Gary Marx:  Research and the Future of Artificial Intelligence!

Dear Commons Community,

Gary Marx, professor of psychology and neural science at New York University, had an op-ed piece in yesterday’s New York Times, speculating on the future of artificial intelligence. He questioned whether it is more hype than substance and indicated that it suffers from limited research efforts.  He recommended a new paradigm for conducting A.I. research that would be more on the scale of CERN,  the European Organization for Nuclear Research, with thousands of scientists and billions of dollars of funding. Here is an excerpt:

“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 machine reading, which is a key to building any truly intelligent system. Too many separate components are needed for any one 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 sentences with other sources of knowledge) and inference (reconstructing what is implied but not written). Each of those problems represents a lifetime of work for any single university lab.

Corporate labs 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 research, but it is unlikely to lead to major breakthroughs. Even Google Translate, which pulls off the neat trick of approximating translations by statistically associating sentences across languages, doesn’t understand a word of what it is translating.

I look with envy at my 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 OpenAI, which has about 50 staff members and is sponsored in part by Elon Musk, is tiny by comparison.”

Marx has a good perspective on A.I. but I believe that many large corporations especially those with significant resources such as Google, Apple,  and Facebook will never give up their own interest in developing this technology.  They also will be wary of collaborating with each other because of the competition factor.  It is my sense that one or more of these companies will develop major breakthroughs in A.I. development in the next ten to fifteen years that will have major ramifications – some good and some less good – on many human endeavors, .



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