Personal
What will AI make possible that's impossible today?
Hearing that Bob Dylan just won the Nobel Prize for Literature, how could I not begin this talk with his famous line, "Something is happening here, but you don't know what it is, do you, Mr. Jones?" The future is full of amazing things. On my way here, I spoke out loud to a $200 device in my kitchen, and asked it to call a Lyft to take me to the airport. And in a few years, that car might well be driving itself. Someone seeing this for the first time would have every excuse to say "WTF?"
NEW BUZZ about the 6 p.m. MSNBC slot -- 14-0 vote against Israel; Trump vows CHANGE -- ASSANGE on Trump -- WEEKEND READS -- ROB SALITERMAN engaged -- B'DAY: Dan Pfeiffer
REVOLVING DOOR -- "Trump appoints his business attorney to manage international negotiations," by CNN's Elise Labott and Teddy Schleifer: "Jason Greenblatt, the executive vice president and chief legal officer for Trump's business empire, will take on the title of special representative for international negotiations. A source familiar with the appointment told CNN that Greenblatt will primarily will be working on Israel-Palestinian peace process, the American relationship with Cuba and trade agreements."
'So much more convenient to have sex with a robot'
French woman Lilly wants to marry her robot. Only her partner is 3D printed robot named Inmmovator who she designed herself, after realising she was attracted to "humanoid robots generally" rather than other people. "I'm really and totally happy," she told news.com.au "Our relationship will get better and better as technology evolves." The "proud robosexual" said she always loved the voices of robots as a child but realised at 19 she was sexually attracted to them as well.
NOBEL ECONOMIST: 'I don't think globalisation is anywhere near the threat that robots are'
A Nobel Prize-winning economist has warned that the rise in robotics and automation could destroy millions of jobs across the world. Angus Deaton, who won the Nobel Prize last year for his work on health, wealth, and inequality, told the Financial Times he believes robots are a much greater threat to employment in the US than globalisation. Addressing the theory that Donald Trump's victory in the US presidential elections was fueled by a backlash against globalisation, Deaton told the FT: "Globalisation for me seems to be not first-order harm and I find it very hard not to think about the billion people who have been dragged out of poverty as a result. I don't think that globalisation is anywhere near the threat that robots are." He added: "It's hard to think that Mark Zuckerberg is actually impoverishing anyone by getting rich with Facebook. But driverless cars are another matter entirely."
Global Bigdata Conference
I'm the Chief Data Officer at VideoAmp, a startup focused on cross-screen advertising. I led the team to build a data platform on Apache Spark that handles over 300,000 requests per second, and machine learning pipelines that process close to a petabyte of data. Previously, I was the Chief Data Scientist for Pasadena Labs, a machine learning startup for online marketing. I got my PhD in Machine Learning from California Institute of Technology (Caltech), where I focused on Deep Learning and Behavioral economics.
How DBS Bank Became The Best Digital Bank In The World By Becoming Invisible
Every year, financial services magazine Euromoney gives out numerous awards for excellence to firms in many categories, at country, regional, and global levels. The story of its digital transformation is all the more remarkable because one of its goals for its technology โ in fact, for the entire bank โ is to disappear from view. DBS is a midsized Asian bank with about 22,000 employees, created by the Government of Singapore in 1968 to help modernize the island nation. However, when DBS brought in Paul Cobban, who is now Chief Operating Officer, Technology and Operations for DBS, to spearhead the bank's transformation in 2009, they were far from best โ in fact, they were among the worst. Cobban recalls an eye-opening story from his first day at the bank. "I was in a taxi and I mentioned I worked at DBS," Cobban recalls.
Interview: Amazon CTO Werner Vogels on AI services and experimentation
Ten years after its U.S. launch, Amazon Web Services (AWS) opened its first Canadian datacentre, located in Montreal, at the beginning of December to much fanfare. In this video interview (two more interviews, on cloud security and the democratization of IT, can be seen here and here), ITWC CIO Jim Love and Amazon.com CTO Werner Vogels discuss AI services and experimentation (hint: they have little, if anything, to do with Hollywood AI) during the company's Dec. 8 AWS Canada (Central) launch event in Toronto. The new Canada Region is currently available for multiple services, including Amazon Elastic Compute Cloud (Amazon EC2), Amazon Simple Storage Service (Amazon S3), and Amazon Relational Database Service (Amazon RDS). Regions are Amazon Web Services' way of describing its own data centre model.
Big Data and The Great A.I. Awakening. Interview with Steve Lohr
My last interview for this year is with Steve Lohr. Steve Lohr has covered technology, business, and economics for the New York Times for more than twenty years. In 2013 he was part of the team awarded the Pulitzer Prize for Explanatory Reporting. We discussed Big Data and how it influences the new Artificial Intelligence awakening. Steve Lohr: Both Google and Microsoft are contributing their tools to expand and enlarge the AI community, which is good for the world and good for their businesses.
Bayesian Basics, Explained
Editor's note: The following is an interview with Columbia University Professor Andrew Gelman conducted by Marketing scientist Kevin Gray, in which Gelman spells out the ABCs of Bayesian statistics. Andrew Gelman: Bayesian statistics uses the mathematical rules of probability to combines data with "prior information" to give inferences which (if the model being used is correct) are more precise than would be obtained by either source of information alone. Classical statistical methods avoid prior distributions. In classical statistics, you might include in your model a predictor (for example), or you might exclude it, or you might pool it as part of some larger set of predictors in order to get a more stable estimate. These are pretty much your only choices.