Astro Teller has an unusual way of starting a new project: He tries to kill it. Teller is the head of X, formerly Google X, the advanced technology lab of Alphabet. At X's headquarters not far from the Googleplex in Mountain View, Calif., Teller leads a group of engineers, inventors, and designers devoted to futuristic "moonshot" projects like self-driving cars, delivery drones, and Internet-beaming balloons. To turn their wild ideas into reality, Teller and his team have developed a unique approach. It starts with trying to prove that whatever it is that you're trying to do can't be done--in other words, trying to kill your own idea. As Teller explains, "Instead of saying, 'What's most fun to do about this or what's easiest to do first?' we say, 'What is the most likely reason this project won't make it?' The ideas that survive get additional rounds of scrutiny, and only a tiny fraction eventually becomes official projects; the proposals that are found to have an Achilles' heel are ...

With AI becoming integral to nearly every industry, it's no surprise that banking is increasingly automated. Chatbots like BankBot and Nao are slowly taking us one step further than digital banking, but there are still privacy risks that come with feeding both banks and their bots more information. BankBot is an app prototype designed by the Polish digital design and communication agency K2. BankBot itself is a robotic bank teller, financial advisor, and personal assistant all in one. The automated sidekick provides a conversational text-based interface, but users can also use their voices instead of typing.

The United Nations forecasts that the global population will rise from 7.3 billion to nearly 10 billion by 2050, a big number that often prompts warnings about overpopulation. Some have come from neo-Malthusians, who fear that population growth will outstrip the food supply, leaving a hungry planet. Others appear in the tirades of anti-immigrant populists, invoking the specter of a rising tide of humanity as cause to slam borders shut. Still others inspire a chorus of neo-Luddites, who fear that the "rise of the robots" is rapidly making human workers obsolete, a threat all the more alarming if the human population is exploding. They may be the one thing that can protect the global economy from the dangers that lie ahead.

JPL and National Cancer Institute Renew Big Data Partnership Every day, NASA spacecraft beam down hundreds of petabytes of data, all of which has to be codified, stored and distributed to scientists across the globe. Increasingly, artificial intelligence is helping to "read" this data as well, highlighting similarities between datasets that scientists might miss. For the past 15 years, the big data techniques pioneered by NASA's Jet Propulsion Laboratory in Pasadena, California, have been revolutionizing biomedical research. On Sept. 6, 2016, JPL and the National Cancer Institute (NCI), part of the National Institutes of Health, renewed a research partnership through 2021, extending the development of data science that originated in space exploration and is now supporting new cancer discoveries. The NCI-supported Early Detection Research Network (EDRN) is a consortium of biomedical investigators who share anonymized data on cancer biomarkers, chemical or genetic signatures related to specific cancers.

This is the 2-part blog version of a talk I've given at DOAG Conference this week. I've also uploaded the slides (no ppt; just pretty R presentation;-)) to the articles section, but if you'd like a little text I'm encouraging you to read on. That is, if you're in the target group for this post/talk. For this post, let me assume you're a SQL girl (or guy). With SQL you're comfortable (an expert, probably), you know how to get and manipulate your data, no nesting of subselects has you scared;-).

"When my father was misdiagnosed and administered the wrong medication placing him in a coma nearly 20 years ago, I saw firsthand the need for technology to help physicians make accurate decisions," said Tanveer Syeda-Mahmood, IBM Fellow and Chief Scientist of the Medical Sieve Radiology Grand Challenge Project at IBM Research – Almaden in San Jose, Calif. This week in Chicago, Dr. Syeda-Mahmood's mission meets the real world as IBM Research debuts a new Watson-powered demo that shows the future of Artificial Intelligence (AI) in radiology. The demo is the result of a shared vision by Dr. Syeda-Mahmood and Dr. Eugene Walach from IBM Research – Haifa to help radiologists make accurate patient diagnoses quickly and easily. In any given day, radiologists can review up to thousands of medical images to make health diagnoses. To date, accuracy has relied mainly on medical professionals piecing together multiple sources of clinical information visually and manually to make critical decisions, including electronic health records, research publications and other data.

The next Angry Birds AI competition will be held at IJCAI 2017 in Melbourne, Australia, August 24-25, 2017. For more details please refer to the Call for Participation and the detailed Competition Rules. This year we will again have two competition tracks, the standard track and a competitive track where two AI agents try to solve the same level with alternating shots. Previous Angry Birds AI competitions were held in Sydney in December 2012 during the Australasian AI conference, in Beijing in August 2013 during the IJCAI conference, in Prague in August 2014 at the ECAI conference, in Buenos Aires in July 2015 at the IJCAI conference, and most recently at the IJCAI 2016 conference in New York. Further details about these past competitions can be found here.

When students enrolled in USC's daunting neuroscience graduate program needed help cracking a tough project, they all went to Bosco Tjan. It didn't hurt that his advice often came with a free cappuccino. Mara Mather, a professor of gerontology and psychology at USC, described Tjan as an affable, caring presence on campus. He always found time to aid students and professors despite a breathless schedule. In many ways, she said, Tjan was the center's heartbeat.

Amazon Lex, Amazon Polly, and Amazon Rekognition are based on the same proven, highly scalable Amazon technology built by the thousands of deep learning and machine learning experts across the company. Amazon AI services all provide high-quality, high-accuracy AI capabilities that are scalable and cost-effective. Amazon AI services are fully managed services so there are no deep learning algorithms to build, no machine learning models to train, and no up-front commitments or infrastructure investments required. This frees developers to focus on defining and building an entirely new generation of apps that can see, hear, speak, understand, and interact with the world around them. To learn more about Amazon Lex, Amazon Polly, or Amazon Rekognition, visit: https://aws.amazon.com/amazon-ai

As in the global survey, we are concerned with platform business models and the design choices that allow these business models to grow. We find the term platform, which is well-established in economic and management literature, offers a more useful and accurate term than some of the terms that have been used such as "share economy companies," "internet companies" or, even more broadly, "tech companies." Network effects are a key characteristic that distinguish platforms from other business models. As more users engage with a platform, the more attractive the platform becomes to potential new users. When more users attract more users, a dynamic is created that in turn triggers a self-reinforcing cycle of growth.