What is Third Wave eCommerce AI?

We are at an exciting stage in the development of artificial intelligence (AI). In the last decade or so AI has gone from an unknown quantity, only ever spoken of in sci-fi movies and hypotheticals, to becoming a part of daily life. Nowadays, AI helps you to shop, it’s what recommends what songs to listen to, what videos you might like and what people you should connect with on social media. 

As a society we are becoming more comfortable with AI-powered technologies such as facial recognition, advanced driving assistance and voice control. But the advancement in AI technology as a whole is something we are less comfortable with meditating upon. However, if you take a step back and look at the history of AI alongside the latest developments in the field today, the upward trajectory becomes clear.

Historically, development in artificial intelligence has gone through waves of machine intelligence capability. These incremental advancements can be used as a benchmark for the level of AI and its current capabilities. Today, we are ushering in the third wave of eCommerce AI. 

But what does it all mean? What is third wave AI (or even – third wave eCommerce AI) and how does it impact us? To understand this is to understand the evolution of AI. 

The First Wave of AI

First Wave AI was purpose-built to solve particular, highly specific and narrowly defined problems. The intelligence in first wave AI was heavily steeped in logic-based reasoning but lacked any learning capability and came unstuck when presented with uncertainty. Abstraction, perception and learning – key indicators of intelligence – were non-existent.

The chess program that beat Garry Kasparov (a chess grandmaster and former world champion) in 1996, named Deep Blue, is a good example of first wave AI. Deep Blue was designed with one clear purpose – to play chess. It followed algorithms and could process astonishing amounts of information in no time at all. However, getting it to do anything other than play chess would have been simply impossible as it had no knowledge outside of the boundaries of the chessboard. 

Additionally, a system in the first wave of AI was unable to contextualize information based on what was happening in the wider world as it had no capacity for perception. 

The Second Wave of AI

As time passed, advancements in machine learning, the internet and big data allowed AI to be able to recognize, and learn from, patterns using massive datasets. The distinguishing feature of second wave AI has been the application of statistical learning. This wave has been driven by near endless amounts of data, increasingly powerful computer ability and machine learning technologies that allow AI to adapt to increasingly complex situations. 

The second wave beckoned in technologies that mightn’t have been considered impossible before. However, there were still limitations. For example, smart speakers are very good at deciphering speech in perfect conditions but struggle in noisy environments, when the subject’s voice is unclear or, in other words, when used in the real world. Facial recognition works on your phone when looking directly at the camera for a specific amount of time but couldn’t be incorporated into CCTV.

Second wave AI is incredibly proficient at processing large amounts of data and then making predictions based on the data provided. However, second wave AI has limited capacity to generalize or conduct abstract reasoning.  

The Third Wave of AI

The third wave of AI is most closely related to the human brain. Third wave AI embraces reasoning, causality and biologically inspired learning methods. Systems in third wave AI can learn in a way that’s much closer to human thought. 

Whereas second wave systems relied heavily on machines being provided with vast amounts of pre-labelled training data to learn from, third wave AI begins to reduce the requirement of this kind of data ‘feeding’, learning instead from contextual models. For example, third wave AI could take data training on how to recognise faces. It could then be given images of species of animals it has never seen before yet still be able to recognise faces. It might not have seen a certain species of dog before but would know what a face looks like regardless. 

Third wave of AI brings in the ability to understand nuance, reason and use learnings from one area and apply it to another. The third wave involves deep learning and perception AI.

How Third Wave eCommerce AI Impacts Business

The differences between first, second and third wave AI are subtle but substantial. The ushering in of the third wave of AI is playing a leading role in driving innovative solutions and customer experiences in the world of eCommerce. eCommerce AI is being used by online sellers for providing chatbot services, analysing customer comments, and providing personalized services to online shoppers.

Companies, such as WUNDER, use AI to enable entirely new levels of personalization. When a customer is shopping online for hiking boots, third wave AI technologies can decipher data and move a few steps ahead. Before, AI might have been used to make basic, linear recommendations. For example, recommendations could include other types of hiking boots or, moving up a level slightly, other types of hiking equipment. With next generation learning capabilities, today’s artificial intelligence could reason that a person that is browzing hiking boots might be the type of person that enjoys camping, mountaineering or adventure sports. 

This opens up a whole new world of personalization and completely transforms the online browsing experience. In a modern world where customers want to feel special and have a connection with the brand, this level of personalization is very exciting.

For online retailers the third wave of AI is one worth catching!