I don't think that the scaling hypothesis gets recognized enough for how radical it is. For decades, AI sought some kind of master algorithm of intelligence. The scaling hypothesis says that there is none: intelligence is the ability to use more compute on more data.
Joscha Bachx.comI don't think that the scaling hypothesis gets recognized enough for how radical it is. For decades, AI sought some kind of master algorithm of intelligence. The scaling hypothesis says that there is none: intelligence is the ability to use more compute on more data.
The scaling hypothesis is the idea that this resource-intensive strategy is all it will take to build a human-level AI system, and possibly systems that surpass human-level intelligence.50
Dwarkesh Patel • The Scaling Era: An Oral History of AI, 2019–2025
So far, the (exponentially) more compute and data you put in, the more intelligence you get out. This effect is so clear and so important that I call the period since 2016 the scaling era of AI.55
Dwarkesh Patel • The Scaling Era: An Oral History of AI, 2019–2025
This is amazing.
They are saying they can predict the level of intelligence based on the compute they use. Which means they have made intelligence just an engineering question rather than magic. https://t.co/dt4zOF8TBo