Headline July 02, 2018/ "' *A.I. -PRIVILEGED- FEW* "'

"' *A.I. -PRIVILEGED- FEW* "'

ARTIFICIAL INTELLIGENCE  is just so stuck. Real progress in growing forward will require an  international scientific collaboration, somewhat along the lines of-

The World Students - most lovingly and respectfully called !WOW!, - for every single subject in the world.

To get computers to think like humans, we need a new "Artificial Intelligence" paradigm, one that places ''bottom-up" and ''Top-down" knowledge on equal footing.

Bottom-up knowledge is the kind of raw information we get directly from our senses, like patterns of light falling on our retina.

"Top-down" knowledge comprises cognitive models of the world and how it works.

DEEP LEARNING is very good at  bottom up knowledge like discerning which patterns of pixels correspond to golden retrievers as opposed to Labradors.

But is of no use when it comes to top-down knowledge.

If my daughter sees her reflection in a bowl of water, she knows the image is illusory; she knows she is not actually in the bowl.

To a deep learning system, though,  the system lacks a theory of the world and how it works, integrating that sort of knowledge of the world may be the next big hurdle in A.I., a pre-requisite to advance medicine and scientific understanding.

I fear, however, that neither of our two current approaches to funding A.I. research - small research labs in the academy and significantly larger labs in private industry - is poised to succeed.

I say this as someone who has experience with both models, having worked on A.I. both as an academic researcher and as the founder of a start-up company Geometric Intelligence, which was recently acquired by Uber.

Academic labs are too small.

Take the development of automated machines reading, which is a key to building any truly intelligent system. Too many separate competencies are need for any lab to tackle the problem.

A full solution will incorporate advances in natural language processing [e.g parsing sentences into words and phrases], knowledge representation {e.g. integrating the content of the sentences with the other sources of knowledge} and -

Inference [reconstruction of what is implied but not written].

Each of these problems represent a lifetime work for any single university lab. 

Corporate labs look like those of Google  and Facebook have the resources to tackle big questions, but in a world of quarterly reports and bottom lines -

They tend to concentrate on narrow problems like optimizing advertisement placement or automatically screening videos for offensive content.

There is nothing wrong with such a research, but it is unlikely to lead to major breakthroughs .
Even Google Translate, which pulls off the neat trick of approximating near translations by statistically associating sentences across languages, doesn't understand a world of what it is translating.

I look with envy at peers in high energy physics, and in particular at CERN, the European Organization for Nuclear Research, a huge, international collaboration, with thousands of scientists and billions of dollars of funding.

They pursue ambitious tightly defined projects - like using the Large Hadron Collider to discover the Higgs boson - and share their results with the world, rather than restricting them to a single country or corporation.

Even the largest open efforts at A.I. like Open A.I., which has about  50 staff members and is sponsored in part by Elon Musk, is tiny by comparison.

At international A.I. mission focused on teaching machines to read could genuinely change the world for the better - the more so if it made A.I. a public good,  rather than the property of privileged few.

The World Students Society thanks Professor Gary Marcus of Psychology and Neural Sciences of New York University.

With respectful dedication to the World, Scientists, Students, Professors and Teachers of the world. See ya all ''register'' on : wssciw.blogspot.com - !WOW!, The World Students Society - for every subject in the world and  Twitter-!E-WOW! - the Ecosystem 2011:


'''' Culture & Computers "'

Good Night and God Bless

SAM Daily Times - the Voice of the Voiceless