StartupSource's Liam Tracey-Raymont recently spoke with Andrew Arruda, CEO and co-founder of ROSS Intelligence Inc. ("ROSS"), to discuss ROSS's growth and to shed some light on the developmental timeline and hurdles associated with launching a tech startup. ROSS, initially developed in Canada and founded by University of Toronto ("U of T") students, is a cloud-based software program that assists users in answering legal questions efficiently and without relying on complicated boolean queries and keywords. While ROSS is still a relatively new product, it has quickly attracted significant media attention and immense interest from U.S. clients, which are predominantly law firms. Liam caught up with the ROSS CEO after Andrew returned to his new home in San Francisco, California, following a week on the road. Andrew, it's been a while. What have you been up to recently?

Most car company executives appear at the annual Los Angeles Auto Show to tout their brand's new vehicles or crow about its balance sheet. Ford Chief Executive Mark Fields came to town this year to give the kick-off keynote speech at AutoMobility L.A., the industry-only portion of the massive car show, and didn't discuss those things at all. Instead, he talked about the future of mobility, the "city of tomorrow" and how Ford is trying to find its place in a changing transportation landscape that -- confronting autonomous driving, connected cars and ride-sharing -- may soon have no place for traditional car companies. The following is an edited version of the conversation. Ford produces the F-150 truck, the most popular vehicle sold in America, but is also offering a hydrogen fuel cell Clarity and a line of plug-in hybrids.

The technology is complex and easy at the same time. The DNA of Aldebaran is maybe not to use the best technologies: If you look at those from Boston Dynamics or the ASIMO robot from Honda, they are wonderful robots. They can run, jump a wall, take glasses and give you drinks – but these machines are far from ready to enter the market and they cost millions of dollars. We believe that with current technology, we are capable of producing a robot that is able to move, able to interact and can go to market today even if it doesn't have the best motor. We use technology that is affordable and know how to make it work correctly.

Ritika Gunnar is vice president of offering management, data and analytics at IBM. She has also served as a software engineer and as vice president for information integration and governance in IBM's platform analytics group. In this exclusive interview with SearchCloudApplications, she discusses the evolution of the data science industry and the skills that developers must possess to flourish in a data-driven world. Bringing development and IT ops together can help you address many app deployment challenges. Our expert guide highlights the benefits of a DevOps approach. Explore how you can successfully integrate your teams to improve collaboration, streamline testing, and more.

The Lovie Awards were privileged to honour Yann LeCun with the 2016 Lovie Lifetime Achievement Award for his work as a pioneer in the creation of neural networks. LeCun's contributions to the science of machine learning, mobile robotics and computational neuroscience among other learned fields, is legendary. As a founder of Neural Nets, LeCun applied biological methods of perception to computer processors. Currently continuing his forward-thinking work as the Head of Artificial Intelligence at Facebook, LeCun is poised to see his genius bear inventive innovations to the social media platform that will affect a global user base. As he continues to inform and experiment with the future of mediums such as the incredibly fast-growing arena of machine learning, LeCun's work will only improve upon the already impressive technologies he has brought to fruition.

Google is announcing today that it's setting up a deep learning and artificial intelligence (AI) research unit in its office in Montreal and giving $3.37 million in grant money to deep learning luminary Yoshua Bengio and seven other people associated with the Montreal Institute for Learning Algorithms (MILA). Bengio himself has previously received backing from Google, and from other companies as well -- namely, IBM, Samsung, and Intel. But the new grant is "bigger than any of the other funding we've received from private companies up until now," he said during an interview with VentureBeat. Bengio will not be formally allying himself with Google proper, because he wants to stay independent. "That's who I am," he said, "that's the choice I made that fits with my values, and I don't need to get the millions, I'm fine. My salary is very good, and I care more about how what I can do could have a positive impact for science, humanity, and for training the next generation [of researchers]."

John Charles Thomas was born in Akron, Ohio and attended Ellet High School. He graduated from Case Western Reserve University majoring in psychology and minoring in mathematics and drama. He received a Ph.D. in experimental psychology from the University of Michigan. His dissertation compared human performance in a problem solving task to that of an early AI system called "The General Problem Solver." After graduate school, Dr. Thomas managed a research project on the psychology of aging at Harvard Medical School.

Are art and science of distinctly different cultures? The former often seems fixated on human experience, the latter on physical processes. In his most recent book, Reductionism in Art and Brain Science: Bridging the Two Cultures, published this year, the Nobel Prize-winning neuroscientist Eric Kandel argues that such a separation no longer exists. The best-known abstractionists, like Mark Rothko, Jackson Pollock, Dan Flavin, and Willem de Kooning, Kandel writes, effectively created "new rules for visual processing." Abstract art, says Kandel, is therefore the key to understanding both how art and science inform one another, and together, they might open up entirely new ways of seeing and imagining.

Of the vast wealth of information unlocked by the Internet, most is plain text. The data necessary to answer myriad questions--about, say, the correlations between the industrial use of certain chemicals and incidents of disease, or between patterns of news coverage and voter-poll results--may all be online. But extracting it from plain text and organizing it for quantitative analysis may be prohibitively time consuming. Information extraction--or automatically classifying data items stored as plain text--is thus a major topic of artificial-intelligence research. Last week, at the Association for Computational Linguistics' Conference on Empirical Methods on Natural Language Processing, researchers from MIT's Computer Science and Artificial Intelligence Laboratory won a best-paper award for a new approach to information extraction that turns conventional machine learning on its head.

A product from Japan created quite the stir at Consumer Electronics Show in Las Vegas and CEATEC JAPAN in Tokyo this year. The "harmony" of clothing analysis, artificial intelligence (AI), and robotics blend together to produce a "fully automatic clothes folding machine." Japan technological alliance "seven dreamers laboratories' is the developer. The product details have been released in various places, so I won't get into that, but as the name says, "It's a robot that folds clothes. No further explanation is needed." The company announced a partnership with Panasonic (TSE:6752) and Daiwa House (TSE:1925) last year, and together established the joint venture Seven Dreamers Laundroid with plans to begin sales by reservation for their first machine "Laundroid 1" in March of 2017. The developer, Seven Dreamers, announced on November 14th the securement of 6 billion yen (around $60 million US) in funds from SBI Investment, in addition to Panasonic and Daiwa House. The shareholding ratios and payment date remain undisclosed. The concept began in 2005, and with the realization of "folding" from 2013, Laundroid was born. I heard from Seven Dreamers CEO Shin Sakane about the road it took to get here. I came today with the idea of asking straight out, "What happened to make robots fold the laundry?" Well, to be straight, "It's now possible to recognize clothes using artificial intelligence," is maybe the simplest answer I can give. Let's go through the process. How did the idea first come to you? Before that, first permit me to talk a little about what criteria the Seven Dreamers esteem. For us, there are three criterion for "Things that have not been realized yet but could change our lives, and also enrich them." The technological hurdles are high and our policy is to clear them. You've made something that sets high hurdles. Since first coming up with the idea, I was thinking about different markets to satisfy all the criteria. Looking around we see many products targeted at men. Starting now and into the future, 'women', 'the elderly', and'children' are the keywords that will become important. After thinking, the idea that maybe the answer lies within the home came to me and, while I don't usually talk with my wife about work, I casually mentioned it to her. What do you wish you had? She came back just as fast, "Of course, it has to be a machine that folds the laundry.