Quantum computing has been touted as the next frontier for at least a decade now, so I’m wondering why we still aren’t seeing any reporting on some breakthroughs, and whether this is due to it all still being beyond the understanding of general public or there just not being any meaningful developments to speak of at all.
Quantum computing is like fusion power. There are so many complicated little details that we discover as we go and that have to be exactly right that success at a meaningful scale is always just over the horizon.
I only read about this stuff, so I might be completely wrong and the analogy might actually be stupid. :)
BTW this was also true for the creation of the silicon transistor if I remember correctly. Having to have many things exactly right for it to work well.
AI was also touted as the next frontier for over 20 years before it would take the world by storm after big advancements in the 2010’s. Remember the fanfare over Deep Blue vs Kasparov in 1997? On the other hand, blockchain also surpassed a decade of vaporware discourse and there’s still no major technological gains in sight. “Time Of Hype” doesn’t seem to be a good predictor of success.
My personal opinion is that Quantum Computing isn’t going to be as lucrative and world changing as AI (Generative and LLMs specifically) has been, but it is going to be relevant for technical details and enable other wildly imaginative things to be built on top of it, like LED was revolutionary but in a different way, so it might still be very fruitful investment.
Fair. I was purposefully imprecise with “over X years” because AI as a field changed a lot since the 1960’s and a lot of the hype was coming from science fiction instead of real R&D results, but I don’t disagree.
Has it, though? In 1970, the second AI winter pushed in from the north after ANNs didn’t become as revolutionary as imagined.
Guess what serves as the backbone of AI today? That’s right, ANNs. We’ve been on the right track for those 50 years. But it took a lot of iteration to suss out the small details – and there is still a lot more work to do.
Quantum computing has been touted as the next frontier for at least a decade now, so I’m wondering why we still aren’t seeing any reporting on some breakthroughs, and whether this is due to it all still being beyond the understanding of general public or there just not being any meaningful developments to speak of at all.
Quantum computing is like fusion power. There are so many complicated little details that we discover as we go and that have to be exactly right that success at a meaningful scale is always just over the horizon.
I only read about this stuff, so I might be completely wrong and the analogy might actually be stupid. :)
BTW this was also true for the creation of the silicon transistor if I remember correctly. Having to have many things exactly right for it to work well.
AI was also touted as the next frontier for over 20 years before it would take the world by storm after big advancements in the 2010’s. Remember the fanfare over Deep Blue vs Kasparov in 1997? On the other hand, blockchain also surpassed a decade of vaporware discourse and there’s still no major technological gains in sight. “Time Of Hype” doesn’t seem to be a good predictor of success.
My personal opinion is that Quantum Computing isn’t going to be as lucrative and world changing as AI (Generative and LLMs specifically) has been, but it is going to be relevant for technical details and enable other wildly imaginative things to be built on top of it, like LED was revolutionary but in a different way, so it might still be very fruitful investment.
The first AI winter was in 1966. Try something closer to 50 years, at very least.
Fair. I was purposefully imprecise with “over X years” because AI as a field changed a lot since the 1960’s and a lot of the hype was coming from science fiction instead of real R&D results, but I don’t disagree.
Has it, though? In 1970, the second AI winter pushed in from the north after ANNs didn’t become as revolutionary as imagined.
Guess what serves as the backbone of AI today? That’s right, ANNs. We’ve been on the right track for those 50 years. But it took a lot of iteration to suss out the small details – and there is still a lot more work to do.
It has, from my pov of course.