HackerPapers

arXiv:1603.08262cs.AI

Towards Machine Intelligence

Kamil Rocki

HN submission. Found in a submission link or body. Submitters do not count as commenters in the main ranking; a submission is not an endorsement.

Abstract

There exists a theory of a single general-purpose learning algorithm which could explain the principles of its operation. This theory assumes that the brain has some initial rough architecture, a small library of simple innate circuits which are prewired at birth and proposes that all significant mental algorithms can be learned. Given current understanding and observations, this paper reviews and lists the ingredients of such an algorithm from both architectural and functional perspectives.

arXiv comments
10 pages, submitted to AGI-16. arXiv admin note: substantial text overlap with arXiv:1512.01926
Journal reference
DOI
Subjects
cs.AIArtificial Intelligence cs.LGMachine Learning cs.NENeural and Evolutionary Computing

On Hacker News

No comments linking this paper were found in the collected sources. Found in 2 HN submissions from Mar 2016 to Mar 2016. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments0 threads

No comments linking this paper were found in the collected sources. Open submission discussions.

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.