Showing posts with label AI researcher. Show all posts
Showing posts with label AI researcher. Show all posts

Artificial Intelligence - What Is An AI Winter?

 



The term AI Winter was established during the American Association of Artificial Intelligence's annual conference in 1984.(now the Association for the Advancement of Artificial Intelligence or AAAI).

Marvin Minsky and Roger Schank, two top academics, used the phrase to describe the imminent bust in artificial intelligence research and development at the time.

Daniel Crevier, a Canadian AI researcher, has detailed how fear of an impending AI Winter caused a domino effect that started with skepticism in the AI research community, spread to the media, and eventually resulted in negative funding responses.

As a consequence, real AI research and development came to a halt.

The initial skepticism may now be ascribed mostly to the excessively optimistic promises made at the time, with AI's real outcomes being significantly less than expected.

Other reasons, such as a lack of computer capacity during the early days of AI research, led to the belief that an AI Winter was approaching.

This was especially true in the case of neural network research, which required a large amount of processing power.

Economic reasons, however, limited attention on more concrete investments, especially during overlapping times of economic crises.

AI Winters have occurred many times during the history of AI, with two of the most notable eras covering 1974 to 1980 and 1987 to 1993.

Although the dates of AI Winters are debatable and dependent on the source, times with overlapping patterns are associated with research abandonment and defunding.

The development of AI systems and technologies has progressed, similar to the hype and ultimate collapse of breakthrough technologies such as nanotechnology.

Not only has there been an unprecedented amount of money for basic research, but there has also been exceptional progress in the development of machine learning during the present boom time.

The reasons for the investment surge vary depending on the many stakeholders involved in artificial intelligence research and development.

For example, industry has staked a lot of money on the idea that discoveries in AI would result in dividends by changing whole market sectors.

Governmental agencies, such as the military, invest in AI research to improve the efficiency of both defensive and offensive technology and to protect troops from imminent damage.

Because AI Winters are triggered by a perceived lack of trust in what AI can provide, the present buzz around AI and its promises has sparked fears of another AI Winter.

On the other hand, others argue that current technology developments in applied AI research have secured future progress in this field.

This argument contrasts sharply with the so-called "pipeline issue," which claims that a lack of basic AI research will result in a limited number of applied outcomes.

One of the major elements of prior AI Winters has been the pipeline issue.

However, if the counterargument is accurate, a feedback loop between applied breakthroughs and basic research will generate enough pressure to keep the pipeline moving forward.


~ Jai Krishna Ponnappan

You may also want to read more about Artificial Intelligence here.



See also: Minsky, Marvin.

Further Reading

Crevier, Daniel. 1993. AI: The Tumultuous Search for Artificial Intelligence. New York: Basic Books.

Kurzweil, Ray. 2005. The Singularity Is Near: When Humans Transcend Biology. New York: Viking.

Muehlhauser, Luke. 2016. “What Should We Learn from Past AI Forecasts?” https://www.openphilanthropy.org/focus/global-catastrophic-risks/potential-risks-advanced-artificial-intelligence/what-should-we-learn-past-ai-forecasts.


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