Why AI is going to be crazy big

What is causing the current boom in artificial intelligence, or AI, innovation?

My current thinking is that there are six primary drivers of the current AI wave.

More importantly these drivers are now in a self-reinforcing cycle which will accelerate the pace of AI innovation and its increasing ubiquity in consumer and business apps.

VC funding in pure-play AI startups has increased more than 10-fold since 2010 according to CB Insights. IBM has committed $1bn to Watson, the firm’s AI division. Google has acquired DeepMind and several other AI-oriented startups like. Baidu, Microsoft, Amazon and other tech majors are equally arming up. And startups like Sentient Technologies have amassed war chests.

The six forces

• Moore’s Law
• The Data Explosion
• Internet Collaboration
• Software eating the world
• API’s and Micro-service architecture (!)
• The law of AI Lock-in (!)

The two forces marked with (!) I credit to Dr Barney Pell, founder of natural language search enginer PowerSet, AI expert and friend.

Moore’s Law

Moore’s Law is now positively astronomical, driving availability of faster and cheaper computing.

Data explosion

There is an explosion in the availability and production of data. A large part of this is user generated content from the social networks. But there are new classes of data from health-monitoring and gene exploration. Internet of things will contribute sensor data to this growing volume. More data, means more things for algorithms to train from, more correlations to find and more predictions to make.

New forms of collaboration

Github, arxiv, Kaggle, in fact, the internet in toto, have made information more accessible to scientists, researchers, engineers and hackers.

Internet collaboration has made the cycle of demonstration, knowledge exchange, experimentation and enhancement much shorter.

This allows us to stand on the shoulders of giants faster than ever.

Software is eating the world

In today’s world, most business problems start to look like software problems.

In short, as Marc Andreesen of Andreesen Horowitz has argued, software is eating the world:

More and more major businesses and industries are being run on software and delivered as online services — from movies to agriculture to national defense. Many of the winners are Silicon Valley-style entrepreneurial technology companies that are invading and overturning established industry structures. Over the next 10 years, I expect many more industries to be disrupted by software, with new world-beating Silicon Valley companies doing the disruption in more cases than not.

Pell’s Observation on APIs and Microservices

In my discussions with Barney Pell, he made a crisp point about the nature of the problem domain. Prior to loosely-coupled architectures, of microservices mediated by APIs, software was large and monolithic.

These systems were multi-factor, entangled, spaghetti systems that did many things. They were menhir stacks of code. This meant problems were themselves general, multifactor and ambiguous. This is the sort of problem at which humans excel. AIs don’t.

In today’s loosely coupled architectures, APIs and microservices have constrained the AI problem. Essentially these are well-defined contracts between components. This means a human intelligence has less of an advantage; and it becomes more of a level playing field for an AI.

And this in part explains the boom in AI as a service startups we’re seeing.

Pell’s law of AI lock-in

The second point of discussion which Barney observed is how the business system changes once AI starts to confer an advantage to a given industry participant.

AI systems have become the key to product success in certain classes of products. As soon as AI gets baked in to the the quality of product and its commercial success, the CEO has an ineluctable rationale for investing more in the AI . This creates a lock-in. Competitors need to respond. Because without AI you are nowhere.

Hence the law of AI lock in.

This has happened in several key industries, such as video games and internet search, where you now simply cannot compete unless you have world-class AI. And these is spreading to more sectors: robotics, defence, finance and more.

What now?

We are at the early days of a Cambrian explosion of AI. Many veteran tech watchers might roll their eyes and say ‘not again’. For non-techies, it may be another part of a hype cycle they don’t understand. These six accelerants might explain why its time is now. 

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