Where does true power reside? Is it waving at you from a stage-lit, Presidentially-sealed podium? Or tucked away inside a billionaire's wallet? Can you smell it in a mahogany-clad clubroom at Yale in the smoke of a Bonesman's cigar, or catch a glimpse of its dark feathers perching on the advisory council of a transnational bank? One thing we know for sure: the nature and location of power is changing, and the agents of that change are the Californian technology companies that have the taken the 21st century by the throat.

Olli, a 3D printed, self-driving minibus, to hit the road in US A new maker of self-driving vehicles burst onto the scene Thursday in partnership with IBM's supercomputer platform Watson, and it's ready to roll right now. The vehicle -- a 3D-printed minibus called "Olli" capable of carrying 12 people -- was unveiled by Arizona-based startup Local Motors outside the US capital city Washington. Napster's improbable journey This week the Rhapsody music service announced that it will retire the Rhapsody name and re-brand its service (and the company) under the Napster brand. The Napster name has endured a long journey in the 17 years since Shawn Fanning first created the service in early 1999. I thought it might be helpful to put together a short history tracing that path.

There's been a lot of handwringing about the algorithms driving what we see related to political news. First, a month ago, there was concern that Facebook's news feed results were biased against conservative news, and this week, there's concern that Google favors Hillary Clinton in its autocomplete suggestions in its search engine. The video shows that Google seems to have suppressed the appearance of "Hillary Clinton indictment" in favor of "Hillary Clinton India," even though data shows people search for information on Clinton's indictment more than information on Clinton and India. It points out that the executive chairman of Google's parent company, Eric Schmidt, is a big Clinton supporter and that Google has many ties to her as well.) Search engines and algorithms decide what's relevant on these sites in very complicated ways, and the public generally doesn't know when it gets tweaked. Generally speaking, people want artificial intelligence.

Large-scale brain-like machines with human-like abilities to solve problems could become a reality, now that researchers have invented microscopic gadgets that mimic the connections between neurons in the human brain better than any previous devices. The new research could lead to better robots, self-driving cars, data mining, medical diagnosis, stock-trading analysis and "other smart human-interactive systems and machines in the future," said Tae-Woo Lee, a materials scientistat the Pohang University of Science and Technology in Korea and senior author of the study. The human brain's enormous computing power stems from its connections. Previous research suggested that the brain has approximately 100 billion neurons and roughly 1 quadrillion (1 million billion) connections wiring these cells together. At each of these connections, or synapses, a neuron typically fires about 10 times per second.

The Defense Advanced Research Projects Agency (DARPA) announced on Friday the launch of Data-Driven Discovery of Models (D3M), which aim to help non-experts bridge what it calls the "data-science expertise gap" by allowing artificial assistants to help people with machine learning. DARPA calls it a "virtual data scientist" assistant. This software is doubly important because there's a lack of data scientists right now and a greater demand than ever for more data-driven solutions. DARPA says experts project 2016 deficits of 140,000 to 190,000 data scientists worldwide, and increasing shortfalls in coming years. For example, in order to construct a model for how different weather, school, location, and crime factors affect congestion for ride-sharing services in downtown Manhattan, a team of NYU students spent the equivalent of more than 90 months of work hours to complete the model.

Robots have already invaded the operating room in some hospitals, but in Belgium they will soon be taking on the potentially more difficult task -- for robots, at least -- of greeting patients and giving them directions. The Citadelle regional hospital in Liège and the Damiaan general hospital in Ostend will be working with Zora Robotics to test patients' reactions to robot receptionists in the coming months. Zora already has experience programming the diminutive humanoid robot Nao to act as a chatty companion for the elderly, offering it as a form of therapy for those with dementia. Now the Belgian company is working with Nao's newer, bigger sibling, Pepper. Both were developed by French robotics company Aldebaran, now owned by Japanese Internet conglomerate SoftBank.

The spread of hackathon-style events and "project sprints" has created an explosion of new business ideas across industries. Despite the flood, the pipeline for developing nascent businesses is broken. Whether you're developing a new line of business inside a corporation or building the next Silicon Valley mega-startup, it can be hard to transition from the high-speed, high-intensity environment of a hackathon to the slow, methodical process of finding product-market fit. Hackathon judges sometimes pick "winners" with great stories but not great business plans, making it even more confusing to tell which ideas have potential. Experienced entrepreneurs know that the customer is the only judge that really matters.

Google executive chairman Eric Schmidt has questioned whether renowned scientist Stephen Hawking and SpaceX billionaire Elon Musk are in a position to accurately predict the future of artificial intelligence. Hawking told the BBC in 2014 that AI could end mankind, while Musk tweeted that same year that AI could be more dangerous than nuclear weapons after reading a book called "Superintelligence." Schmidt was asked at the Brilliant Minds conference in Stockholm on Thursday what he made of their predictions. In response, he said: "In the case of Stephen Hawking, although a brilliant man, he's not a computer scientist. Elon [Musk] is also a brilliant man, though he too is a physicist, not a computer scientist."

Welcome to my home page. I specialize in artificial intelligence, machine learning, and data visualization, and regularly write about my latest work on my personal blog. I also occasionally collaborate with the media and private companies on projects that I believe are important, many of which have been featured all over the world and in the news. If you'd like to talk data, hire me to consult on a data project, commission me to teach a workshop in your area, or anything else, please feel free to contact me by email.

Even research which is conducted within the university setting is increasingly pushing up against new ethical frontiers in the creation of machine learning algorithms based on vast pools of human-created training data. For example, several researchers I spoke with mentioned situations where colleagues had taken large datasets licensed to the university for strictly non-commercial use or collected from human subjects for strictly academic research and used them to construct large machine learning computer models. These models were then licensed from the university to the faculty member's private startup, where they were then used for commercial gain. In at least some cases, protected human subjects data was used to create a computer model for academic research, which was approved by IRB, but that model was then allegedly subsequently licensed by the university for commercial use to the faculty member's startup. None of the researchers were privy to whether IRB had approved the commercial licensing or if that occurred without IRB knowledge and they argued that the very nature of a machine learning model deidentifies such data to the point that it should no longer be considered human subjects data.