Building any AI system is hard, but building a real-time AI brings its own challenges. At Yedup and Clearpool, we built a real-time AI system to simultaneously trade against hundreds of securities by extracting fundamental signals from real-time social media feeds. We’ve gone back to first principals to build out a technology stack from scratch to meet our specific needs.

This talk looks at how we’ve exploited algorithmic architecture to build a real-time AI system that delivers market leading alpha. That’s interesting in itself, but what’s more interesting is looking at some of the challenges that we’ve had to overcome in order to deliver a system that can not only trade hundreds of instruments simultaneously, but that can also correlate the relationships across industries and sectors to extract yet more alpha.

These are issues that would be applicable to any similar class of problems (such as real-time AI) and this talk explores a couple of the key challenges, such as maintaining and recovering with huge amounts of in-flight state to deliver fast, scalable and robust AI systems.