The 4 Waves of AI — And why they matter
I can’t open a newspaper or visit my friendly local bookstore without coming across a think piece about why AI is a *BIG DEAL* and how it changes everything. The tone of most of the material that I have come across is aptly summed up in this classic xkcd panel.
In January 2019, I read Kai-Fu Lee’s fantastic book “AI Super-Powers: China, Silicon Valley, and The New World Order.” Mr. Lee is a thoughtful, even-handed guide to what is going on in the field of Artificial Intelligence (specifically Machine Learning) and how it may impact our future. The book is also an eye-opening account of the Chinese startup eco-system — but perhaps more on that another day.
Early in the book, Mr. Lee talks about how the spread of AI is happening in four waves. These waves are:
- Internet AI
- Business AI
- Perception AI
- Autonomous AI
Let’s take quick a look at each of these waves.
We deal with Internet AI every time we shop online, scroll through our social media feeds or Google something. From AI Superpowers:
Internet AI is mainly about using AI algorithms as recommendation engines: systems that learn our personal preferences and then serve up content hand-picked for us.
Examples of Internet AI include online advertising optimization, personalized news feeds, and algorithmic content recommendation.
Advances in machine learning have allowed businesses to take advantage of labeled, structured data that resides in data repositories and train algorithms to outperform humans on clearly defined optimization tasks. Some examples here include automated credit scoring, fraud detection, algorithmic trading, and supply chain optimization. While not the most exciting topic, in the short term, Business AI has the potential to have a significant impact in the way we work and more potently, what *types of work* make sense to automate.
Business AI is about optimising and generating value from structured data.
Business AI has the potential to make what were once stable professions like accountancy, insurance, and medicine obsolete in their current form. It also has the potential to generate vast and lucrative new opportunities. More on this later.
Perception AI is about the “Digitisation of the physical world.” It is about using real-world data captured from IoT devices, cameras, smartphones, and other devices to blur the lines between the online and offline worlds. We already see applications of facial recognition and machine translation technology enhance offline experiences such as shopping and travel as well as enrich experiences such as education.
Perception AI is about blurring the lines between the online and offline world
Augmented reality (AR) devices and applications increase merging of the offline and online world. Perception AI also has worrying implications around surveillance, privacy and data protection.
Autonomous AI represents the culmination of the three preceding waves of AI. What was once science fiction is slowly becoming mundane. Autonomous AI is about fusing the ability to optimize from extremely complex datasets and integrate them with powerful sensory abilities resulting in machines that can understand and shape the world around them.
Autonomous AI results in machines that can understand and shape the world around them.
We already see some limited applications of Autonomous AI in the fields of self-driving cars, automated factories and pollinators.
What does it all mean?
“Tech is building different kinds of businesses, and so will take different shares of that opportunity, but more importantly change what those industries look like.“
He says further that a combination of high internet penetration, changing consumer expectations and a general “unbundling” of supply chains are creating business models that in turn are enabled and accelerated by AI. The breaking apart of tightly coupled logistics supply chains is just one example of this phenomenon.
At my work with Jeavio’s portfolio companies, I can already see this in action. We support entrepreneurs who are working in diverse fields such as customer experience analytics, construction and high tech agriculture. In each of these various fields, we see applications of Business AI that have the potential to disrupt existing models and generate tremendous value.
In my previous career working in high-frequency algorithmic trading, I have seen technology disrupt financial markets. Advances in AI are now doing the same in a wide variety of fields.
While AI cannot by itself generate new business models, it is already a potent force multiplier, which when deployed effectively, can increase efficiency and help businesses capture more value. We may not worry about our Robot Overlords just yet; we should keep an eye on the disruption and opportunities presented by the four waves of AI.