Curious if you have any other thoughts on this after another 10 months?
Those I know who train large models seem to be very confident we will get 100 Trillion parameter models before the end of the decade, but do not seem to think it will happen, say, in the next 2 years.
There is a strange disconcerting phenomena where many of the engineers I’ve talked to most in the position to know, who work for (and in one case owns) companies training 10 billion+ models, seem to have timelines on the order of 5-10 years. Shane Legg recently said he gave a 50% chance of AGI by 2030, which is inline with some the people I’ve talked to on EAI, though many disagree. Leo Gao, I believe, tends to think OpenPhil’s more aggressive estimates are about right, which is less short than some.
I would like “really short timelines” people to make more posts about it, assuming common knowledge of short timelines is a good thing, as the position is not talked about here as much as it should be given how many people seem to believe in it.
For what it’s worth I settled on the Ajeya report aggressive distribution as a reasonable prior after taking a quick skim of the report and then eyeballing the various distributions to see which one felt the most right to me—not a super rigorous process. The best guess timeline feels definitely too slow to me. The biggest reason why my timeline estimate isn’t shorter is essentially correction for planning fallacy.
Those I know who train large models seem to be very confident we will get 100 Trillion parameter models before the end of the decade, but do not seem to think it will happen, say, in the next 2 years.
Curious if you have any other thoughts on this after another 10 months?
Those I know who train large models seem to be very confident we will get 100 Trillion parameter models before the end of the decade, but do not seem to think it will happen, say, in the next 2 years.
There is a strange disconcerting phenomena where many of the engineers I’ve talked to most in the position to know, who work for (and in one case owns) companies training 10 billion+ models, seem to have timelines on the order of 5-10 years. Shane Legg recently said he gave a 50% chance of AGI by 2030, which is inline with some the people I’ve talked to on EAI, though many disagree. Leo Gao, I believe, tends to think OpenPhil’s more aggressive estimates are about right, which is less short than some.
I would like “really short timelines” people to make more posts about it, assuming common knowledge of short timelines is a good thing, as the position is not talked about here as much as it should be given how many people seem to believe in it.
For what it’s worth I settled on the Ajeya report aggressive distribution as a reasonable prior after taking a quick skim of the report and then eyeballing the various distributions to see which one felt the most right to me—not a super rigorous process. The best guess timeline feels definitely too slow to me. The biggest reason why my timeline estimate isn’t shorter is essentially correction for planning fallacy.
FWIW if the current trend continues we will first see 1e14 parameter models in 2 to 4 years from now.