US data firm Remark is looking to collate all the major social network’s data into one platform. This would include data from the likes of Facebook, Baidu, Twitter, Instagram, Alibaba, Tencent and Sina Weibo. Remark is currently working alongside some of China’s biggest names in the world of AI and fintech.
“What we’re working on together serves both sides with two purposes,” explains Jason Wei, Remark’s CTO. “One is to marry the data from both sides into useful models.” While AI is most notably seen making business decisions in the marketing industry, it’s also used across other industries too. Wei also explained that one of the reasons Remark works alongside Alibaba is because it has the best online retail data. But, that’s just one small piece of the puzzle. In order to create a full picture the company still has to connect a person’s social behaviour and offline consumer insights. And that’s where it’s partnerships with brands such as Aston Martin, Uniqlo, and H&M come in.
Variety is very important when it comes to training AI. It’s not enough just to have a lot of data. “The reason why Alibaba and Tencent both invited us is the data that we have. Now when we take our data and join it with theor data we have over 11 or 12,000 different data points on how we can identify a person’s behavioral history,” said Tao. Remark is big on social credit rating – that is making a decision about your ability to pay a loan based on what you share or like, what you buy, and who your friends are. In China, this kind of data is often used to decide creditworthiness as only 25% of the population have any kind of credit history.
Previously because of the risk to financial institutions in scoring people this way, they typically offered high rates of interest. But, since the government stepped in to help regulate the industry, rates have fallen significantly. And as a result fintech companies are now looking to lower their risk when offering people credit. That’s where Remark’s plethora of data come sin very useful.
AI is advancing at a phenomenal rate, but it still very much relies on humans to operate effectively. “The AI will start human experience and will be limited to human experience or what you call bias – it depends on what kind of samples you feed the AI,” said Wei. “Since the human is part of the training process the bias is not going to be avoidable. That’s why machine learning will lead us to the next generation of AI in which we believe we will take humans out of the process.”