Google has had an eventful couple of weeks, announcing enhancements to its search and map capabilities at its virtual "Search On" event on Oct. 15, and on Oct. 20 being accused by the US Justice Department of engaging in anti-competitive practices in order to preserve its search engine business. At the Search On event, Google detailed how it has tapped AI and machine learning techniques to make improvements to Google Maps as well as Search. In an expansion of its search "busyness metrics," users will be able to see how busy locations are without identifying the specific beach, grocery store, pharmacy or other location. COVID-19 safety information will also be added to business profiles across Search and Maps, indicating whether the business is using safety precautions such as temperature checks or plexiglass shields, according to an account in VentureBeat. An improvement to the algorithm beneath the "Did you mean?" features of search, will enable more accurate and precise spelling suggestions.
The ability of computers to autonomously learn, predict, and adapt using massive datasets is driving innovation and competitive advantage across many industries and applications. The artificial intelligence (AI) is budding faster and prompting businesses to hop aboard the next big wave of computing to uncover deeper insight, quickly resolve their most difficult problems, and differentiate their products and services. Whether the goal is to build a smarter city, power an intelligent car, or deliver personalized medicine, we've only just begun to understand the real potential of AI. For the implementation of AI, HPE OEM has the expertise, edge to core technologies and partner ecosystem to help explore different use cases, experiment with AI and data technologies, and build the solution to be enterprise-ready. HPE OEM will benefit at all stages of the journey from formulating a roadmap through implementation and data migration.
Amazon Go is the first store where no checkout is required. Customer simply enter the store using the Amazon Go app to browse and take the required products or items they want and then leave. Customer being able to purchase, products without suing a counter or checkout. The following video shows how Self-driving Robot (Delivery Bot and named as YAPE) brings goods directly to you, it uses Facial Recognition to recognize the customer to deliver. It makes delivery fast and easy, bot easily navigates sidewalks. YAPE has a 70 kg loading capacity and can travel 80km on a single charge.
Transaction data is like a friendship tie: both parties must respect the relationship and if one party exploits it the relationship sours. As data becomes increasingly valuable, firms must take care not to exploit their users or they will sour their ties. Ethical uses of data cover a spectrum: at one end, using patient data in healthcare to cure patients is little cause for concern. At the other end, selling data to third parties who exploit users is serious cause for concern.2 Between these two extremes lies a vast gray area where firms need better ways to frame data risks and rewards in order to make better legal and ethical choices.
Eight technologies developed by MIT Lincoln Laboratory researchers, either wholly or in collaboration with researchers from other organizations, were among the winners of the 2020 R&D 100 Awards. Annually since 1963, these international R&D awards recognize 100 technologies that a panel of expert judges selects as the most revolutionary of the past year. Six of the laboratory's winning technologies are software systems, a number of which take advantage of artificial intelligence techniques. The software technologies are solutions to difficulties inherent in analyzing large volumes of data and to problems in maintaining cybersecurity. Another technology is a process designed to assure secure fabrication of integrated circuits, and the eighth winner is an optical communications technology that may enable future space missions to transmit error-free data to Earth at significantly higher rates than currently possible.
Always worried about the potential for embarrassing background noises at home during video meetings? Microsoft is working on an update that could save you from future videoconferencing faux pas. The company's Microsoft 365 roadmap lists as in development "AI-based real-time noise suppression," which is scheduled for release in November 2020. The feature, spotted by news site Windows Latest, "will automatically remove unwelcome background noise during your meetings." Artificial intelligence technology is used to analyze a user's audio and "specially trained deep neural networks" will filter out noises and keep the person's voice, the software giant's planning document says.
The retail experience is certainly changing in the face of the global pandemic. A Rip Van Winkle who might have fallen asleep in January 2020 and woken up in September 2020 would find their retail experience to be a surreal experience with shoppers wearing masks, markings on the floor separating folks from one another by six feet, and plexiglass screens by registers in checkout aisles. The online shopping experience has changed in many ways as well, with some items that had previously been taken for granted such as toilet paper, inflatable pools, and other commodities now being scarce commodities. Online retail is changing in other profound ways as consumers change their buying patterns and behaviors, with the shift to work-from-home and school-at-home changing the way people live, work, and socialize. Retail establishments that had previously counted on big Fourth of July and Labor Day celebrations, back-to-school specials, large social gatherings, and practically the whole travel and hospitality industry have had to throw out their usual sales, marketing, and supply chain practices and rethink their fundamental business strategies.
In recent years, it's become increasingly clear that Artificial Intelligence (AI) startups can scale to become $1 billion-plus companies. When it comes to innovation at the early-stages, there is a pressing need to differentiate between hype and actual potential for scale and impact. Today, many startups claim to be innovating through the use of AI. Whilst some succeed, others fail to deliver upon their promise. How does one go about cutting through the noise and identifying the AI startups that have the most potential for scale?
Modern AI has produced models that exceed human performance across countless tasks. Now, an international research team is suggesting AI might become even more efficient and reliable if it learns to think more like worms. In a paper recently published in Nature Machine Intelligence journal, the team from MIT CSAIL, TU Wien in Vienna, and IST Austria proposes an AI system that mimics biological models. The system was developed based on the brains of tiny animals such as threadworms and is able to control a vehicle using just a small number of artificial neurons. The researchers say the system has decisive advantages over other deep learning models because it copes much better with noisy input, and, because of its simplicity, its operations can be explained in detail -- alleviating the "black box" concerns affecting today's deep AI models. Explains TU Wien Cyber-Physical Systems head Professor Radu Grosu in a project press release: "For years, we have been investigating what we can learn from nature to improve deep learning.
The possibilities opened up to us by the rise of the Internet of Things (IoT) is a beautiful thing. However, not enough attention is being paid to the software that goes into the things of IoT. This can be a daunting challenge, since, unlike centralized IT infrastructure, there are, by one estimate, at least 30 billion IoT devices now in the world, and every second, 127 new IoT devices are connected to the internet. They are increasingly growing sophisticated and intelligent in their own right, housing significant amounts of local code. The catch is that means a lot of software that needs tending.