The prediction cluster groups expectations among 15 tracked speakers across 4 sources that AI capabilities will broaden despite uneven performance, often alongside faster research and work.
Daniel Kokotajlo
Daniel Kokotajlo
Scott Alexander
Scott Alexander
Daniel Kokotajlo
Daniel Kokotajlo
Dwarkesh Patel
Dwarkesh Patel
Thomas Larsen
Tim Scarfe
Dwarkesh Patel
Each window as stated
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When each expects it, as they put it. 11 of 88 predictions give a date.
“I think it might be useful to think of our timelines as being like 2070, 2100. It's just that the last 50 to 70 years of that all happened during the year 2027 to 2028 because we are going through this intelligence explosion.”
Scott Alexander and Dwarkesh Patel disagree over whether human ability provides grounds for judging language models negatively when they fail to make the kind of discovery under discussion.
1 for · Scott AlexanderDwarkesh Patel · against 1
“Yeah, and then the example I gave was that humans also can't do this.”
The question is whether a small amount of reinforcement learning on a strong model necessarily produces only a small behavioral effect.
1 for · Beren MillidgeDwarkesh Patel, Beren Millidge and an unidentified speaker · against 3
“can still be like super dramatic you know even if it's like even like one bit can change like your function space a lot and it can like rule out like half the hypothesis space which is huge so like i don't think it's necessarily the case …”