The Japanese automaker already has a research lab in the Silicon Valley technology hub of Palo Alto, where it works with Stanford University, and another in Cambridge, Massachusetts, where it collaborates with MIT. Its new facility near the University of Michigan will have a staff of about 50 employees. The world's top-selling automaker announced in November that it would invest 1 billion in research and development over the next five years in artificial intelligence technologies, which are critical to the computer brains of self-driving cars. Toyota's investment in R&D comes as competition in the fast-moving field of autonomous vehicles expands beyond carmakers in Asia, Europe and the United States to non-traditional sources such as Alphabet's Google and Apple. The new Ann Arbor facility will focus primarily on fully autonomous driving, in which the car takes full control, the company said.

Years from now, a robotic astronaut named Val could walk across the dusty Martian terrain to greet a spaceship carrying humans ready to colonize the Red Planet. How well the robot does that job will fall to some Bay State universities, who are playing a key role in teaching Val how to be an astronaut's best friend. "What she will be able to do, hopefully, is just about everything that a suited astronaut in a planetary field could do," said Kris Ver deyen, NASA project manager for Val. "This is NASA's first foray into a bipedal motion robot, so we're basically learning the ropes as we go." Val -- short for Valkyrie -- is a 6-foot, 2-inch, 300-pound mass of metal, wires and plastic that was delivered to University of Massachusetts Lowell at 6:30 yesterday morning, along with a squad of NASA engineers, who put together the robot piece by piece.

This week in Amsterdam, a team of computer scientists and Rembrandt experts unveiled a new portrait that looks alarmingly similar to the work of the famed Dutch artist. The portrait of a man wearing a broad hat is the latest example of how advanced computer methods are making it increasingly easy to mimic the style of history's most acclaimed artists. Art that hangs in museums, sells for millions and that has endured for generations is being emulated by computer wizards without the pedigree of Rembrandt and kin. When lined up against Rembrandt's work, it can be difficult to tell which portrait a machine created and which the Dutch painter created roughly 400 years ago. The creators of the "new Rembrandt" used computers to 3D scan and analyze 346 Rembrandt paintings.

It's also critical to understand the differences between a Data Analyst and a Machine Learning engineer. In simplest form, the key distinction has to do with the end goal. As a Data Analyst, you're analyzing data in order to tell a story, and to produce actionable insights. The emphasis is on dissemination--charts, models, visualizations. The analysis is performed and presented by human beings, to other human beings who may then go on to make business decisions based on what's been presented.

Should I get started with "Machine Learning" to improve my situation? If you are trying to pick an action based on a problem you are facing, how should you approach it? You have heard a lot or a little about "Machine Learning." Here's my personal story to help you decide. As a software programmer, when I want solve a problem, I try to figure out a way to automate it.

Among all of the fictional artificial intelligence (AI) systems, by far, the coolest one has to be Tony Stark's JARVIS--It can not only control everything for Iron Man, it's also a highly intuitive and sentient entity that has become part and parcel of his Tony Stark's way of life. Now, Microsoft has announced that they are planning to create something similar--a highly advanced personal digital assistant--which will be available as smartphone application.

Once the three-billion-letter-long human genome was sequenced, we rushed into a new "omics" era of biological research. Scientists are now racing to sequence the genomes (all the genes) or proteomes (all the proteins) of various organisms – and in the process are compiling massive amounts of data. For instance, a scientist can use "omics" tools such as DNA sequencing to tease out which human genes are affected in a viral flu infection. But because the human genome has at least 25,000 genes in total, the number of genes altered even under such a simple scenario could potentially be in the thousands. Although sequencing and identifying genes and proteins gives them a name and a place, it doesn't tell us what they do.

Once, a messenger app did just that – message. But with the rise of artificial intelligence, tech companies are falling over themselves to prove how much more useful and interactive their apps can be – which is why you're about to see an explosion of "bots". Kik, the mobile chat application popular with teenagers, launched its Bot Shop on 5 April, and Facebook is poised to launch its own bot store for Facebook Messenger next week. Every brand from Barbie to the Washington Post seems to be working on a chat bot of its own. For Kik, chat bots are the next step in the evolution of the internet.

While Siri now lives on the phones of hundreds of millions of Apple users, just a few people are responsible for helping get the now ubiquitous assistant off the ground. One of those people is Dag Kittlaus, co-founder and CEO of Siri and now co-founder and CEO of Viv, a new platform-based AI product. Dag is the CEO and co-founder of Viv, which he started with Siri vets Adam Cheyer and Chris Brigham. Previously, he was the Co-founder and CEO of Siri after spinning the technology out of Stanford Research Institute in 2007. After Apple acquired Siri in 2010 Dag became the Director of iPhone Apps at Apple running the Siri and speech recognition teams.

There's already plenty of angst out there about the prospect of jobs lost to artificial intelligence, but this week, artists got a fresh reason to be concerned. A new "Rembrandt" painting unveiled in Amsterdam is not the work of the Dutch master Rembrandt van Rijn at all, but rather the creation of a combination of technologies including facial recognition, AI, and 3D printing. Essentially, a deep-learning algorithm was trained on Rembrandt's 346 known paintings and then asked to produce a brand-new one replicating the artist's subject matter and style. Dubbed "The Next Rembrandt," the result is a portrait of a caucasian male, and it looks uncannily like the real thing. One particularly interesting detail about The Next Rembrandt project, which was a collaboration among several organizations including Dutch bank ING and Microsoft, is how the algorithm chose the subject for its painting, since it had to be entirely new.