By my own, completely arbitrary split of this into 16 predictions, I would say that this hits on maybe 8 of 16 if we are being a bit generous. Which is good, but certainly not "Inevitable" (the title of the book).
With that said, maybe he meant inevitable as N approaches infinity... So there's still time!
Aside: I think the biggest interesting prediction he had was that AI would obey a user driven network effect. It seems like a very clean prediction, and yet it has failed to materialize? I wonder if this has more to do with just how scrape-able the whole internet was or with distilation or what? There is certainly an advantage to having good user data, but it seems like it is largely something that can be worked around (by hook or crook)?
naasking 33 minutes ago [-]
Is 50% good? It's what you'd expect by posing "will AI do X by 2026?" and then flipping a coin to get an answer.
cousinbryce 4 hours ago [-]
Google’s main product was and continues to be ads
pipes 3 hours ago [-]
It's a bit nit picky because what most users use is theirnai search , well I'm guessing that's what most of us interact with
dude250711 26 minutes ago [-]
Google is a ChatGPT for quick answers, and ChatGPT is a Google for deep web search.
euiee 1 hours ago [-]
They are an ads business my friend - it’s what generate the revenues to cross subsidies the freebies.
jakzurr 3 hours ago [-]
Yes, thank you.
at1as 3 hours ago [-]
In addition to writing about current (and future) technology, Kevin Kelly also put together Vanishing Asia, a photo book documenting disappearing communities and traditions across Asia
Possibly the best photography book I've come across. It's out of print, but I managed to snag a copy on eBay last year
rossdavidh 1 hours ago [-]
I would say that KK's "The bulk of AI will be special purpose software brains" has turned out closer to the truth than "The Bitter Lesson" has. LLM's do not drive cars, or vice versa. Stockfish still beats the newest, largest LLM at chess. Etc. Most of the truly productive "AI" is customized for a specific purpose, or class of purposes anyway.
BenzeneDream 1 hours ago [-]
For now. But the trend remains that bigger, smarter, general purpose AI beats smaller specific purpose models. This is why GPT 5 and 6 remain better at OCR than anything Mistral has put out.
petermcneeley 52 minutes ago [-]
Dont many of the LLMs have smaller sub expert models inside?
froobius 3 hours ago [-]
these are good / accurate, but what's the error-rate? assuming these have been cherry picked, and he made more predictions
AndrewKemendo 5 hours ago [-]
If you really want your mind blown look at how accurate Ray Kurzweil was from his 1999 book Age of Spiritual Machines
The most striking thing is that almost all of his missed predictions were missed not because the technology was not available, but because society rejected or didn’t adopt that technology
socializer 3 hours ago [-]
> but because society rejected or didn’t adopt that technology
OK, so imagine that in 1980, I predicted that we'll colonize Mars by the year 2020. Today, I'm arguing that I was right in my prediction - in broad strokes, we have the technology! Nothing is stopping us. It's just that politicians have different priorities.
Of course, that's a load of bull. You can't decouple predictions about the future of mankind from what said mankind actually decides.
I looked up the predictions on Wikipedia and I'd say that most of them are general enough that they'd hard to disagree with back in 1999 (there will be bioengineering, there will be portable computers, there will be robots, there will be AI), but the timing or the specifics are off on almost every single one of them.
simonebrunozzi 2 hours ago [-]
Except, we don't have the technology to even get to Mars. Forget about colonizing. [0]
Explain what you mean by not being able to get to Mars?
hyperpape 3 hours ago [-]
Go to Dan Luu's evaluation (https://danluu.com/futurist-predictions/), search for "Appendix: detailed information on predictions". Seems like Kurzweil's has a huge number of awful predictions. This is from four years ago, so a few things are closer to being real now. But many things he predicted for the early 2000s still haven't arrived.
AndrewKemendo 2 hours ago [-]
To be clear I’m not saying he got everything right but if you look at the missed ones, many were/are possible technically
jurgenburgen 57 minutes ago [-]
What’s the value of predictions if they’re not good enough to make decisions on?
at1as 3 hours ago [-]
I think it is largely domain dependent. He's had solid predictions around computing, but for biology (and longevity) he seems to be way off.
For instance, by his prediction, we're already many years past a 100 year average life expectancy (with 120 years expected by the end of the decade).
I think his mistake was tightly coupling exponential compute with exponential progress in biology - which has so far not panned out.
_doctor_love 4 hours ago [-]
> but because society rejected or didn’t adopt that technology
I would argue that society would likely have been glad to adopt, but the profit-seeking motive got in the way (again).
AndrewKemendo 4 hours ago [-]
Actually I think it’s the inverse
I was focused on augmented reality largely in part because it was such a big enabler of all other AI technologies
However people have almost uniformly rejected AR glasses my entire career for social reasons and that is only increasing
To the point where in 2016 I was debating with Jessica Alba and she was firm that they won’t take off cause most people don’t want to wear glasses
NDlurker 4 hours ago [-]
I don't like wearing glasses. I should wear my glasses more often, but I don't. But that isn't going to stop me from buying the Even Reality G2
esafak 2 hours ago [-]
All right, let's see his 2026 predictions for the next ten.
royal__ 2 hours ago [-]
Another prediction I remember from this book was that AI would be supplied much like electricity as a kind of utility into many different appliances. This is basically how it has turned out with tokens and APIs.
brabel 4 hours ago [-]
[dead]
nialv7 2 hours ago [-]
OK, but which ones of his predictions did NOT come true? We don’t want survivorship bias do we?
zaik 16 minutes ago [-]
The real survivorship bias is the selection of forecasters.
Rendered at 22:01:14 GMT+0000 (Coordinated Universal Time) with Vercel.
With that said, maybe he meant inevitable as N approaches infinity... So there's still time!
Aside: I think the biggest interesting prediction he had was that AI would obey a user driven network effect. It seems like a very clean prediction, and yet it has failed to materialize? I wonder if this has more to do with just how scrape-able the whole internet was or with distilation or what? There is certainly an advantage to having good user data, but it seems like it is largely something that can be worked around (by hook or crook)?
Possibly the best photography book I've come across. It's out of print, but I managed to snag a copy on eBay last year
The most striking thing is that almost all of his missed predictions were missed not because the technology was not available, but because society rejected or didn’t adopt that technology
OK, so imagine that in 1980, I predicted that we'll colonize Mars by the year 2020. Today, I'm arguing that I was right in my prediction - in broad strokes, we have the technology! Nothing is stopping us. It's just that politicians have different priorities.
Of course, that's a load of bull. You can't decouple predictions about the future of mankind from what said mankind actually decides.
I looked up the predictions on Wikipedia and I'd say that most of them are general enough that they'd hard to disagree with back in 1999 (there will be bioengineering, there will be portable computers, there will be robots, there will be AI), but the timing or the specifics are off on almost every single one of them.
[0]: https://idlewords.com/2023/1/why_not_mars.htm
For instance, by his prediction, we're already many years past a 100 year average life expectancy (with 120 years expected by the end of the decade).
I think his mistake was tightly coupling exponential compute with exponential progress in biology - which has so far not panned out.
I would argue that society would likely have been glad to adopt, but the profit-seeking motive got in the way (again).
I was focused on augmented reality largely in part because it was such a big enabler of all other AI technologies
However people have almost uniformly rejected AR glasses my entire career for social reasons and that is only increasing
To the point where in 2016 I was debating with Jessica Alba and she was firm that they won’t take off cause most people don’t want to wear glasses