Boltt: Boltt fitness wearables is a step ahead in technological innovation. We have developed a way to do away with fragmented fitness solutions and are introducing intuitive'connected solutions.' Artificial Intelligence is the next step in every segment, and it is evident from the way tech giants have been involved in its development which also indicates it to be a space which still has a lot unexplored. We have thereby put our efforts in discovering the capabilities of AI technology, and we were thrilled to see its magnanimity. The industry today is heaped with wearable fitness brands which evidently lacks in offering personal coaching.

"The Next Voice You Hear Will Be Your Own" – Jackson Browne You know how things can sneak up on you, particularly trends. There are dribs and drabs and all of a sudden a swirling tornado of evidence that something is happening? I have had that experience these last few weeks with a realization that the phenomenon of voice will likely be the next meaningful user interface in healthcare. We may all be excited by man-made artifacts like artificial intelligence (AI), virtual reality (VR), 3D, and a multiplicity of other two-letter acronyms that spring from the minds of engineers, but the natural human thing that is our voice may well be the most interesting 200,000-year overnight sensation to bring meaning to medicine. I remember back as far as college, when dinosaurs still roamed the earth and iPhones were just a twinkle in Steve Jobs' eye, that I took part in some student experiments about voice recognition technology that were largely absurd in their lack of utility. Yes, occasionally by shouting at your phone you could find your way to Sand Hill Road, but more likely it would instead offer you the mating habits of the sandy toad.

Machine learning is all about faster processing of massive amounts of data, no? Take the new iPhone camera for example. It has an image signal processor (ISP) enhanced by machine learning that makes editing photos more intelligent.

Ten thousand creatives and designers, have descended on San Diego for the annual pilgrimage that is Adobe Max, showcasing the 2017 updates to its all-powerful Creative Cloud suite of software. Principal among its announcements was Adobe Sensei, the company's latest foray into artificial intelligence that will work across all three of its clouds – Document, Marketing and Creative. According to Adobe, Sensei (the Japanese word for teacher) is a new framework and set of intelligent services for dramatically improving the design and delivery of digital experiences. Adobe Sensei's intelligent services tackle today's complex experience challenges – including image matching across millions of images, understanding the meaning and sentiment of documents and finely targeting important audience segments – leveraging machine learning, artificial intelligence (AI) and deep learning capabilities. This announcement builds upon the machine learning capabilities unveiled in Adobe Marketing Cloud at Adobe Summit in March.

Machine learning is often thought to be too complicated for everyday development tasks. I have always felt like we can benefit from using machine learning for simple tasks that we do regularly. At Mailgun, we work with e-mail and as part of our offering, we parse HTML quotations. This allows a user to grab the latest reply instead of the entire conversation, which is returned as part of our webhook response. For those of you who don't know, here's what parsing HTML from the public Internet looks like: Changing the parsing library can help, but it won't solve the issue completely because every library has its limitations.

In-memory data store Redis recently acquired a module architecture to expand functionality. The latest module is a machine learning add-on that accelerates delivery of results from trained data rather than training itself. Redis-ML, or the Redis Module for Machine Learning, comes courtesy of the commercial outfit that drives Redis development, Redis Labs. It speeds the execution of machine learning models while still allowing those models to be trained in familiar ways. Redis works as an in-memory cache backed by disk storage, and its creators claim machine learning models can be executed orders of magnitude more quickly with it.

In recent years, there has been a big leap in machine learning due to the capabilities of graphic processing units (GPUs) evolving at lightning speed. Even though machine learning is never going to be exactly human-like, we are getting closer in a few areas, like imagenet large scale challenge, where the error rates are on par with or better than humans. A recent announcement of SAP human resources implementing bias filters is another great example of machine learning performing better than humans. Machine learning promises a next wave of innovations for every application, business process, and interaction of the enterprise with its customers. To disrupt, companies need to have a "machine learning-first" mentality to differentiate them in the marketplace.

Leveraging its machine learning, artificial intelligence (AI) and deep learning capabilities, software major Adobe Systems has unveiled Adobe Sensei -- a new framework and set of intelligent services that improve the design and delivery of digital experiences -- at its ongoing annual creativity conference here. Adobe "Sensei", which means "master" or "teacher" in Japanese, tackles complex experience challenges, including image matching across millions of images, understanding the meaning and sentiment of documents and finely targeting important audience segments. "Adobe Sensei is uniquely focused on solving today's complex experience challenges in the design, document and marketing fields, where only Adobe has decades of expertise and market leadership," Shantanu Narayen, President and CEO of Adobe said on Wednesday. "Leveraging our machine learning and AI capabilities, as well as trillions of content and data assets, Adobe Sensei will be one of our biggest strategic investments. We're excited to open it up to our broader ecosystem of partners, ISVs and developers to enable even more innovation," he added. Adobe Sensei, unveiled at the Adobe Max 2016 creativity conference, includes a unified AI/machine learning framework that power Creative Cloud, Adobe Document Cloud and Adobe Marketing Cloud and automates mundane tasks, drive predictive and personalization capabilities and boost productivity.

NEC Corporation has launched a new software program that uses artificial intelligence (AI) in video footage search to quickly identify a person by facial recognition. NeoFace Image Data Mining (Idm) is a new product offering from NEC that can use video footage, for example, data gathered by CCTV cameras, and scan it to accurately identify an individual whose image is captured on camera. It can also be used to search for people who appear at a certain time and place, or who appear with other specified individuals. A complete search for a specific person among one million captured images can be concluded in under 10 seconds. Idm combines existing facial recognition technology with profiling parameters – what NEC refers to as'Profiling Across Spatio-Temporal Data' technology.