In late 2015 Toyota proclaimed a five-year project investing 1 billion in artificial intelligence and robotics research with the establishment of Toyota Research Institute (TRI) facilities at Stanford University and the Massachusetts Institute of Technology. The fields of study are artificial intelligence, autonomous transportation, and mobile indoor robotics. Gil Pratt, CEO of TRI as well as an MIT alum and a former program manager at the Defense Advanced Research Projects Agency (DARPA), laid out two tracks for autonomous vehicle research: one for "chauffeur model" wholly autonomous cars, one for "guardian angel" systems that would create more helpful, "intelligent" but traditional cars. A guardian angel, like a fearless driving instructor with a mirrored set of controls in the passenger's seat, would only take over if it determines an incident is imminent. Seen as a mid-term step ahead of the fully autonomous cars Toyota is also working on – and Google, Uber, Ford, and Volvo – the introduction of advanced AI monitoring systems could see production before self-driving cars since the human remains in charge more than 99 percent of the time.

Description: The ATLAS conference is an interdisciplinary workshop on mathematical and algorithmimcal approaches for high dimensional problems in data sciences. This year's event is particularly dedicated to signal processing and applications in different fields as medical imaging, neurosciences, astrophysics.... with a particular emphasis on the use of innovative optimization methods. The workshop's program will feature plenary talks given by experts in the field, as well as short talk.

At US 15, the Quark Microcontroller Developer Kit D2000 is perhaps the least expensive computer Intel has ever shipped. The single-board computer has all the components mashed onto a tiny circuit board. It can be used to develop gadgets, wearables, home automation products, industrial equipment and other Internet of Things products. Developers could also use the computer to hook up sensors for temperature, light, sound, weather and distance to devices. The developer board is now available from Mouser Electronics.

Seismic launched their own collaboration platform called Workspace and claim to be "the only sales enablement platform with every essential capability in place now." The new cloud forum enables enterprise users to collectively gather, share and access content and add comments, annotations, feedback and commentary to their sales content. Amazon acquisition of deep learning startup Orbeus Inc, underlining their efforts to apply AI based deep learning techniques in their delivery systems and cloud computing business. Orbeus has developed a photo recognition technology based on neural networks named ReKognition. Conversocial, a social customer care platform launched its Channel API and announced initial integration partnerships with social Intelligence, monitoring and analytics companies Synthesio and Brandwatch.

For a while (at least several months since many people began to implement it with Python and/or Theano, PyLearn2 or something like that), nearly I've given up practicing Deep Learning with R and I've felt I was left alone much further away from advanced technology… But now we have a great masterpiece: {h2o}, an implementation of H2O framework in R. I believe {h2o} is the easiest way of applying Deep Learning technique to our own datasets because we don't have to even write any code scripts but only to specify some of its parameters. That is, using {h2o} we are free from complicated codes; we can only focus on its underlying essences and theories. With using {h2o} on R, in principle we can implement "Deep Belief Net", that is the original version of Deep Learning*1. I know it's already not the state-of-the-art style of Deep Learning, but it must be helpful for understanding how Deep Learning works on actual datasets. Please remember a previous post of this blog that argues about how decision boundaries tell us how each classifier works in terms of overfitting or generalization, if you already read this blog.

Autonomous agents are a huge trend in consumer, business, industry, and other domains. They're popping up in everything from physical devices -- such as Internet of things (IoT) endpoints and mobile handsets -- to cloud services such as virtual personal assistants and smart advisers. Autonomous IoT devices will allow us to multitask like never before. As we incorporate more of them into our lives, we can offload much of the drudgery we once needed to handle manually. We will let self-driving cars manage our commute, offload the more strenuous yardwork to our robotic household assistants, and depend on personal drones to keep an eye on the neighborhood.

IBM is developing a new weapon in the battle against cancer that will put Watson to work in a new way. Partnering with the American Cancer Society, IBM is building a virtual advisor that uses machine learning to give patients personalized information and advice. The advisor will begin by looking at the type of cancer the patient is suffering from, the stage of the disease and the treatments administered so far. Using that and other data, it will try to offer care advice and answer patients' questions. Watson's voice recognition and natural language processing will enable users to ask questions and receive audible responses.

Facebook will now allow businesses to deliver automated customer support, ecommerce guidance, content, and interactive experiences through chatbots. By providing utility through its huge developer and business ecosystem, Facebook could boost loyalty with Messenger, one-up SMS, and keep up chat competitors like Kik, Line and Telegram that have their own bot platforms. This confirms TechCrunch's scoops from February that Facebook was working with chatbot developers, and last week that a program for automated agents would launch at F8. [Update: the official name for the platform is "bots on Messenger", not "agents on Messenger", which was a previous codename] Facebook announced a slew of chatbot partnerships with developers who got early access, like 1-800 Flowers, so you can order flowers by just sending its Messenger bot a friend's name. Or CNN could send you a "daily digest" of stories that match your interests, and skip the topics you don't care about. Zuckerberg explained that with AI and natural language processing combined with human help, people will be able to talk to Messenger bots just like they talk to friends. Through the Messenger Platform's new Send/Receive API, bots can send more than just text.

Facebook Messenger users will be able to talk with automated bots using a new set of developer tools, the social networking company announced Tuesday during its F8 conference in San Francisco. The new Messenger Platform Send/Receive API will let developers build bots that can converse with users and do things like let them purchase items and get the latest news. It gives developers a set of user interface tools that will allow them to create buttons inside a Messenger conversation that guides users on what a bot can do, along with handling text conversation. The tools are available in beta to developers Tuesday, with companies like shopping app Spring, CNN, and weather bot Poncho providing Facebook bots to users at launch. The news comes just weeks after Microsoft devoted a large chunk of its Build developer conference keynote to what its executives called "conversations as a platform." The company released a free toolkit to help developers make bots that work across a variety of platforms, including Messenger competitors GroupMe and Telegram.

Jon Barker: Jon Barker is a Solution Architect with NVIDIA, helping customers and partners develop applications of GPU-accelerated machine learning and data analytics to solve defense and national security problems. He is particularly focused on applications of the rapidly developing field of deep learning. Prior to joining NVIDIA, Jon spent almost a decade as a government research scientist within the U.K. Ministry of Defence and the U.S. Department of Defense R&D communities. While in government service, he led R&D projects in sensor data fusion, big data analytics, and machine learning for multi-modal sensor data to support military situational awareness and aid decision making. He has a Ph.D. and B.Sc. in Pure Mathematics from the University of Southampton, U.K.