Instead of having SGD “grow” intelligence, design the algorithms of intelligence directly to get a system we can reason about. Align this system to a narrow but pivotal task, e.g. upload a human.
The key to intelligence is finding the algorithms that infer world models that enable efficient prediction, planning, and meaningfully combining existing knowledge.
By understanding the algorithms, we can make the system non-self-modifying (algorithms are constant, only the world model changes), making reasoning about the system easier.
Understanding intelligence at the algorithmic level is a very hard technical problem. However, we are pretty sure it is solvable and, if solved, would likely save the world.
Current focus: How to model a world such that we can extract structure from the transitions between states (‘grab object’=useful high level action), as well as the structure within particular states (‘tree’=useful concept).
Goal: Understand Intelligence
Save the world by understanding intelligence.
Instead of having SGD “grow” intelligence, design the algorithms of intelligence directly to get a system we can reason about. Align this system to a narrow but pivotal task, e.g. upload a human.
The key to intelligence is finding the algorithms that infer world models that enable efficient prediction, planning, and meaningfully combining existing knowledge.
By understanding the algorithms, we can make the system non-self-modifying (algorithms are constant, only the world model changes), making reasoning about the system easier.
Understanding intelligence at the algorithmic level is a very hard technical problem. However, we are pretty sure it is solvable and, if solved, would likely save the world.
Current focus: How to model a world such that we can extract structure from the transitions between states (‘grab object’=useful high level action), as well as the structure within particular states (‘tree’=useful concept).
I am leading a project on that. Read more here and apply on the AISC website.