The Mirai is Toyota's car of the future. It runs on hydrogen fuel cells, gets 312 miles on a full tank and only emits water vapor. So, to target tech and science enthusiasts, the brand is running thousands of ads with messaging crafted based on their interests. The campaign was written by IBM's supercomputer, Watson. After spending two to three months training the AI to piece together coherent sentences and phrases, Saatchi LA began rolling out a campaign last week on Facebook called "Thousands of Ways to Say Yes" that pitches the car through short video clips.

Watson, IBM's supercomputer, is most well known for beating two quizmasters on popular quiz show Jeopardy! in 2011. The impressive artificially intelligent software was developed to advance machine learning capabilities, including natural language processing, reasoning and knowledge retrieval. Watson can access information from an endless list of sources, from literature to databases. As AI continues to attract investment and R&D, it will impact our lives in so many ways. It's not surprising, then, that Watson has rather expanded its repertoire since its Jeopardy!

The Cognitive Adaptive Learning Classification and Response for Communications Threats system, (CALCR) uses a case-based reasoning (CBR) and case-based learning (CBL) approach to address issues encountered in a contested RF communications environment. CALCR was the result of a research project that explored new approaches to understanding communications threats and responding with appropriate countermeasures. Modern communications threats may be modified from existing systems, or may be completely new systems, and CALCR enables a response to these unknown or unanticipated threats. CALCR integrates existing properties of CBR, along with several innovations, making it ideal for this problem: the ability for a case library to be extended through CBL as new conditions are encountered; the robustness of CBR in situations where there is missing data, which CALCR addresses with an advanced intelligent similarity measure; the ability to detect classes unknown to the case library through the use of a confidence measure; and the ability to provide a best-attempt solution, when multiple threat classes are matched, through the use of a new approach called the taxonomy reasoner.

Case-based reasoning (CBR) systems have tight connections with machine learning and knowledge discovery and often incorporate diverse knowledge discovery functionalities and algorithms. This article presents themes identified in work presented at recent workshops on synergies between CBR and knowledge discovery. Among the main themes appear Big Data, with cases involving signals, images, texts, and other complex types of data; similarity metric discovery, in the form of weight spaces, feature weights, and feature selection; adaptation knowledge; explainability and transparency; and user centeredness and interactivity. Researchers highlight the advantages of case-based reasoning in terms of its lazy learning, explainability, user centeredness, and interactivity when performing knowledge discovery, as well as how diverse knowledge discovery methods can improve CBR.

Humans seek to gain knowledge and structure data by many means including both bottom-up and top-down methods. But often, people have a specific purpose to their activity that drives the process, that is, they have particular questions that need answering in support of some broader investigation. These questions often change as answers point in various directions during an investigation, whether the investigation is formal (e.g., scientific, legal, journalistic, or military) or simply an informal browsing of the internet. Here we take a mixed-initiative approach to knowledge discovery, and we present a system called Kyudo that supports the process using a conversational case-based reasoning process. Cases in Kyudo are sequences of knowledge goals or questions that form arcs through a multidimensional knowledge space and that form the core activity in a dialogue between the user and system. As the system gains more experience and therefore more cases, it is able to detect similarity in knowledge goals and prompt the user with additional relevant goals that can short circuit the human reasoning process to minimize tangents or false starts. In this paper we present a distance-based mechanism that reduces the total length of a goal trajectory through guidance that accelerates the human reasoning process and aids effective knowledge discovery.

IBM's Watson will power in-game voice command for Ubisoft's upcoming release of Star Trek: Bridge Crew during an experimental Beta period later this summer following the game's launch on May 30. Bridge Crew provides players the first opportunity -- ever – to use their voice, in natural language, to interact with their virtual Starfleet crew members. IBM's new "VR Speech Sandbox," the software used to build this feature, is now available for all developers to adapt for their own virtual reality (VR) applications and services. The Sandbox combines IBM's Watson Unity SDK with two services, Watson Speech to Text and Watson Conversation. Developers now have the opportunity to build new and innovative user interfaces, leveraging the power of voice interaction in virtual reality. In-game speech experiences, built with IBM Watson for Star Trek: Bridge Crew will be available this summer in Beta for cross-platform play.

The key to efficient starship management, as Captains Picard, Kirk, and Janeway have demonstrated, is communication. With Romulans closing in fast and Klingons on the starboard bow, you can't be mumbling orders from the captain's chair -- you need the kind of commanding presence to inspire blind devotion in your crew. And now you'll be able to hone those command skills in virtual reality. Star Trek Bridge Crew -- the VR game that puts you in the slip-on space shoes of a Starfleet officer -- already emphasizes vocal communication when you're playing with real humans, but it will soon allow you to use your voice to issue orders to computer-controlled characters, too. The feature has been made possible using IBM's VR Speech Sandbox.

IBM Watson's artificial intelligence platform will enable voice commands in Ubisoft's Star Trek: Bridge Crew virtual reality game. IBM and French video game developer Ubisoft have partnered to include Watson's interactive speech and cognitive capabilities in a VR game for the first time when Star Trek: Bridge Crew launches on May 30 on the Oculus Rift with Touch, HTC Vive, and PlayStation VR (PSVR). It's another one of those wonderful confluences of technology and games that we highlighted at our GamesBeat Summit event. With IBM Watson, Star Trek: Bridge Crew will provide players the opportunity to use their voice and natural-language commands to interact with their virtual Starfleet crew members. This feature is part of a strategic partnership with Ubisoft.

Ubisoft's Star Trek: Bridge Crew won't just put you in a VR starship when it finally launches. It'll also give you the power to interact with the virtual Starfleet crew with your voice. The company has teamed up with IBM to add Watson's interactive speech capabilities to the game, so you can tell a crew member to launch a missile -- and maybe even pompously add "make it so" in the end -- instead of using manual controls. Bridge Crew was supposed to launch last year but was plagued with numerous delays. It's now scheduled to come out on May 30th for the PC and PS4, with Watson's voice commands to follow later this summer during a Beta period.

A new study releases this week by UK-based Juniper Research supports our prediction that chatbots will redefine the customer service industry, with healthcare and banking industries expected to benefit the most. The new report titled "Chatbots: Retail, eCommerce, Banking & Healthcare 2017-2022," estimates that chatbots will help businesses save more than $8 billion per year by 2022, which is a huge increase from the $20 million estimated for this year. Call centers and customer service departments should already be investing in these new conversational technologies if they want to stay competitive and cost-effective as companies across industries grow their investment in building chatbots to help service customers faster, across any channel, device or platform, 24 7. Advancements in technology continue to transform customer service interactions. From improvements in loyalty and brand reputation to new revenue streams, the pathway to real-time self-service in customer service brings huge opportunities to forward-thinking businesses. Juniper also forecasts that the success rate of bot interactions in healthcare sector, completed without the assistance of a human agent, will increase from the current 12% to over 75% in 2022.