A big issue that a lot of these tech companies seem to have is that they don’t understand what people want; they come up with an idea and then shove it into everything. There are services that I have actively stopped using because they started cramming AI into things; for example I stopped dual-booting with Windows and became Linux-only.
AI is legitimately interesting technology which definitely has specialized use-cases, e.g. sorting large amounts of data, or optimizing strategies within highly restrained circumstances (like chess or go). However, 99% of what people are pushing with AI these days as a member of the general public just seems like garbage; bad art and bad translations and incorrect answers to questions.
I do not understand all the hype around AI. I can understand the danger; people who don’t see that it’s bad are using it in place of people who know how to do things. But in my teaching for example I’ve never had any issues with students cheating using ChatGPT; I semi-regularly run the problems I assign through ChatGPT and it gets enough of them wrong that I can’t imagine any student would be inclined to use ChatGPT to cheat multiple times after their grade the first time comes in. (In this sense, it’s actually impressive technology - we’ve had computers that can do advanced math highly accurately for a while, but we’ve finally developed one that’s worse at math than the average undergrad in a gen-ed class!)
The answer is that it’s all about “growth”. The fetishization of shareholders has reached its logical conclusion, and now the only value companies have is in growth. Not profit, not stability, not a reliable customer base or a product people will want. The only thing that matters is if you can make your share price increase faster than the interest on a bond (which is pretty high right now).
To make share price go up like that, you have to do one of two things; show that you’re bringing in new customers, or show that you can make your existing customers pay more.
For the big tech companies, there are no new customers left. The whole planet is online. Everyone who wants to use their services is using their services. So they have to find new things to sell instead.
And that’s what “AI” looked like it was going to be. LLMs burst onto the scene promising to replace entire industries, entire workforces. Huge new opportunities for growth. Lacking anything else, big tech went in HARD on this, throwing untold billions at partnerships, acquisitions, and infrastructure.
And now they have to show investors that it was worth it. Which means they have to produce metrics that show people are paying for, or might pay for, AI flavoured products. That’s why they’re shoving it into everything they can. If they put AI in notepad then they can claim that every time you open notepad you’re “engaging” with one of their AI products. If they put Recall on your PC, every Windows user becomes an AI user. Google can now claim that every search is an AI interaction because of the bad summary that no one reads. The point is to show “engagement”, “interest”, which they can then use to promise that down the line huge piles of money will fall out of this pinata.
The hype is all artificial. They need to hype these products so that people will pay attention to them, because they need to keep pretending that their massive investments got them in on the ground floor of a trillion dollar industry, and weren’t just them setting huge piles of money on fire.
I know I’m an enthusiast, but can I just say I’m excited about NotebookLLM? I think it will be great for documenting application development. Having a shared notebook that knows the environment and configuration and architecture and standards for an application and can answer specific questions about it could be really useful.
“AI Notepad” is really underselling it. I’m trying to load up massive Markdown documents to feed into NotebookLLM to try it out. I don’t know if it’ll work as well as I’m hoping because it takes time to put together enough information to be worthwhile in a format the AI can easily digest. But I’m hopeful.
That’s not to take away from your point: the average person probably has little use for this, and wouldn’t want to put in the effort to make it worthwhile. But spending way too much time obsessing about nerd things is my calling.
You’re using the wrong tool.
Hell, notepad is the wrong tool for every use case, it exists in case you’ve broken things so thoroughly on windows that you need to edit a file to fix it. It’s the text editor of last resort, a dumb simple file editor always there when you need it.
Adding any feature (except possibly a hex editor) makes it worse at its only job.
From a nerdy perspective, LLMs are actually very cool. The problem is that they’re grotesquely inefficient. That means that, practically speaking, whatever cool use you come up with for them has to work in one of two ways; either a user runs it themselves, typically very slowly or on a pretty powerful computer, or it runs as a cloud service, in which case that cloud service has to figure out how to be profitable.
Right now we’re not being exposed to the true cost of these models. Everyone is in the “give it out cheap / free to get people hooked” stage. Once the bill comes due, very few of these projects will be cool enough to justify their costs.
Like, would you pay $50/month for NotebookLM? However good it is, I’m guessing it’s probably not that good. Maybe it is. Maybe that’s a reasonable price to you. It’s probably not a reasonable price to enough people to sustain serious development on it.
That’s the problem. LLMs are cool, but mostly in a “Hey this is kind of neat” way. They do things that are useful, but not essential, but they do so at an operating cost that only works for things that are essential. You can’t run them on fun money, but you can’t make a convincing case for selling them at serious money.
Being able to summarize and answer questions about a specific corpus of text was a use case I was excited for even knowing that LLMs can’t really answer general questions or logically reason.
But if Google search summaries are any indication they can’t even do that. And I’m not just talking about the screenshots people post, this is my own experience with it.
Maybe if you could run the LLM in an entirely different way such that you could enter a question and then it tells you which part of the source text statistically correlates the most with the words you typed; instead of trying to generate new text. That way in a worse case scenario it just points you to a part of the source text that’s irrelevant instead of giving you answers that are subtly wrong or misleading.
Even then I’m not sure the huge computational requirements make it worth it over ctrl-f or a slightly more sophisticated search algorithm.
The answer is that it’s all about “growth”. The fetishization of shareholders has reached its logical conclusion, and now the only value companies have is in growth. Not profit, not stability, not a reliable customer base or a product people will want. The only thing that matters is if you can make your share price increase faster than the interest on a bond (which is pretty high right now).
As you can see, this can’t go on indefinitely. And also such unpleasantries are well known after every huge technological revolution. Every time eventually resolved, and not in favor of those on the quick buck train.
It’s still not a dead end. The cycle of birth, growth, old age, death, rebirth from the ashes and so on still works. It’s only the competitive, evolutionary, “fast” model has been killed - temporarily.
These corporations will still die unless they make themselves effectively part of the state.
BTW, that’s what happened in Germany described by Marx, so despite my distaste for marxism, some of its core ideas may be locally applicable with the process we observe.
It’s like a worldwide gold rush IMHO, but not even really worldwide. There are plenty of solutions to be developed and sold in developing countries in place of what fits Americans and Europeans and Chinese and so on, but doesn’t fit the rest. Markets are not exhausted for everyone. Just for these corporations because they are unable to evolve.
Lacking anything else, big tech went in HARD on this, throwing untold billions at partnerships, acquisitions, and infrastructure.
If only Sun survived till now, I feel they would have good days. What made them fail then would make them more profitable now. They were planning too far ahead probably, and were too careless with actually keeping the company afloat.
My point is that Sun could, unlike these corporations, function as some kind of “the phone company”, or “the construction company”, etc. Basically what Microsoft pretended to be in the 00s. They were bad with choosing the right kind of hype, but good with having a comprehensive vision of computing. Except that vision and its relation to finances had schizoaffective traits.
Same with DEC.
The point is to show “engagement”, “interest”, which they can then use to promise that down the line huge piles of money will fall out of this pinata.
Well. It’s not unprecedented for business opportunities to dry out. It’s actually normal. What’s more important, the investors supporting that are the dumber kind, and the investors investing in more real things are the smarter kind. So when these crash (for a few years hunger will probably become a real issue not just in developing countries when that happens), those preserving power will tend to be rather insightful people.
If only Sun survived till now, I feel they would have good days
The problem is a lot of what Sun brought to the industry is now in the Linux arena. If Sun survived, would Linux have happened? With such a huge development infrastructure around Linux, would Sun really add value?
I was a huge fan of Sun also, they revolutionized the industry far above their footprint. However their approach seemed more research or academic at times, and didn’t really work with their business model. Red Hat figured out a balance where they could develop opensource while making enough to support their business. The Linux world figured out a different balance where the industry is above and beyond individual companies and doesn’t require profit
I’ve ran some college hw through 4o just to see and it’s remarkably good at generating proofs for math and algorithms. Sometimes it’s not quite right but usually on the right track to get started.
In some of the busier classes I’m almost certain students do this because my hw grades would be lower than the mean and my exam grades would be well above the mean.
I understand some of the hype. LLMs are pretty amazing nowadays (though closedai is unethical af so don’t use them).
I need to program complex cryptography code for university. Claude sonnet 3.5 solves some of the challenges instantly.
And it’s not trivial stuff, but things like “how do I divide polynomials, where each coefficient of that polynomial is an element of GF(2^128).” Given the context (my source code), it adds it seamlessly, writes unit tests, and it just works. (That is important for AES-GCM, the thing TLS relies on most of the time .)
Besides that, LLMs are good at what I call moving words around. Writing cute little short stories in fictional worlds given some info material, or checking for spelling, or re-formulating a message into a very diplomatic nice message, so on.
On the other side, it’s often complete BS shoehorning LLMs into things, because “AI cool word line go up”.
