RAD's suite of products which presently includes SCOT, WALLY and FRED provides recurring monthly revenue for RAD. On average, each SCOT, WALLY and FRED respectively can generate, over a 4 year period, $60,000, $25,000 and $12,000 of total revenue for the Company. To date the aggregate of all units presently deployed, at purchase order stage and client verbal commitment stage equal more than $2,400,000 worth of total potential revenue. RAD expects to reach $100,000 of monthly recurring revenue by this fiscal year end February 28, 2019, which represents approximately $5,000,000 of total potential revenue. RAD already has total deployments, purchase orders and verbal commitments for half of this amount to date.

To use the title of Brad Stone's seminal book about the nation's largest online retailer, Amazon is so much "The Everything Store" that it can be a little hard to remember when it was just a bookstore. But Jeff Bezos' ambitions are actually the grandest in the land, and the dozen-plus Alexa devices the company announced today show the next step. Throughout tech history, incumbents have needed to beware of leapfroggers. Apple never needed to defend a dumb-phone business, so it could upend smartphones. T-Mobile had no landline thinking, so it could become the UnCarrier.

CEO, Martin Spencer, addresses their 2018 progress in multiple markets. For over twenty years, GeckoSystems has dedicated itself to development of "AI Mobile Robot Solutions for Safety, Security and Service(tm)." We have further cost reduced the direct manufacturing costs of our proprietary, breakthrough SafePath! It is our AI enabled human quick sense and avoid of moving and/or unmapped obstacles that opens up the immense HME/DME rehab and power wheelchair markets to GeckoSystems for a first mover opportunity. We now believe that our collision free benefit can be added to most power wheelchairs for less than $2,000 MSRP, installed. "Recently, I had the opportunity to do some Delphi Market Research with one of Pride Mobility's largest US dealers and their master rehab power wheelchair technician.

Microsoft and Amazon said that voice and video calls via the service will come to Alexa devices (including Microsoft's Xbox One) with calls that you can start and control just by voice. Last year the two companies announced plans to make Alexa and Cortana work together and it's taken a while to arrive, but now it's here. Amazon's push to make people buy more things via its assistant could provide a boost to Microsoft's aspirations of product integration in a way that didn't happen after the launch of the Xbox One and Kinect, which already featured voice control for Skype before Cortana and Alexa were on the scene.

It wouldn't be an Amazon event without a slew of new Echo devices, and this time is no different. The company announced not one, not two, but seven new Echo products today at an event today in Seattle. Not only are there now new versions of the Echo Dot, the Echo Plus and the Echo Show, Amazon also introduced several new Echo companions that you can use to bring Alexa to every room in your house -- and even your car. Like the new Echo Show, the new Echo Dot and Echo Plus look a lot better this year than last. The Dot, for example, no longer looks like an oversized hockey puck.

Artificial intelligence (AI) processing today is mostly done in a cloud-based data center. The majority of AI processing is dominated by training of deep learning models, which requires heavy compute capacity. In the last 6 years, the industry has experienced a 300,000X growth in compute requirements, with graphics processing units (GPUs) providing most of that horsepower. According to a new report from Tractica, however, as the diversity of AI applications grows, an increasing amount of AI processing will be handled within edge devices rather than in a centralized, cloud-based environment. Tractica forecasts that AI edge device shipments will increase from 161.4 million units in 2018 to 2.6 billion units worldwide annually by 2025.

Neo4j, the market leader in connected data, announced today the upcoming release of Neo4j 3.5, the native graph platform designed to drive the success and adoption of real-time business applications, including artificial intelligence (AI) and machine learning (ML) systems. Neo4j customers – including eBay and Caterpillar – have demonstrated that connected graph datasets are a foundational element of enterprise AI applications. Graph-based data models provide the necessary context for AI applications by capturing facts related to and relationships among people, processes, applications, data and machines. Informed by successful AI customer deployments – including knowledge graphs, fraud detection, recommendation systems and conversation engines – Neo4j 3.5 delivers foundational features for AI-powered systems of connection to generate bottom-line business value. "The way we organize and represent knowledge in AI-powered systems has a profound effect on what and how they can learn," said Bowles.

The consulting specialists and innovation drivers CAMELOT Management Consultants today announced the start of the "Global Community for Artificial Intelligence in Supply Chain Management". With immediate effect, CAMELOT is offering supply chain management and AI masterminds from research and practice an open platform for the targeted transfer of knowledge. The initiative gives companies the opportunity to collaborate in implementing the first flagship projects using artificial intelligence in supply chain management (SCM). Members of the community will benefit from the latest innovations and research outcomes, motivational speeches, use cases and how-to guides for artificial intelligence in supply chain management. The focus here is on AI applications in logistics.

and Poster program is to provide including their capabilities and workings.

According to the report, the global machine learning chip market was valued at $2,425.6 million in 2017, and is projected to reach $37,849.8 million by 2025, registering a CAGR of 40.8% from 2018 to 2025. The trend in artificial intelligence (AI), use of machine learning in numerous applications and emergence of quantum computing are the factors which increase the demand for machine learning chip market. In addition, the development of autonomous robots that can control themselves without human intervention is anticipated to provide potential growth opportunities for the market. However, dearth of skilled workforce and AI phobia are the major restraints of the market. Moreover, increase in demand for smart homes & cities, rise in efforts to make more human-like robots and popularity of IoT across the globe are expected to create tremendous opportunities for the market expansion.