The first electrical motors and lightbulbs absolutely sucked, but the former was still a radical transformation from factories based on a huge steam engine prime mover distributing motive power via belts and pulleys, and the latter was still an improvement over gas lanterns.
The very early internet also sucked, but was nevertheless useful. This was still true even for the very early public web, which was decades later.
The AI which already actually exists is a major general technological breakthroughs, comparable to the Internet and electricity.
Any given AI doesn't need to be superhuman to be comparable.
> And are any of them actually succeeding?
Yup. Old example now, but most physical post (at least in industrialised nations) is now read and sorted by machines which learned to read handwriting as well as printed addresses. ML on handwritten text was basically the "hello world" of AI even 5-10 years back.
And online, spam filtering has always needed help from AI. Before Transformers came along, the state of the art for natural language processing was just counting words in whichever bucket (sales for spam, good-and-bad for sentiment, etc.) and applying Bayesian rules.
This kind of thing was the bread and butter of AI before ChatGPT came along and people forgot AI could be anything beyond a chatbot. Though even as a chatbot, it's a surprisingly effective tool; heck, even as autocomplete it's a surprisingly effective tool, and that's about the weakest thing you can do with it.
> Where are the new AI businesses? Where's the new wealth and money?
Google.
Like, not just today's Google, the original one.
The whole thing about Page Rank is a matrix multiply, and then they added personalisation and ads which uses your every action as signal to optimise a multi-armed-bandit problem. It is, in fact, a machine learning problem; it is AI.
And of course the thing with ads is this argument applies to all ad agencies, so also Facebook. (And not just how Facebook has AI generated scams etc., though even scams are still "where's the money").
Ditto recommendation engines. Both for what news article to read next, what goods Amazon or eBay etc. will suggest, and what shows or clips YouTube etc. will suggest.
And translation. If you forget machine learning and try to write translation software as a traditional piece of software, it will suck: the example I was given when I was young was someone's attempt that ended up with "water sheep" for "hydraulic rams". Google Translate wasn't the first, nor only, tool, but Google did invent the Transformer model specifically for improved translations. And while Google didn't monetise this directly (but did put auto-translation into Chrome and (IIRC) Android apps so perhaps indirectly), some of the other translation companies sure did.
> Where's the one guy AI pioneer doing what used to take 100s?
Depending on what you mean, either "LMGTFY", or "they joined the big companies to do even more because resources", or "the people posting AI-generated projects on Show HN", or "you can sort of see this by looking at employee count and finding the ones with very small head-counts: https://www.ycombinator.com/companies/industry/ai "
To combine the examples, here's an AI product originally authored by one person to do translation on OCR'ed text which got bought by big tech: https://en.wikipedia.org/wiki/Word_Lens
The first electrical motors and lightbulbs absolutely sucked, but the former was still a radical transformation from factories based on a huge steam engine prime mover distributing motive power via belts and pulleys, and the latter was still an improvement over gas lanterns.
The very early internet also sucked, but was nevertheless useful. This was still true even for the very early public web, which was decades later.
The AI which already actually exists is a major general technological breakthroughs, comparable to the Internet and electricity.
Any given AI doesn't need to be superhuman to be comparable.
> And are any of them actually succeeding?
Yup. Old example now, but most physical post (at least in industrialised nations) is now read and sorted by machines which learned to read handwriting as well as printed addresses. ML on handwritten text was basically the "hello world" of AI even 5-10 years back.
And online, spam filtering has always needed help from AI. Before Transformers came along, the state of the art for natural language processing was just counting words in whichever bucket (sales for spam, good-and-bad for sentiment, etc.) and applying Bayesian rules.
This kind of thing was the bread and butter of AI before ChatGPT came along and people forgot AI could be anything beyond a chatbot. Though even as a chatbot, it's a surprisingly effective tool; heck, even as autocomplete it's a surprisingly effective tool, and that's about the weakest thing you can do with it.
> Where are the new AI businesses? Where's the new wealth and money?
Google.
Like, not just today's Google, the original one.
The whole thing about Page Rank is a matrix multiply, and then they added personalisation and ads which uses your every action as signal to optimise a multi-armed-bandit problem. It is, in fact, a machine learning problem; it is AI.
And of course the thing with ads is this argument applies to all ad agencies, so also Facebook. (And not just how Facebook has AI generated scams etc., though even scams are still "where's the money").
Ditto recommendation engines. Both for what news article to read next, what goods Amazon or eBay etc. will suggest, and what shows or clips YouTube etc. will suggest.
And translation. If you forget machine learning and try to write translation software as a traditional piece of software, it will suck: the example I was given when I was young was someone's attempt that ended up with "water sheep" for "hydraulic rams". Google Translate wasn't the first, nor only, tool, but Google did invent the Transformer model specifically for improved translations. And while Google didn't monetise this directly (but did put auto-translation into Chrome and (IIRC) Android apps so perhaps indirectly), some of the other translation companies sure did.
> Where's the one guy AI pioneer doing what used to take 100s?
Depending on what you mean, either "LMGTFY", or "they joined the big companies to do even more because resources", or "the people posting AI-generated projects on Show HN", or "you can sort of see this by looking at employee count and finding the ones with very small head-counts: https://www.ycombinator.com/companies/industry/ai "
To combine the examples, here's an AI product originally authored by one person to do translation on OCR'ed text which got bought by big tech: https://en.wikipedia.org/wiki/Word_Lens