Ross Pamphilon is a founding member of ECM Asset Management Ltd’s investment team and currently serves as its Chief Investment Officer and Chief Executive Officer. With over 20 years of experience in trading and portfolio and risk management, including 17 years overseeing or investing in sub-investment grade securities, Ross Pamphilon has directed the firm’s investment process for nearly two decades.
Prior to joining ECM back in 1999, Ross Pamphilon was an emerging markets specialist at Merrill Lynch in London and New York. During his time at Merrill Lynch, Ross was responsible for trading local currency fixed income debt and derivative and foreign exchange products. Throughout his career at ECM, Ross Pamphilon has been responsible for a range of businesses including emerging markets, investment grade corporate debt, high yield, long-short relative value strategies and front office IT before assuming overall responsibility for portfolio management and credit research.
Apart from his career, Ross Pamphilon takes great interest in Artificial Intelligence. At a young age, Ross’ curiosity surrounding the industry was very much apparent. Often times, Ross found himself programming on the ZX Spectrum and dreaming of the point in time when machines would finally outsmart human beings. More notably, Ross recalls the thrill he experienced when IBM’s Deep Blue defeated legendary world chess champion, Garry Kasparov, back in 1997.
More specifically Ross Pamphilon finds machine learning a rather fascinating subfield of artificial intelligence.
“We come across this almost every day, for example, online marketing profiling algorithms that look to profile you based on statistical factors (age, sex, location etc) and the type of searches and products that you’ve purchased previously. Making predictions from a small sample of data which have statistical regularities makes the task of building a model significantly easier. However, in the real world we often have to deal with vast amounts of data which creates a lot of noise and uncertainty. To move towards true artificial intelligence as opposed to simple learning algorithms what if it’s possible to harness the power of the internet? A learning algorithm focusing on the internet would have access to almost unlimited information, images, language and cultural references. Furthermore, the web based database is growing on a daily basis and it is fascinating to think about how powerful learning algorithms might be able to use this information in developing their own artificial intelligence.”
Ross Pamphilon looks forward to the point in human history where artificially intelligent machines surpass human biological intelligence. And though that may still be some years off, once we reach that point it seems likely that super intelligent AI will quickly follow.