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Introduction
I happen to be in that happy stage in the research cycle where I ask for money so I can continue to work on things I think are important. Part of that means justifying what I want to work on to the satisfaction of the people who provide that money.
This presents a good opportunity to say what I plan to work on in a more layman-friendly way, for the benefit of LessWrong, potential collaborators, interested researchers, and funders who want to read the fun version of my project proposal
It also provides the opportunity for people who are very pessimistic about the chances I end up doing anything useful by pursuing this to have their say. So if you read this (or skim it), and have critiques (or just recommendations), I'd love to hear them! Publicly or privately.
So without further ado, in this post I will [...]
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Outline:
(00:06) Introduction
(02:40) Reinforcement learning
(02:44) Agentic AIs vs Tool AIs
(04:54) Data walls
(07:05) Values
(07:49) Ok, but concretely what will you actually do?
(11:10) Call to action
The original text contained 1 footnote which was omitted from this narration.
---
First published:
Source:
Narrated by TYPE III AUDIO.
Introduction
I happen to be in that happy stage in the research cycle where I ask for money so I can continue to work on things I think are important. Part of that means justifying what I want to work on to the satisfaction of the people who provide that money.
This presents a good opportunity to say what I plan to work on in a more layman-friendly way, for the benefit of LessWrong, potential collaborators, interested researchers, and funders who want to read the fun version of my project proposal
It also provides the opportunity for people who are very pessimistic about the chances I end up doing anything useful by pursuing this to have their say. So if you read this (or skim it), and have critiques (or just recommendations), I'd love to hear them! Publicly or privately.
So without further ado, in this post I will [...]
---
Outline:
(00:06) Introduction
(02:40) Reinforcement learning
(02:44) Agentic AIs vs Tool AIs
(04:54) Data walls
(07:05) Values
(07:49) Ok, but concretely what will you actually do?
(11:10) Call to action
The original text contained 1 footnote which was omitted from this narration.
---
First published:
Source:
Narrated by TYPE III AUDIO.
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