"investing" entries
Roger Chen on hardware and robotics startups
The O’Reilly Hardware Podcast: Hardware from the venture capitalist’s point of view.
Subscribe to the O’Reilly Hardware Podcast for insight and analysis about the Internet of Things and the worlds of hardware, software, and manufacturing.
In this new episode of the Hardware Podcast, David Cranor and I talk with Roger Chen, formerly a principal at O’Reilly AlphaTech Ventures, O’Reilly Media’s sister VC firm.
Discussion points:
- Chen’s perspective as an investor on companies that are creating 3D robotics, drones, and satellites
- The Maker movement’s impact on the hardware startups
- Etsy’s influence on the new hardware movement
- Trends in robotics, and the outlook for robotics startups
Is 2016 the year you let robots manage your money?
The O’Reilly Data Show podcast: Vasant Dhar on the race to build “big data machines” in financial investing.
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In this episode of the O’Reilly Data Show, I sat down with Vasant Dhar, a professor at the Stern School of Business and Center for Data Science at NYU, founder of SCT Capital Management, and editor-in-chief of the Big Data Journal (full disclosure: I’m a member of the editorial board). We talked about the early days of AI and data mining, and recent applications of data science to financial investing and other domains.
Dhar’s first steps in applying machine learning to finance
I joke with people, I say, ‘When I first started looking at finance, the only thing I knew was that prices go up and down.’ It was only when I actually went to Morgan Stanley and took time off from academia that I learned about finance and financial markets. … What I really did in that initial experiment is I took all the trades, I appended them with information about the state of the market at the time, and then I cranked it through a genetic algorithm and a tree induction algorithm. … When I took it to the meeting, it generated a lot of really interesting discussion. … Of course, it took several months before we actually finally found the reasons for why I was observing what I was observing.
The race to build ‘‘big data machines’’ in financial investing
Robot wealth managers and approaches will grow and offer alternative ways of investing.
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Editor’s note: This post originally published in Big Data at Mary Ann Liebert, Inc., Publishers, in Volume 3, Issue 2, on June 18, 2015, under the title “Should You Trust Your Money to a Robot?” It is republished here with permission.
Financial markets emanate massive amounts of data from which machines can, in principle, learn to invest with minimal initial guidance from humans. I contrast human and machine strengths and weaknesses in making investment decisions. The analysis reveals areas in the investment landscape where machines are already very active and those where machines are likely to make significant inroads in the next few years.
Computers are making more and more decisions for us, and increasingly so in areas that require human judgment. Driverless cars, which seemed like science fiction until recently, are expected to become common in the next 10 years. There is a palpable increase in machine intelligence across the touchpoints of our lives, driven by the proliferation of data feeding into intelligent algorithms capable of learning useful patterns and acting on them. We are living through one of the greatest revolutions in our lifestyles, in which computers are increasingly engaged in our lives and decision-making, to a degree that it has become second nature. Recommendations on Amazon or auto-suggestions on Google are now so routine, we find it strange to encounter interfaces that don’t anticipate what we want. The intelligence revolution is well under way, with or without our conscious approval or consent. We are entering the era of intelligence as a service, with access to building blocks for building powerful new applications. Read more…