We've lived through enormous computing advances, but it's been fairly obvious for some time that hardware improvements are slowing.
I'm sure there will be amazing advancements in the next 50 years, but I expect a lot of the progress to be in fields that are either currently unknown, or seem unimportant today. Those new fields will see better return on investment.
Now we have countless companies and several countries all competing and building off each other's work in the AI space. So long as people don't get bored or the global economy doesn't collapse, progress should keep chugging along. Another key difference is that it's basically free to get into. Anyone out there can download data sets, existing algorithms, and get to work on tweaking things. There's a strong foundation for any motivated person to build off of.
I disagree with that part. Things slowed dramatically because we stopped putting extreme amounts of effort in, largely because there wasn't enough market demand for aviation or space flight beyond 1970s technology... for a while.
Overcoming physical limitations is one thing. An intelligent being creating something equally or more as intelligent as itself? And obviously I don't mean reproducing. Creating an entirely new class of thing which has intelligence equal to the creator is very different to using the forces of nature to give you an edge over gravity.
We will figure out how the brain works, make better transistors, develop better algorithms, etc
An AI “space race” between the US and China, for instance, will push the field forward over the next decade.
https://www.nasa.gov/audience/formedia/speeches/fg_kitty_haw...
70 years from the first flight to the concorde and the saturn 5. But in the 50 years since, improvements in aerospace have been incremental.
In 75 years we went from ENIAC to TFLOPS in a laptop. But looks like that breakneck pace is slowing down sharply. We've been doing AI nearly as long, and have gone from say, Eliza to GPT-3. A huge advance, but not AGI.
A lot can happen in 50 years, but we've already had our first 70ish years with AI without an AGI breakthrough.
To the definition of AGI in the link, maybe a hundred million data scientists can hone a million models, one per "economically viable" task, and start chipping away at the 95% of the economy target, but till now I'd wager AI has put many more people to work than out of it.
It just goes to show that technological advancement can happen rather unpredictably.
And since then, not much has changed. Commercial supersonic flight never took off, and nowadays planes still use turbofans (invented during WWII). Engineering fields commonly make many breakthrough in a really short time, and then settle down for a long period. We can't predict how far IA progress will go. In the 50s, having flying cars by 2000 didn't sound unrealistic given how much flight advanced during the first half of the century. Yet, I don't think anyone nowadays believes we'll have them by 2100.
Also, between Da Vinci's Codex of the flight of birds (1502) and the Wright brothers flight, there has been four centuries. And regarding AGI, we might be closer to Da Vinci then to the Wright.
Conflating them only demonstrates how far we have to go.
As for impossible talk, we have biological examples all around us of what needs to be built. We just need to imitate. Much like computer vision, algorithms sucked at it until they didn't (and all it took was someone scaling up an old design idea plus a lot of data). On the scale of gigantic ambitious goals it's pretty special in that regard. Curing cancer or death or mars colonies may indeed be impossible, by contrast.
I will agree that I trust no one's ability to predict anything. They are all just making almost-entirely-uneducated guess using a few variables out of some vast number of unknowns.
Why stick with this concept - consciousness - which is not well defined, instead of using a much more practical concept: embodiment. Embodiment is the missing link towards human level AI. Agents embodied in a world, like AlphaGO, already surpass humans (on the Go board or Dota 2), we just need to take that ability to real world. The source of meaning is in the game, not the brain. What we need is a better simulator of the world, or a neural technique for imagination in RL, which is under works [1].
> We do know how to quantify intelligence (..).
But how exactly do we do that?
A lot can happen in 50-70 years.
We now have 7 billion people, with more of the world coming online to do R&D. China, specifically, has made it a goal to lead the world in AI by 2025.
India’s economy should grow over the next 2 decades and they will also become a world leader.
With so many resources, the world should easily advance more in the next 50 than it did in the last 100 years.