This is an automated archive.
The original was posted on /r/singularity by /u/Benista on 2024-01-12 01:23:28+00:00.
Its been something I've been thinking about since the first LK99 paper. One thing that really stuck out to me was that it was derived from extremely common, and well understood materials. Of course, it turned out to be not so simple, but the idea still stuck. What are we missing, that is right infront of our eyes, but no one person can know enough to actually see it? Is there a much greater cost to specalisation than we realise?
A lot of people in my family are specialists, various PHDs, highly focused careers, and deep mastery of a variety topics. But, all have had to pay the same cost of eschewing a lot of knowleadge to purse a depth of knowleadge. We are only human afterall, there is always a limit to our ability. What if there wasn't though? What if instead of being a jack of all trades, master of none, you could just be a master of all? Maybe a human can't (yet), but what about a machine?
The computer age, sometimes also called the information age, has allowed us to collect vast, VAST quantities of information. Every day, every hour huge amount of new knowleadge is created, research published, thoughts spewed out into the internet. A lot of it useless, much of it derivitive, and who knows how much of it is repetitive. But, do we actually know how valuable a piece of information is? Maybe we can assess it within our own discipline, but what about in that discipline, or that one? So many of our discoveries are stumbled upon by accident, or a chance encounter.
I think we only understand a fraction of our knowleadge. AI doesn't have to go out and discover, or create, radical new things. Though, im sure in the future it will. In the meantime, it is going to help us understand far more about what we already know. Crucially, this is something AI is also very good. It doesn't have to surpass human's in depth of knowleadge, just in breadth, for it to discover increadible new things.
I bring this up in particular because a lot of people focus on the brand new things AI could discover, but forget about all our own discoveries that AI could help us understand better. About all the new ways that our existing knowleadge can be combined. Because if we can potentially pull something a significant as a room tempreture superconductor (or atleast a new field of research) from two of the best understood materials in the world. What other things are just waiting to be discovered, and all you need to do is combine existing information in new ways? Like giant neural networks trained on ever more powerful super computers.
This is one of the main reasons I think AI is going to have major impacts sooner rather than later. I don't think it needs crazy new breakthroughs, we just need to collate as much of our research as possible, and train up new LMM's on it. It's not even inter-disciplinary information either, the amount of knowleadge we have collected is so vast, that true specalists have to focus on very narrow topics, within already narrow fields. This is something that will happen much sooner, rather than later.