At the NULLCON International Security Conference in Goa, India, a startup presented a prototype vulnerability scanner... This email address is already registered. By submitting my Email address I confirm that I have read and accepted the Terms of Use and Declaration of Consent. By submitting your email address, you agree to receive emails regarding relevant topic offers from TechTarget and its partners. You can withdraw your consent at any time.

Salesforce is set to acquire deep learning start up MetaMind in an effort to bolster it artificial intelligence capabilities. While terms of the deal have not been released, it would appear to be an "acqhire" based agreement, as Salesforce will integrate MetaMind's technology into its current services. Long-term intentions have not been announced, though MetaMind's capabilities will be used to automate and personalize customer support in the first instance. "With MetaMind and Salesforce coming together, we'll be able to offer customers real AI solutions with breakthrough capabilities that further automate and personalize customer support, marketing automation, and many other business processes," said MetaMind Founder Richard Socher. "We'll extend Salesforce's data science capabilities by embedding deep learning within the Salesforce platform."

With robotic research on the rise, the implementation of artificial intelligence is paving the way for robotic achievements. An AI passed the first round of a literary competition, begging the question, how safe are the creative arts? After an artificial intelligence software proved creative enough to -- with the help of humans -- pass the first round of a national Japanese literary competition, people have now become more afraid of AI. Of course, now AI has seeped into the arts, so there's no stopping them. We're going to be taken over by computers, right?

Employing artificial intelligent robots in Chinese restaurants – an idea that attracted national headlines – has not proved such a smart idea after all, mainland media reports. A number of restaurant owners have chosen to fire about 10 robots because they were just not clever or sophisticated enough to do their jobs properly, the Xiamen Daily reported. The plug has been pulled on a number of the robots – employed as chefs and waiters – only a few years after a catering business in the seaport city of Xiamen, in southern Fujian province, scrambled to employ them instead of people, the newspaper said on Tuesday. Workers are ready for the robot revolution, but are their managers? Another restaurant, which opened last October, made local headlines for using four automated waiters that were able to take orders and deliver food to customers' tables.

Have you ever begun a Google search, only to click on the words the box lays before you? Tagged a friend's face when Facebook prompted it? Have you spoken to your iPhone? The artificial intelligence technology behind these tools is neither self-aware nor homicidal. But they are driven by a computational technique called machine learning, which is, at its simplest, a way to teach machines to teach themselves.

We identified 32 companies that are already applying machine learning techniques and predictive analytics to reduce drug discovery times, provide virtual assistance to patients, and diagnose ailments by processing medical images, among other things. The 32 startups on the list have raised more than 530M in aggregate funding. This year, New York-based AiCure raised 12.3M in Series A funding and National Science Foundation-grantee Cloud Pharmaceuticals raised a 350K round from undisclosed investors. London-based health services startup, Babylon Health, raised a 25M Series A round from investors including Google-owned DeepMind Technologies and Hoxton Ventures. The company will reportedly roll out a Siri-like voice recognition interface this year.

"It shows that people respond to robots in a primitive, social way," researcher Jamy Li said in the release. "Social conventions regarding touching someone else's private parts apply to a robot's body parts as well. This research has implications for both robot design and theory of artificial systems." As shown in the video above, the robot in the experiment also provides an anatomical definition of each body part touched. There were four female volunteers and six male volunteers in the small study, according to The Guardian.

In episode five of Season two Ryan walks us through variational inference, we put some listener questions about Go and how to play it to Andy Okun, president of the American Go Association (who is in Seoul South Korea watching the Lee Sedol/AlphaGo games). Plus we hear from Suchi Saria of Johns Hopkins about applying machine learning to understanding health care data.

At least, that's what we've been telling young professionals and mid-career workers alike who want to hack it in the modern workforce--in fact, it's advice I've given myself. And judging by the proliferation of coding schools and bootcamps we've seen over the past few years, not a few have eagerly heeded that instruction, thinking they're shoring up their livelihoods in the process. Unfortunately, many have already learned the hard way that even the best coding chops have their limits. More and more, "learn to code" is looking like bad advice. Anyone competent in languages such as Python, Java, or even web coding like HTML and CSS, is currently in high demand by businesses that are still just gearing up for the digital marketplace.

Students, global experts and researchers recently gathered for the third annual Machine Learning and Data Analytics Symposium (MLDAS) in Doha. Organized by the Qatar Computing Research Institute (QCRI) and the Boeing Company, the event served as a platform to discuss happenings in machine learning and data analytics from applications to recent advances. "When we organized the first MLDAS three years ago, we wanted to drive conversations and innovations in the machine learning and data analytics field," Dragos Margineantu, MLDAS co-chair and technical fellow with Boeing Research & Technology, said. "Since that time, we have seen unprecedented growth and, though we're just one piece of a huge field, I'm proud that we've been involved and helped connect respected researchers with practitioners and students to further advance research in the fields of machine learning and data analytics." The two-day symposium included talks on how machine learning techniques can be applied to scientific discovery and aircraft health maintenance.