You might argue the internet has evolved since its inception. Originally a narrowband tool for researchers, it now is a broadband tool used widely by most consumers and businesses. Early on in the development of the World Wide Web, people gained the ability to publish, says Charles Fan, Cheetah Mobile CTO. Then, with the emergence of search, we gained the ability to find the world’s information, he says. The problem is that you have to know what you are looking for, to find it. That makes search less useful.
In the coming wave, content relevant to a consumer will be found and then “pushed” to each user. We already see glimmers of that in the high use of social apps, where people now find “information” useful and relevant to them. Also, “news” is redefined less as what is happening in the broader world, and more what is happening with your friends, family and social circles.
To a large extent, that means we are using an algorithm that essentially assumes “what is interesting to your friends is interesting to you.” That is correct, up to a point. The next wave will involve use of artificial intelligence, coupled with big data stores, to actually predict what you like.
In the next generation of the internet, machine learning will be better than knowing your social graph, as a way of connecting you with things you are interested in. That AI-driven model might also lead to creation of huge new business models to replace existing and older models (advertising, e-commerce or peer trading mechanisms like Uber), says Fan.
For most of us, artificial intelligence (AI) has been a science project for the past few decades: interesting and provocative, but not something that actually affects the businesses most of us deal with on a daily or even annual basis.
There are reasons to believe that is changing. Charles Fan, Cheetah Mobile CTO, said it might seem odd for a mobile app and tools company such as Cheetah Mobile to be seriously evaluating AI. Actually, it turns out to be most practical, as Cheetah Mobile launches new applications in the news aggregation area.
Eventually, the ability to personalize and then predict what a particular person might like will require AI to mine and then predict and deliver “suggested items” to individual people.
Your social profile helps, but only so much. Content providers or advertisers can assume you are somewhat like your “friends” in terms of interests. But only up to a point is that correct. Each individual actually is quite different, at a more-granular level. But it will take AI to rapidly process all the data used to assemble a highly-personalized set of content and then match people with highly-targeted offers and ads.