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Agreed, the two are virtual opposites: no one is making money from AI (yet), but everyone is using it, while in crypto, a bunch of people were making money from

Agreed, the two are virtual opposites: no one is making money from AI (yet), but everyone is using it, while in crypto, a bunch of people were making money from it and no one was actually using it.

Kalanos 4y ago
Did you mean one is making money from "generative" AI yet? Let's not forget the decade of supervised AI success
- vannevar 4y ago
  Correct, AI has obviously been making money for a long time. But it wasn't described as a bubble until recent developments fired up a rapid rise in startups/investment.
rg111 4y ago
We, in my last company saved our business customers US$2-3mn/year using AI products. And we made good money selling those products. Those weren't products sold from techies to techies (the way Blockchain made some people money) either. And those products were end-user facing- it solved problems for them, too. And I know a lot of people who are making money solving real problems for people outside of tech. Equating AI and blockchain is a common HN commentariat fallacy.
lostlogin 4y ago
Siemens are selling AI for large sums from their medical division. I use it all day every day to denoise then upscale medical images and it’s fantastic. https://www.siemens-healthineers.com/magnetic-resonance-imaging/technologies-and-innovations/deep-resolve https://www.siemens-healthineers.com/magnetic-resonance-imag...
- mrguyorama 4y ago
  What guarantee do they make that their algorithm wont hallucinate away an important tumor or something?
  - lostlogin 4y ago
    The entirety of the acquired data is in the image you see. You can turn the processing off and look at the images without it if you are worried. You also don’t diagnose off one image. You use several in each plane, and more than one image weighting. The software is unaware of the other planes and images when processing. You don’t need long playing with it to be very confident that it’s utterly transformed MR imaging. An example: decent resolution cervical spine Sag T2 imaging used to take a few minutes (2 or 2:30?), it’s now 40 ish seconds. It’s made scans faster, and better looking.

Agreed, the two are virtual opposites: no one is making money from AI (yet), but everyone is using it, while in crypto, a bunch of people were making money from it and no one was actually using it.

Kalanos 4y ago

Did you mean one is making money from "generative" AI yet? Let's not forget the decade of supervised AI success

vannevar 4y ago
Correct, AI has obviously been making money for a long time. But it wasn't described as a bubble until recent developments fired up a rapid rise in startups/investment.

rg111 4y ago

We, in my last company saved our business customers US$2-3mn/year using AI products. And we made good money selling those products. Those weren't products sold from techies to techies (the way Blockchain made some people money) either. And those products were end-user facing- it solved problems for them, too. And I know a lot of people who are making money solving real problems for people outside of tech. Equating AI and blockchain is a common HN commentariat fallacy.

lostlogin 4y ago

Siemens are selling AI for large sums from their medical division. I use it all day every day to denoise then upscale medical images and it’s fantastic. https://www.siemens-healthineers.com/magnetic-resonance-imaging/technologies-and-innovations/deep-resolve https://www.siemens-healthineers.com/magnetic-resonance-imag...

mrguyorama 4y ago
What guarantee do they make that their algorithm wont hallucinate away an important tumor or something?
- lostlogin 4y ago
  The entirety of the acquired data is in the image you see. You can turn the processing off and look at the images without it if you are worried. You also don’t diagnose off one image. You use several in each plane, and more than one image weighting. The software is unaware of the other planes and images when processing. You don’t need long playing with it to be very confident that it’s utterly transformed MR imaging. An example: decent resolution cervical spine Sag T2 imaging used to take a few minutes (2 or 2:30?), it’s now 40 ish seconds. It’s made scans faster, and better looking.