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Just keep in mind that there are many highly motivated people directly working on this problem. It's hard to predict how quickly it will be solved and by whom
by deet 8mo ago
Just keep in mind that there are many highly motivated people directly working on this problem.
It's hard to predict how quickly it will be solved and by whom first, but this appears to be a software engineering problem solvable through effort and resources and time, not a fundamental physical law that must be circumvented like a physical sciences problem. Betting it won't be solved enough to have an impact on the work of today relatively quickly is betting against substantial resources and investment.
- datsci_est_2015 8mo agoThe implication of your assertion is pretty much a digital singularity. You’re implying that there will be no need for humans to interact with the digital world at all, because any work in the digital world will be achievable by AI. Wonder what that means for meatspace. Edit: Would also disagree this isn’t a physics problem. Pretty sure power required scales according to problem complexity. At a certain level of problem complexity we’re pretty much required to put enough carbon in the atmosphere to cook everyone to a crisp. Edit 2: illustrative example, an Epic in Jira: “Design fusion reactor”
- slopinthebag 8mo agoWhy do you think it's not a physical sciences problem? It could be the case that current technologies simply cannot scale due to fundamental physical issues. It could even be a fundamental rule of intelligent life, that one cannot create intelligence that surpasses its own. Plenty of things get substantial resources and investment and go nowhere. Of course I could be totally wrong and it's solved in the next couple years, it's almost impossible to make these predictions either way. But I get the feeling people are underestimating what it takes to be truly intelligent, especially when efficiency is important.
- jatari 8mo ago>It could even be a fundamental rule of intelligent life, that one cannot create intelligence that surpasses its own. Well that is easily disproved by the fact that people have children with higher IQ's than their own.
- slopinthebag 8mo agoThat's not what I mean, rather than humans cannot create a type of intelligence that supersedes what is roughly capable from human intelligence, because doing so would require us to be smarter basically. Not to say we can't create machines that far surpass our abilities on a single or small set of axis.
- small_model 8mo agoGiven SOTA models are Phd level in just about every subject this is clearly provably wrong.
- zozbot234 8mo agoI'll believe that claim when a SOTA model can autonomously create content that matches the quality and length of any average PhD dissertation. As of right now, we're nowhere near that and don't know how we could possibly get there. SOTA models are superhuman in a narrow sense, in that they have solid background knowledge of pretty much any subject they've been trained on. That's great. But no, it doesn't turn your AI datacenter into "a country of geniuses".
- slopinthebag 8mo agoAre humans just Phd students in a vat? Can a SOTA model walk? Humans in general find that task, along with a trillion other tasks that SOTA models cannot do, to be absolutely trivial.
- ordersofmag 8mo agoSeems like if evolution managed to create intelligence from slime I wouldn't bet on there being some fundamental limit that prevents us from making something smarter than us.
- mitthrowaway2 8mo agoThink hard about this. Does that seem to you like it's likely to be a physical law? First of all, it's not necessary for one person to build that super-intelligence all by themselves, or to understand it fully. It can be developed by a team, each of whom understands only a small part of the whole. Secondly, it doesn't necessarily even require anybody to understand it. The way AI models are built today is by pressing "go" on a giant optimizer. We understand the inputs (data) and the optimizer machine (very expensive linear algebra) and the connective structure of the solution (transformer) but nobody fully understands the loss-minimizing solution that emerges from this process. We study these solutions empirically and are surprised by how they succeed and fail. We may find we can keep improving the optimization machine, and tweaking the architecture, and eventually hit something with the capacity to grow beyond our own intelligence, and it's not a requirement that anyone understands how the resulting model works. We also have many instances in nature and history of processes that follow this pattern, where one might expect to find a similar "law". Mammals can give birth to children that grow bigger than their parents. We can make metals puter than the crucible we melted them in. We can make machines more precise than the machines that made those parts. Evolution itself created human intelligence from the repeated application of very simple rules.
- ThrowawayR2 8mo agoMany highly motivated people with substantial resources and investment have worked on a lot of things and then failed at them with nothing to show for it.