Consumer adoption of artificial intelligence-powered virtual assistants will increase, but some brands don't see the capabilities fully replacing humans. The number of active users of virtual assistants will grow to 2 billion consumers in 2021, up from 390 million last year, according to new research from Tractica. Global revenue generated by virtual assistants will grow to 16 billion by 2021, up from 2 billion last year. The majority (75%) of revenues will come from the consumer side of the market, according to Tractica. The Asia Pacific region will lead the market in revenue and multiply in value by 10 times to account for more than 5 billion by 2021. "The consumer and enterprise use cases for virtual digital assistants are proliferating rapidly thanks to accelerated innovation and scalability of underlying technologies, such as natural language processing and artificial intelligence," Mark Beccue, principal analyst at Tractica, said in a statement.

There's no human instinct more basic than speech, and yet, for many people, talking can be taxing. Unfortunately, many behaviorally-based voice disorders are not well understood. In particular, patients with muscle tension dysphonia (MTD) often experience deteriorating voice quality and vocal fatigue ("tired voice") in the absence of any clear vocal cord damage or other medical problems, which makes the condition both hard to diagnose and hard to treat. But a team from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and Massachusetts General Hospital (MGH) believes that better understanding of conditions like MTD is possible through machine learning. Using accelerometer data collected from a wearable device developed by researchers at the MGH Voice Center, researchers demonstrated that they can detect differences between subjects with MTD and matched controls.

Today, Facebook is announcing new recipients to the GPU Partnership Program announced earlier this year. This program, fashioned with the goal of helping others make faster progress in the field of AI, is intended to overcome a large challenge, ensuring the world's top researchers have the infrastructure, tools and techniques to solve some of the largest technical problems. To help accomplish this, we are distributing 22 high-powered GPU servers to 15 world-class research groups across 9 European countries. The Facebook AI Research (FAIR) team will also work with recipients to ensure they have the software required to run the servers as well as directly collaborate with them in their ongoing research efforts. FAIR is well known for its open research efforts, and the insights from the GPU program are intended to be shared with the global scientific community.

When it comes to enterprise customer care, machine learning enables Virtual Assistant solutions to automate tasks that used to require a live agent: password resets; address and complex information collection; even sales support. Integrating machine learning into enterprise customer care opens doors to more flexible automated solutions. It also frees up live agents to focus on handling complex or revenue-generating tasks. With the growing challenges and volume of customer interactions that most companies' must handle, that flexibility, efficiency, and accuracy is exactly what's needed. With a little help and vetting from the IT department, the contact center can take enterprise customer care to the next level.

A recent study found computer software was able to intuitively translate patient charts into diagnostic information with 99 percent accuracy at 30 times the speed of doctors.

Earlier this summer, humans submitted their selfies and computer scientists submitted their algorithms to be competitors and judges in the first beauty contest judged by artificial intelligence. The six AI judges were trained to evaluate wrinkles, face symmetry, skin color and several other parameters before choosing men and women winners in various age groups ranging from 18 to 69. A total of 60,000 people submitted their selfies, and the winners have been chosen. It actually stemmed from a project that involves using AI to evaluate health and hopefully slow aging in the future.

As the world's foremost event covering the practical implications of AI for enterprise organizations and solutions, more than 600 business CxOs are attending alongside AI start-up innovators, media and acclaimed researchers. The AI Summit's elite content program offers exclusive insights into the future world of AI-empowered businesses. Inbenta Chief Operating Officer and previous CTO, Ferran Saurina, will join a leading panel session highlighting customer engagement solutions that serve as entry points for any business. "AI is happening in most, if not all industries; and the number one consumer applications is through chatbots. Savvy companies aren't asking if their business needs a bot, but how they should be integrated. September 28th at 5:25 pm - 6:10 pm Panel Debate: What does a business leader need to know when choosing a partner for AI? A number of leading organizations spanning finance, law, healthcare, manufacturing, transport, energy, education and many more are looking to implement the technologies or have already started. The conference programs include exclusive announcements on AI Projects from American Airlines, Capital One, UBER, General Electric, Wells Fargo, Navistar, BMS, Johnson & Johnson and many more. "AI is being implemented by leading organizations in a broad range of industries and we are very excited to host Inbenta, alongside key industry names that include Amazon, Facebook, Google, IBM Watson, Microsoft, Tata and Accenture,'' underlines Daniel Pitchford, Commercial Director, The AI Summit.

Due to the recent achievements of artificial neural networks across many different tasks (such as face recognition, object detection and Go), deep learning has become extremely popular. This post aims to be a starting point for those interested in learning more about it. If you already have a basic understanding of linear algebra, calculus, probability and programming: I recommend starting with Stanford's CS231n. The course notes are comprehensive and well-written. The slides for each lesson are also available, and even though the accompanying videos were removed from the official site, re-uploads are quite easy to find online.

Either a comprehensive list, or some combination of these AI technologies, can help implement AI systems or AI like systems/applications or increase an application's "intelligent" behavior somewhat.

A new speech recognition system can transcribe English or Mandarin about three times faster than humans can type on a smartphone, according to a recent study. SEE ALSO: Mark Zuckerberg's First Stop in China: Baidu Headquarters The study, a collaboration between Stanford University, Baidu and the University of Washington, also found that the system produced 20.4 percent fewer errors than people typing in English and 63.8 percent fewer than people working in Mandarin. "We're putting speech recognition up against people who are really good at this task," study co-author James Landay told Stanford News. The system produced 20.4 percent fewer errors than people typing in English and 63.8 percent fewer than people working in Mandarin.