Sebastien Makes the Start of AGI Case for GPT-4

Sebastien Makes the Start of AGI Case for GPT-4

Microsoft Windows

Sebastien Bubeck makes the case that intelligence has emerged with the trillion parameter generative AIs. He says there are internal representations and learning algorithms inside the systems. Sebastien is a Sr. Principal Research Manager in the Machine Learning Foundations group at Microsoft Research (MSR).

He says the generative systems can be used to explain itself.

GPT-4 still has weaknesses but it can use tools to mitigate those weaknesses. It can call Mathematica to precisely solve math problems.

GPT-4 does not have planning yet. There are some new systems that are trying to address this by working with GPT4.

GPT-4 is not set up to have much learning or memory. It can only remember within a session.

GPT-4 was slightly dumbed down from the internal testing system in order to address safety issues.

1:47 – Sebastien starts
5:36 – goal of the talk: there is some intelligence in the system
6:05 – “beware of trillion-dimensional space and its surprises”
8:20 – example demonstrating GPT4’s common sense
10:40 – theory of the mind
12:29 – theory of mind example
14:27 – consensus definition of intelligence by psychologists published in 1994 and if GPT4 matches this definition
18:00 – how to test GPT4’s intelligence
19:00 – Asking GP4 to write a proof of infinitude of primes
22:13 – The Strange Case of the Unicorn
27:15 – GPT4 vs Stable Diffusion
29:44 – Coding with a copilot that understands
32:57 – GPT4’s performance on coding interviews
33:41 – GPT4’s weaknesses, which can be overcome with toolsSebastien Makes the Start of AGI Case for GPT-4
36:09 – A mathematical conversation with GPT4
42:40 – GPT4 cannot do true planning
45:02 – Is GPT4 intelligent and does it matter?

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