart, and hope for the future.
I'm really quite disappointed in what we've done with these marvelous tools. As I've gotten older, wiser, and a lot more cynical, I can tell you that, if I had known, then, about human nature, what I know now, it would have been entirely predictable.
I think we'll be seeing AI-driven scammers, calling and messaging us, almost incessantly, I think we'll be seeing AI-generated political manipulation, like fake videos and audio, of politicians and public figures, I think we'll be seeing AI-driven promotional campaigns, and almost undetectably subtle media manipulation, like corporations seeding news stories with their talking points. I also think that we'll be seeing AI-driven workplaces, where it will be hard to be simply human, and AI-driven surveillance, by authoritarian regimes (and people right here, will happily sell it to them).
I want to believe that we'll do good, but bad pays so well, and there's outright scorn for doing stuff for any reason other than pure, personal profit.
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The internet evolved, it wasn't just useful all at once (as in "a demonstration that struck me"). Early users struggled every day to grow its utility and find more uses, all the way from a glorified BBS to what it is today.
The first time someone demo'ed the web to me, my first thought was -- why would I use this when I have ftp, gopher, archie, etc... The web definitely didn't seem revolutionary to me. And for me my introduction to the internet was even more mundane -- it was just email and the ability to telnet so I could do my programming assignments.
I think the web would have evolved quite differently had their been a good PowerPoint like gui design tool for building sites, one that wasn’t focused on the backside.
Oh please . This is such a trope at this point. We asked ChatGPT a question about a system the other day. Its response was, > That number is equivalent to [another number]. That number controls $thing, and that number is the recommended value for thing according to $standard. It relates to $unrelated_thing. It did the math wrong when converting the number from one unit to another. (From days to seconds.) While it got…
I was very excited by GPT when it came out, but this showed to me how an absolute confident bullshiter it is. It can't say "I don't know".