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Tad Slaff is the founder of Inovance Financial Technologies, the creator of TRAIDE – a strategy creation platform that uses machine learning algorithms to help traders uncover patterns in assets and indicators and build more reliable trading strategies. In this episode, Tad speaks about the state of machine learning in finance today, and touches on how future applications of machine learning and trends may alter what gives an edge to one hedge fund or institutional investor over another.

Machine Learning Not a Crystal Ball, But It Brings Clarity to Investment Decisions

In many ways, AI and finance are made for each other. Machine learning and other techniques make it easier to identify patterns that might otherwise not be detected by the human eye, and finance is quantitative to begin with so that it’s hard not to find traction. Financial firms have also invested heavily in AI in the past, and more are starting to tap into the  financial applications of machine learning (ML) and deep learning. This week, we’re joined by CEO and Co-founder of Kavout&nbsp;Alex Lu, whose company offers AI trading applications for enterprises and individuals. Lu speaks today about the kinds of patterns that traders now have access to in finance, and he gives examples of ways Kavout and other institutions are using artificial intelligence in stock trading to build better and more personalized products and services. &nbsp;

Artificial Intelligence in Stock Trading - Future Trends and Applications

In recent years hedge funds have taken the lead in algorithmic investing - or robo-trading as it’s sometimes called. But there’s no reason the hedge fund world should have all the good stuff. In this episode of the AI Podcast, we speak with Gaurav Chakravorty, co-founder of qplum, a startup that’s working to bring that same machine learning investing approach to the rest of us.

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