Bill Gates says that the company that cracks the Third Wave of AI will be worth 10 Microsofts. But what is this ‘Third Wave’, anyway?

AI isn’t as newfangled as we’d like to think, and over the years upgrades in existing hardware and techniques have periodically energized interest and development in the field, similar to the jumps in VR technology. Our progress in the AI field is significantly greater than where it was even just ten years ago. When we talk about ‘waves’, we’re talking about these jumps.

First Wave AI

Traditional, First Wave AI was purpose-built to solve particular and often niche problems. They were lovingly handcrafted and trained to think in a certain way, and were what John Haugeland (philosopher and cognitive scientist) called ‘Good, Old-Fashioned Artificial Intelligence’ (GOFAI). Deep Blue, the chess program that beat Garry Kasparov in 1996, is a good example of this. The program was designed with one clear purpose in mind, and getting it to do anything other than play chess would have been simply impossible as it had no knowledge beyond that of the game itself.

Later on, machine learning, the internet and massive leaps in available processing power allowed us to train AIs to be able to recognise and learn from patterns using massive datasets. This is how neural nets figure out how to recognise faces, or how DeepMind’s AlphaStar is now a Starcraft master that can beat the pros. Neural nets have even helped build programs which can now solve CAPCHAs by comparing patterns in the words to images stored on its neural network.

Second Wave AI

This Second Wave of AI proved to be in order of magnitudes more powerful than its predecessors.

But modern AI lacks that sci-fi quality of being able to think like a human. We’re still decades, or perhaps centuries, off from building a CP-30 (or more likely a depressed Marvin). Our programs find it hard to think outside the box or process natural language without getting confused by our pitch, cadence, or choice of words.

In order to break this ceiling, experts suggest the entire field needs to be scrapped and rebuilt on different principles.

The Third Wave of AI

This is the Third Wave of AI that Bill Gates was speaking of. Whoever builds an AI capable of reasoning like a human, of learning without being told what to learn, that can take data-training on how to recognise faces and use it to recognise all sorts of visual schema without being shown how.

But it is worth asking: is it even possible to build an AI capable of reasoning like a human? Is true artificial intelligence, the likes of which we think of when we think about the Third Wave, logically capable of happening? Perhaps the most well-known yet controversial opinion on the matter comes from the philosopher John Searle, who wrote the paper “Can Computers Think?” He believed that the one barrier which separates natural life from that which is programmed is its inability to look past the syntax and towards the semantics.

Take language for example. When a human hears the word “help” they not only understand the definition or syntax of it (to offer one’s services to aid another), but they also understand what it means to be in a situation where a person needs to physically ask for help. They understand what “help” feels like; this is the semantics of the term. An AI may hear the word “help” and know the definition/syntax of it, and they may even know how they should help somebody out, but they can never grasp the semantics of knowing what help actually feels like.

Searle’s conclusion was that the artificial intelligence of which Bill Gates speaks of (this Third Wave) is not possible, but bear in mind that his views were crafted in 1980, a time when AI was in its infancy. The developments we have currently seen in the field are likely more impressive than Searle imagined at the time of his paper, even if we are not within the Third Wave just yet.

For instance, Google’s BERT project recently forwarded the sub-field of Natural Language Processing by proving that computers which bidirectionally learn can gain an understanding of texts on a level which was only previously hoped. Even if a computer can never grasp the semantics of something, it is certainly possible that grasping the full depth of its syntax would provide only a fractional difference and even bridge the gap between the two.

And if there’s anything computers are great at, it’s grasping syntax; in the future they may even be better at it than us. They might never need semantics to reason like a human, they might even figure out how to do it independently.

This is why the people who will take us to the Third Wave will be worth 10 Microsofts. They’ll be creating something so complex and capable that we may even need to consider it as a life independent of us. They’ll be building AI which will be able to do what humans do.

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