AS DOOMSDAY SCENARIOS go, it does not sound terribly frightening. The "paperclip maximiser" is a thought experiment proposed by Nick Bostrom, a philosopher at Oxford University. Imagine an artificial intelligence, he says, which decides to amass as many paperclips as possible. It devotes all its energy to acquiring paperclips, and to improving itself so that it can get paperclips in new ways, while resisting any attempt to divert it from this goal. Eventually it "starts transforming first all of Earth and then increasing portions of space into paperclip manufacturing facilities". This apparently silly scenario is intended to make the serious point that AIs need not have human-like motives or psyches.

In his quest to transform the way the Pentagon wages war, Defense Secretary Ashton Carter has turned to Silicon Valley, hoping its experimental culture, innovation and sense of urgency would rub off on the rigid bureaucracy he runs. Carter has made several trips to the region and appointed Eric Schmidt, the chairman of Google's parent company to an advisory board. And recently he sat down at the Pentagon with Elon Musk to see what suggestions the billionaire founder of Tesla and SpaceX might have to make the nation's military more efficient and daring. "Having an incentive structure that rewards innovation is extremely important," he said in an interview after the meeting. Whatever you reward will happen." The Pentagon finds itself in a new arms race, struggling to keep pace with forms of combat that are fought with bytes as well as bullets. The technological advancements disrupting established business sectors are now shaking up the world of war - where robots, swarming drones and ...

IBM Watson joined forces with the X Prize Foundation to launch an open 5 million challenge to build an artificial intelligence app for healthcare that could also be used in other industries, including education, energy, the environment, global development or even exploration. "In the coming decade, as X Prize strives to achieve its impact mission through incentive competitions and crowd-sourcing, we see tremendous opportunity in this emerging generation of problem solvers to use AI to solve humanity's grandest challenges," X Prize CEO Marcus Shingles said in a statement. "The IBM Watson AI X Prize is intended to promote and progress the notion of'AI for impact' among the global bold innovator crowd, both the established community of practitioners, as well as encourage newcomers to experiment and ultimately demonstrate how AI can be used as a tool for good." Unlike previous X Prizes, including the Tricorder X Prize, in which companies are vying to develop a handheld medical scanner, and the original Ansari X Prize for suborbital flight, this contest allows the participants to define their own goals and to focus on solving different problems. "Rather than set a single, universal goal for all teams, this competition allows teams to define their own challenges and demonstrate their solutions, encouraging myriad problem-solving approaches," Amir Banifatemi, X Prize lead for the IBM Watson AI competition, said in a statement.

Consider TPOT your Data Science Assistant. TPOT is a Python tool that automatically creates and optimizes machine learning pipelines using genetic programming. TPOT will automate the most tedious part of machine learning by intelligently exploring thousands of possible pipelines to find the best one for your data. Once TPOT is finished searching (or you get tired of waiting), it provides you with the Python code for the best pipeline it found so you can tinker with the pipeline from there. TPOT is built on top of scikit-learn, so all of the code it generates should look familiar... if you're familiar with scikit-learn, anyway.

At the Oregon Digital Government Summit held in Salem earlier this month, Michael Finch, CIO of Lane County, Ore., discussed some of the opportunities for cognitive learning and artificial intelligence at the local government level, citing the ability to better serve constituents with tailored services informed by usage data. Eyragon Eidam is the assistant news editor for Government Technology magazine, and covers legislation, social media and public safety. He can be reached at eeidam@erepublic.com.

Artificial intelligence is a major player at Cannes Lions this week. And while AI is expected to transform tech within five years, Alphabet Executive Chairman Eric Schmidt assured attendees that there's little chance it will become "evil" as Hollywood films have depicted. In fact, he said, there are imminent benefits of AI. "Computer vision is now better than human vision. It means self-driving cars probably see a lot better than you, especially if you are drunk." Meanwhile, British musician and producer Brian Eno spoke about creativity and AI, defending human intelligence. "AI is not as advanced as we expected it would be," he said.

Over at the Mercury News site, Ethan Baron has a fun story on tourists who travel (sometimes from other countries) to Silicon Valley to visit big companies such as Apple, Facebook, and Google. None of these places are set up to welcome civilians, and all are security conscious, so the visits usually don't amount to much more than posing in front of signage and maybe buying a tchotchke in a gift shop. As the article conveys, Google's campus is at least a tad more tourist-friendly than most: The giant sculptures of Android mascots are on a public thoroughfare and well worth a visit. The local color also spills out onto the streets of Mountain View, where every motorist gets to experience the novelty of dodging Googlers on colorful bikes. But really, if you've traveled to Silicon Valley to learn about Silicon Valley, my top recommendation would be to visit the wonderful Computer History Museum.

Machine Learning is a powerful tool, and if you attended our first session you learned the basics, now it's time to really dig in and try it for yourself. What do you do when the accuracy of your predictions doesn't meet your business needs? What can you do differently with the data or the algorithms to improve your results? Ideally you attended the first session to learn the basics, but if you missed it you can complete this tutorial to catch up on what you missed. In this session we will challenge you to train a model to get higher accuracy, get hands on and make changes to improve the results.

Machine Learning is a powerful tool, and if you attended our first session you learned the basics, now it's time to really dig in and try it for yourself. What do you do when the accuracy of your predictions doesn't meet your business needs? What can you do differently with the data or the algorithms to improve your results? Ideally you attended the first session to learn the basics, but if you missed it you can complete this tutorial to catch up on what you missed. In this session we will challenge you to train a model to get higher accuracy, get hands on and make changes to improve the results.

Robots probably won't kill people, but people could kill people with robots. That's the concern of an open letter signed by scientists and other interested parties -- including Elon Musk, Steve Wozniak and Stephen Hawking. If any major military power pushes ahead with AI weapon development, a global arms race is virtually inevitable, and the endpoint of this technological trajectory is obvious: autonomous weapons will become the Kalashnikovs of tomorrow. See also: Team KAIST won the 2015 DARPA Robotics Challenge, so now what? The Future of Life Institute, the volunteer-backed research organization which posted the letter, aims to "maximize the future benefits of AI while avoiding pitfalls," according to its website.