Quantum Physicist Brian Cox provided the keynote at BBH’s 2017 London Symposium Making the Quantum Leap. Physicists, like asset managers and other roles in financial services, deal with massive amounts of data and rely on the combination of human efforts and technology to gather, track, organize, and analyze it all.
Q: How are you using Robotics Process Automation and Artificial Intelligence to sort through enormous amounts of data?
Particle physics is partly, at least, pattern recognition. And you find that computers you can teach to recognize patterns so they can find their own patterns, so they're useful in that respect. So, there's an element of that, although actually, in particle physics analysis the real element is mainly post docs and PHD students writing code. So, it's important, I think, that what we've found throughout science actually is that computers are very good at searching for very predictable patterns or to teach themselves to look for patterns - they can do it very quickly. But when you're looking for something in science, you don't know what it is that you're looking for, necessarily. So, you could be looking for the Higgs particle and we knew how we expected that to behave. But we didn't know whether that was the way that nature chose to operate, if that's the right way to say it. We didn't know whether our theories were correct, so a lot, and we don't know whether we're looking for something that the theory has not yet predicted. So, there could be things in the data that we don't expect and we have no knowledge of and no prediction of, so in that case in tends to be that you need humans very much to exercise their ingenuity and to check and to look for the unexpected. And I think, although I'm not an expert in Artificial Intelligence but I think most people I talk to would say that when you're talking about the unexpected, whether it's humans going to Mars to study the surface of the planet and look for life, or whether it's looking for interesting patterns in particle physics data, then humans are still significantly better than computers.
Brown Brothers Harriman (“BBH”) is not affiliated with and does not endorse the views of any third party contributors that appear in this video. The positions expressed in this material are those of the author as of 6 July 2017 and may or may not be consistent with the views of Brown Brothers Harriman & Co. and its subsidiaries and affiliates (“BBH”), and are intended for informational purposes only. Information contained herein is based upon various sources believed to be reliable and subject to change without notice. This material should not be construed as research or as investment, legal or tax advice, nor should it be considered information sufficient upon which to base an investment decision.
BBH is not affiliated with Brian Cox. IS-2017-07-12-3061