EET: How does statistical learning theory relate to artificial intelligence and neural networks?
Patterson: Statistical learning theory is sort of the new AI. It is based on statistics rather than logic.
Back in the 1980s, AI made all these promises based on expert systems and logic that just didn't come true. The idea was that you would write rules that would make a synthetic expert in a narrow area, to look at certain situations and figure out what to do with a given a set of inputs.
The statistics model is that we can look at mountains of data and find a needle that says when you have a statistically significant situation.
By contrast, neural nets seem to be more fragile. A bad input could mess up how a neural net gets trained.
Discover the benefits of scalable backbone and network services for application and cloud providers.
Network automation is gaining momentum. Here's how you can drive this powerful technology to its full potential.
Subsea cable alternatives can provide a level of comfort for those concerned about disruptions. Realistically, they will continue to play a small, but critical role in the short term.
