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The AGI Landscape

$\Omega$

is going to push the boundary of artificial general intelligence.$\mathbf{\Omega} = \underset{\theta}{\arg\max}\ \mathcal{AGI}(\theta)$

Concepts

Frameworks

Out-of-sample extension of graph adjacency spectral embedding: consider the problem of obtaining an out-of-sample extension for the adjacency spectral embedding, a procedure for embedding the vertices of a graph into Euclidean space.

Measuring and avoiding side effects using relative reachability: introduces a general definition of side effects, based on relative reachability of states compared to a default state, that avoids these undesirable incentives.

Nov

Books

Probability

There are many other books at roughly the same ``first year graduate" level. Here are my personal comments on some.

Jim Pitman has his very useful lecture notes linked to the Durrett text; these notes cover more ground than my course will! Also some lecture notes by Amir Dembo for the Stanford courses equivalent to our 205AB.

Reference

1.

The

`Books`

: https://www.stat.berkeley.edu/~aldous/205B/index.html, by Professor David Aldous from UC Berkeley.Last modified 2yr ago

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