Isn't it enough that clueless marketers who get their Tech knowledge from businessinsider and bloomberg are constantly harping on about AI.
Seems we as a community have resigned or given up in this battle against common sense. Maybe long ago. Still there should be some form of moderation penalizing these shill posts that only glorify AI as being the future, ... the same way that not everything about crypto or the blockchain ended up on the FP. Seems with AI we're looking the other way and are OK with it?
Or maybe it's me.
The AI discussions can indeed be repetitive and tiresome here, especially for regulars, but they already seem to be downweighted and clear off the front page quite fast.
But it's a major focus of the industry right now, involving a genuinely novel and promising new class of tools, so the posts belong here and the high engagement that props them up seems expected.
Not just him.
> But it's a major focus of the industry right now, involving a genuinely novel and promising new class of tools, so the posts belong here and the high engagement that props them up seems expected.
In your opinion (and admittedly others), but that doesn't make the overhype any less tiresome. Yes it is novel technology, but there's alway novel technology, and it isn't all in one area, but you wouldn't know it by what hits the front page these days.
Anyway, it's useless to shake fists at the clouds. This hype will pass, just like all the others before it, and the discussion can again be proportional to the relevance of the topic.
I use Claude and Chatgpt EVERY DAY.
Those services help me run out scripts for data munging, etc etc very quickly. I don't use it for high expertise writing, as I find it takes more than I get back, but I do use it to put words on a page for more general things. If your deep expertise is programming, you may not use it much either for that. But man oh man has it magnified my output on the constellation of things I need to get done.
What other innovation in the last decade has been this disruptive? Two years ago, I didn't use this. Now I do as part of my regular routine, and I am more valuable for it. So yes, there is hype, but man oh man, is the hype deserved. Even if AI winter started right now, the productivity boom from Claude level LLMs is nothing short of huge.
We use several tools derived from "AI research" every single day in our lives.
They are tools and, at every cycle, we gain new tools. They hype is the issue.
I think the issue is whether you think that HN posts on AI are basically marketing, or about sharing new advances with a community that needs to be kept on top of new advances. Some posts are from a small startup trying something, or from a person sharing a tool. I think these are generally valuable. I might benefit from a RAG, but won't build one from scratch. In terms of this crowd, I can't think of advances that in other areas that are as impactful as machine learning lately. Its not like crypto. Crypto was an interesting innovation, but one in which mostly sought a market instead of the a market seeking an innovation. There is no solid "just use a database" analogical response here like was the well used refrain to attempt at practical uses of cryptocurrency tech. Sure, AI companies built on selling something silly like "the perfect algorithm to find you a perfect date!" is pure hackery, but even at the current level of llm, I don't think we are any where near understanding its full potential/application. So even if we are on the brink of an AI winter, its in the Bahamas.
Also, looking at the most popular stories with AI in the title over the last month show quite a varied array of topics. https://hn.algolia.com/?dateRange=pastMonth&page=0&prefix=fa...
If HN readers feel that AI-related articles are showing up too much, then I'd say it would be on them to find articles on topics that interest them and post them to HN.
I disagree.
One of my biggest irritations with HN comment sections is how frequently people seem to want to ignore the specific interesting thing an article is about and just express uninteresting and repetitive generic opinions about the general topic area instead.
CACM was totally complicit in spreading the blockchain hype: https://cacm.acm.org/?s=blockchain
That said, I'm not hating the player, people gotta eat. But I totally lack appreciation for the game.
Now, they are good text interfaces. They're good for parsing and creating text. There even seems to be very, very basic thought and maybe even creativity (at a very, very basic level). At this point though, I can't see them improving much more without a major change in technology, techniques, something. The first time I saw them I thought they were just regression analysis on steroids, and not going to lie, they still have that vibe considering tech companies have clusters up to 350k H100s and LLMs still are dumber than the average person for most tasks.
I'm currently creating an app that uses an LLM as an interface and it's definitely interesting, but most of the heavy lifting of the app will be the functions it calls and a knowledge database since it needs to have more concrete and current knowledge. But hey, it's nicer than implementing search from scratch I guess.
AI is really neat. I don’t understand how a business model that makes money pops out on the other end.
At least crypto cashed out on NFTs for a while.
Tractors and farming.
By turning what is traditionally a labour intensive product into a capital intensive one.
For now, the farmers who own tractors will beat the farmers who need to hire, house and retain workers (or half a dozen children).
This goes well for quite some time, where you can have 3 people handle acres & acres.
I'll be around explaining how coffee beans can't be picked by a tractor or how vanilla can't be pollinated with it.
Edit: Also, 3 people can handle 100 acres of land, given the crop. That happens today.
Edit: Crop-type was specified, I was incorrect.
Capital intensive industries require low crime and geopolitical stability. Strongman politics means that investors who buy such equipment will simply be robbed at literal gunpoint by local gangs.
What issues do you see?
I pay for ChatGPT and for cursor and to me that's money very well spent.
I imagine tools like cursor will become common for other text intensive industries, like law, soon.
Agreed that the hype can be over the top, but these are valuable productivity tools, so I have some trouble understanding where you're coming from.
[1]: https://www.fooddive.com/news/sprig-is-the-latest-meal-deliv...
[2]:https://techcrunch.com/2019/01/21/munchery-shuts-down/?gucco...
It seems with crypto the business "benefits" were mostly adversarial (winners were those doing crimes on the darknet, or to allow ransomware operators to get paid). The underlying blockchain Tech itself though failed to replace transactions in a database.
The main value for AI today seems to be generative Tech to improve the quality of Deepfakes or to help everyone in Business write their communication with an even more "neutral" non-human like voice, free of any emotion, almost psychopathic. Like the dudes who are writing about their achievements on LinkedIn in 3rd person, ... Only now it's psychopathy enabled by the machine.
Also I've seen people who, without AI are barely literate, are now sending emails that look like they've been penned by a post-doc in English literature. The result is it's becoming a lot harder to separate the morons, and knuckle-draggers from those who are worth reaching out and talking to.
yes old man yelling at cloud.
In the 1980s, AI was a few people at Stanford, a few people at CMU, a few people at MIT, and a scattering of people elsewhere. There were maybe a half dozen startups and none of them got very big.
The industry as a whole was smaller though.
The word sense disambiguation problem did kill a lot of it pretty quickly though.
There were a lot of places that tried a bit of '80s "AI", but didn't accomplish much.
I don't know how that can be dismissed as nothing.
I've wondered for a while if Artificial Life is in its own winter, waiting for someone to apply the lessons of scale we learned from neural nets.