"At the most rudimentary level, AI involves teaching machines to learn and to interact in order to undertake cognitive tasks that were usually performed by humans. The type of AI featured in sci-fi films in which machines possess a human-like intelligence, sometimes referred to as general artificial intelligence, remains a distant and elusive prospect. The most optimistic experts, such as Google’s director of engineering, Ray Kurzweil, predict that AI will be able to outsmart humans by 2029. Conservative predictions expect this to take at least 100 years, if at all..."
"Not that long ago, it looked like it was game over for the field of study that produced the mortgage backed security, the credit default swap and all manner of other exotic derivatives that exploded so spectacularly in the financial crisis of 2008.
"Now, financial engineering theory is being touted by several academics as the key to curing cancer faster, reducing the impact of climate change and imposing better risk discipline on the same banks that were once almost felled by the discipline’s creations..."
On this episode of the HBO documentary series, Andrew Lo discusses an idea he and colleagues developed with regard to the FDA approval process. They've developed a model that incorporates patient preferences into the design of clinical trials in order to set appropriate thresholds for FDA approval.
At a conference last year, I was approached by an audience member after my talk. He thanked me for my observation that it’s unrealistic to expect investors to do nothing in the face of a sharp market-wide selloff, and that pulling out of the market can sometimes be the right thing to do. In fact, this savvy attendee converted all of his equity holdings to cash by the end of October 2008. He then asked me for some advice: “Is it safe to get back in now?” Seven years after he moved his money into cash, he’s still waiting for just the right time to reinvest; meanwhile, the S&P 500 earned an annualized return of 14% during this period. Investing is an emotional process. Managing these emotions is probably the greatest open challenge of financial technology. Investing is much more complicated than other chores like driving, which is why driverless cars are already more successful than even the best robo advisers.
"Does evolutionary biology offer better insight into today’s markets than the immutable laws of physics? Andrew Lo, director of the Laboratory for Financial Engineering at the Massachusetts Institute of Technology, thinks so..."
"Hazte a un lado, Janet Yellen, la automatización del lugar de trabajo está a punto de volverse personal. Imagínese si en vez de confiar en la presidenta de la Reserva Federal (Fed) se usara una computadora para transformar montañas de datos económicos en bruto en proyecciones fidedignas de desempleo, inflación y producto interno bruto. ¿Cuál es el mejor nivel para la tasa de fondos federales? Presione..."
"Move over Janet Yellen, automation in the workplace is about to get personal.
"Instead of relying on the Federal Reserve chair, imagine using a computer to transform mountains of raw economic data into reliable predictions for unemployment, inflation and gross domestic product. What’s the best level for the federal funds rate? Press .
“'The capability is here,' says Andrew Lo, director of the Laboratory for Financial Engineering at the Massachusetts Institute of Technology, near Boston. 'The biggest hurdle is the cultural barrier. You’ve got a lot of central bankers who are not as open to technology.'"
"Uncertainty around how long it will take to find a cure for different forms of cancer is forcing investors to reconsider pumping hundreds of millions of dollars into pharmaceuticals.
"But offering long-term debt rather than venture capital can help draw them back, according to Andrew Lo, Professor of Finance at the MIT Sloan School of Management. He was speaking at the Financial Innovations in Healthcare conference, held at London Business School (LBS) and supported by the AQR Asset Management Institute."
"With the advent of social media, there has been an explosion of interest in how information shared online can be used to profit in the stock market.
"Twitter, the social media monster that allows users to share their thoughts on anything–as long as those thoughts are 140 characters or less–is emerging as a favorite dataset for financial researchers..."
"On the 15th March 2016, an artificially intelligent (AI) software programme called AlphaGo, defeated the world champion of an ancient board game called Go. The game is immensely complex, with a total combination of possible moves numbering several hundred orders of magnitude more than the number of atoms in the universe. Winning the series four-to-one, AlphaGo’s victory was emphatic. It also showcased significant advances in AI’s ability to recognise obscure patterns, learn new ones and adapt strategies to changing circumstances.
"Yet, just two weeks after AlphaGo’s impressive victory, a new chatbot called Tay, exposed a darker side to AI. Designed to engage in friendly conversation with people online and assist them with Microsoft services, Tay’s unique design feature was that “she” learns from her online interactions. Upon Tay’s public release a coordinated barrage of abuse and incessant trolling by Twitter users, taught Tay the wrong lessons. The programme was corrupted into spewing racist, sexist and xenophobic comments, revealing the potential for flaws in the design and programming of AI, as well as the uneasy interaction between artificial intelligence and the natural kind..."