AI and Machine Learning

Artificial Intelligence (AI) and Robotic Process Automation (RPA) may not be using reason, but they are undeniably effective in cutting costs and improving customer service, and gradually encroaching on ever-more areas of life and work. They also raise profound questions about law, audit, regulation, ethics, the future of employment and especially the standard of living. This is a summary of the first of many Future of Finance discussions about the commercial, economic and social impact of AI.

Artificial intelligence (AI) is not yet what its pioneers imagined or what its detractors fear. At the moment it is no more than a branch of computational statistics, which looks for correlations in large vats of digital data through brute force processing guided by algorithms. That it is producing useful findings and outputs is not in question. Most of the apps we use would not exist without it. But at times it feels as if only Ray Kurzweil is keeping alive the dream of building an artificial mind. So it is refreshing to encounter a data scientist inspired by neuroscience. Francisco Webber, co-founder and CEO of Cortical.io told Dominic Hobson how banks and insurers are using his firm’s technology to read unstructured data such as emails and contracts.

Francesco Corea, Ph.D., is a complexity scientist and tech investor who is mainly focusing on science-driven companies in high-social-impact verticals including

life sciences, energy, and artificial general intelligence. Francesco has a background that ranges from economics and finance to applied machine learning,
and he's been working on a variety of different data problems over the past few years (e.g., sentiment analysis, fraud detection, behavioural science, etc.).
He has worked with AI companies as well as an emerging VC funds and strategic consulting firms. Dr. Corea holds a Ph.D. in Economics.

Artificial Intelligence (AI) and China, an interesting blend of ethics, ambition and world domination.  In February 2018, the FT published an article ‘Why we are in danger of overestimating AI’, arguing that ‘considerably more work is needed before we can reach the long-dreamt-of moment when machine intelligence matches the human variety’. By 2030, just 11 years from now, China intends to lead the world in AI. Is this a realistic ambition, or has China become over-confident in her re-emerged wealth and growing geopolitical muscle?