Machine learning

From RB Wiki
Revision as of 23:27, 20 January 2020 by Lê Nguyên Hoang (talk | contribs) (Created page with "Machine learning is the idea of letting algorithms write (or update) their own codes. It is at the heart of recent breakthroughs in computer science, especially in image analy...")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)

Machine learning is the idea of letting algorithms write (or update) their own codes. It is at the heart of recent breakthroughs in computer science, especially in image analysis, speech recognition, natural language processing, but even problem solving [cite AlphaFold, deep learning for symbolic math]. Perhaps most crucially, there are strong arguments to suggest that it will allow further spectacular progress in the coming years.

Turing's argument

The most compelling case for machine learning is arguably given in Section 7 of Turing 1950 paper.

Supervised, unsupervised and reinforced

There are 3 main forms of learning.

What makes machine learning safety hard

Can't apply formal verification!

Machine learning is data and goal-driven!

This means that we should care about quality data collection, but also on objective function design. It has been argued that the latter should follow the principle of alignment.