The Rise of the Thinking Machine

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This year has seen some notable advancements in computer-based brain mimicry, not just on the artificial intelligence (AI) front, but also related to in silico brain simulations. Watson's vanquishing of Jeopardy champions Brad Rutter and Ken Jennings in February set the stage for the year. The now world-famous IBM super exhibited a sophisticated understanding of language semantics along with the ability to integrate that understanding into a complex analytics engine. Since the Jeopardy match, IBM has been looking to take the technology into the commercial realm, most notably in the health care arena. Meanwhile projects like FACETS (Fast Analog Computing with Emergent Transient States) and SpiNNaker are working to uncover the nature of the brain at the level of the neuron.


When AI dominates, what will we do for a crust?

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What does the worldwide head of research at Google tell his kids about how to prepare for the future of work with artificial intelligence? "I tell them … wherever they will be working in 20 years probably doesn't exist now," Peter Norvig says. Be flexible, he says, "and have an ability to learn new things". Future of work experts (yes, it's a thing now) and AI scientists who spoke to Lateline variously described a future in which there were fewer full-time, traditional jobs requiring one skill set; fewer routine administrative tasks; fewer repetitive manual tasks; and more jobs working for and with "thinking" machines. From chief executives to cleaners, "everyone will do their job differently working with machines over the next 20 years," Andrew Charlton, economist and director of AlphaBeta, says.


The Future Of Growth And Economic Development Powered By Human And Artificial Intelligence

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The recent technological advancement within artificial intelligence, the "Internet of Things", and robotics has generated significant impact on traditional businesses, causing decreasing profit margins across several sectors, whereas most of the big winners in the Wall Street IPOs are companies with innovative ideas from Facebook (NASDAQ: FB) and Twitter, (NASDAQ: TWTR) to Snapchat (NYSE: SNAP). There are two common determining factors among those successful IPOs: Ideation and User Generated Content (UGC). In the era of big data and artificial intelligence, we will soon be able to create the tools to better capture the value from ideation and UGC, as well as spur economic growth by capitalizing on human ingenuity. With the ever-accelerating developments in technology, the world is in the process of moving from a consumer economy to a knowledge-based economy, and from a debt- based system to an equity based system, which will include movement from tangible assets to intangible assets. Hence we envision that our world economic system will operate on a new growth formula.


IBM's Watson is getting into ETF business as robot attack on stock market heats up

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Equbot, the Fund's sub-advisor, is a technology-based company focused on applying artificial intelligence to investment analyses. It is part of the IBM Global Entrepreneurs start-up roster. IBM already has a Watson effort for financial services more broadly, which includes a Watson analytical tool for wealth advisors and wealth management groups, and Watson applications for financial markets analysis. The filing says Equbot will use IBM's Watson AI to perform a fundamental analysis of U.S.-listed stocks and real estate investment trusts based on up to 10 years of historical data and then apply that analysis to recent economic and news data. "Each day, the Equbot Model ranks each company based on the probability of the company benefiting from current economic conditions, trends and world events and identifies approximately 30 to 70 companies with the greatest potential for appreciation and their corresponding weights, while maintaining volatility comparable to the broader U.S. equity market."


Wealth management in an era of robots, regulation, and new money

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By redirecting focus, wealth managers can successfully respond to challenges brought on by digital disruption, demographic shifts, and tighter regulation. Wealth managers have seen their fair share of ups and downs in recent years, and while challenges remain, advisers can drive business and growth by paying attention to demographic segmentation, how investors are using technology, and changes in regulation. In this episode of the McKinsey Podcast, Simon London first speaks with PriceMetrix chief customer officer Patrick Kennedy and McKinsey partner Jill Zucker about the North American wealth-management industry; he follows that with a discussion with senior partner Joe Ngai, on the industry in China. Simon London: Welcome to the McKinsey Podcast with me, Simon London. Today, we're going to be talking about financial advice and the people who provide it: financial advisers, or as they're sometimes known, wealth managers. Wealth management is a very big business--and also a business facing a number of challenges, such as new technology, changing demographics, and tighter regulation in a lot of countries. A little later, we're going to be getting a perspective on China. But we're going to start here in North America. For the first part of the conversation, I'm joined on the line by Jill Zucker, a McKinsey partner based in New York, and Patrick Kennedy, who's based in Toronto. Pat is chief customer officer for PriceMetrix, which provides data and analytics to the wealth-management industry.