Whats AI, and whats not

Artificial intelligence has become as meaningless a description of technology as all natural is when it refers to fresh eggs. At least, thats the conclusion reached by Devin Coldewey, a Tech Crunch contributor.

AI is also often mentioned as a potential cybersecurity technology. At the recent RSA conference in San Francisco, RSA CTO Zulfikar Ramzan advised potential users to consider AI-based solutions carefully, in particular machine learning-based solutions, according to an article on CIO.

AI-based tools are not as new or productive as some vendors claim, he cautioned, explaining that machine learning-based cybersecurity has been available for over a decade via spam filters, antivirus software and online fraud detection systems. Plus, such tools suffer from marketing hype, he added.

Even so, AI tools can still benefit those with cybersecurity challenges, according to the article, which noted that IBM had announced its Watson supercomputer can now also help organizations enhance their cybersecurity defenses.

AI has become a popular buzzword, he said, precisely because its so poorly defined. Marketers use it to create an impression of competence and to more easily promote intelligent capabilities as trends change.

The popularity of the AI buzzword, however, has to do at least partly with the conflation of neural networks with artificial intelligence, he said. Without getting too into the weeds, the two are not interchangeable -- but marketers treat them as if they are.

AI vs. neural networks

By using the human brain and large digital databases as metaphors, developers have been able to show ways AI has at least mimicked, if not substituted for, human cognition.

The neural networks we hear so much about these days are a novel way of processing large sets of data by teasing out patterns in that data through repeated, structured mathematical analysis, Coldeway wrote.

The method is inspired by the way the brain processes data, so in a way the term artificial intelligence is apropos -- but in another, more important way its misleading, he added. While these pieces of software are interesting, versatile and use human thought processes as inspiration in their creation, theyre not intelligent.

AI analyst Maureen Caudill, meanwhile, described artificial neural networks (ANNs) as algorithms or actual hardware loosely modeled after the structure of the mammalian cerebral cortex but on much smaller scales.

A large neural network might have hundreds or thousands of processor units, whereas a brain has billions of neurons.

Caudill, the author of Naturally Intelligent Systems, said that while researchers have generally not been concerned with whether their ANNs resemble actual neurological systems, they have built systems that have accurately simulated the function of the retina and modeled the eye rather well.

So what is AI?

There about as many definitions of AI as researchers developing the technology.

The late MIT professor Marvin Minsky, often called the father of artificial intelligence, defined AI as the science of making machines do those things that would be considered intelligent if they were done by people.

Infosys CEO Vishal Sikka sums up AI as any activity that used to only be done via human intelligence that now can be executed by a computer, including speech recognition, machine learning and natural language processing.

When someone talks about AI, or machine learning, or deep convolutional networks, what theyre really talking about is a lot of carefully manicured math, Coldewey recently wrote.

In fact, he said, the cost of a bit of fancy supercomputing is mainly what stands in the way of using AI in devices like phones or sensors that now boast comparatively little brain power.

If the cost could be cut by a couple orders of magnitude, he said, AI would be unfettered from its banks of parallel processors and free to inhabit practically any device.

The federal government sketched out its own definition of AI last October. In a paper on Preparing for the future of AI, the National Science and Technology Councilsurveyed the current state of AI and its existing and potential applications.

The panel reported progress made on narrow AI," which addresses single-task applications, including playing strategic games, language translation, self-driving vehicles and image recognition.

Narrow AI now underpins many commercial services such as trip planning, shopper recommendation systems, and ad targeting, according to the paper.

The opposite end of the spectrum, sometimes called artificial general intelligence (AGI), refers to a future AI system that exhibits apparently intelligent behavior at least as advanced as a person across the full range of cognitive tasks. NSTC said those capabilities will not be achieved for a decade or more.

In the meantime, the panel recommended the federal government explore ways for agencies to apply AI to their missions by creating organizations to support high-risk, high-reward AI research. Models for such an organization include the Defense Advanced Research Projects Agency and what the Department of Education Department has done with its proposal to create an ARPA-ED, which was designed to support research on whether AI could help significantly improve student learning.

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What's AI, and what's not - GCN.com