Facebook on Monday began using artificial intelligence to help people with visual impairments enjoy photos posted at the leading social network. Facebook introduced machine learning technology trained to recognize objects in pictures and then describe photos aloud. "As Facebook becomes an increasingly visual experience, we hope our new automatic alternative text technology will help the blind community experience Facebook the same way others enjoy it," said accessibility specialist Matt King. The feature was being tested on mobile devices powered by Apple iOS software and which have screen readers set to English. Facebook planned to expand the capability to devices with other kinds of operating systems and add more languages, according to King, who lost his vision as a US college student studying electrical engineering.

SAN JOSE, CA--(Marketwired - Apr 5, 2016) - GPU Technology Conference -- NVIDIA (NASDAQ: NVDA) today announced that it is a founding technology partner of the MGH Clinical Data Science Center, which aims to advance healthcare by applying the latest artificial intelligence techniques to improve the detection, diagnosis, treatment and management of diseases. Massachusetts General Hospital -- which conducts the largest hospital-based research program in the United States, and is the top-ranked hospital on this year's US News and World Report "Best Hospitals" list -- recently established the MGH Clinical Data Science Center in Boston. The center will train a deep neural network using Mass General's vast stores of phenotypic, genetics and imaging data. The hospital has a database containing some 10 billion medical images. To process this massive amount of data, the center will deploy the NVIDIA DGX-1 -- a server designed for AI applications, launched earlier today at the GPU Technology Conference -- and deep learning algorithms created by NVIDIA engineers and Mass General data scientists.

The field of artificial intelligence has experienced a striking spurt of progress in recent years, with software becoming much better at understanding images, speech, and new tasks such as how to play games. Now the company whose hardware has underpinned much of that progress has created a chip to keep it going. On Tuesday Nvidia announced a new chip called the Tesla P100 that's designed to put more power behind a technique called deep learning. This technique has produced recent major advances such as the Google software AlphaGo that defeated the world's top Go player last month (see "Five Lessons from AlphaGo's Historic Victory"). Deep learning involves passing data through large collections of crudely simulated neurons.

Linglong Kong (mathematical and statistical sciences) is the co-lead of a new collaboration of 18 researchers across North America working together to improve the way neuroimaging data is analyzed. In the hands of the right reader, it may prove to be a very important one--such as the likelihood of a particular patient developing a neurological disorder like dementia or responding positively to a new treatment for depression or ADHD. Recent rapid innovations in technology have enabled the unprecedented collection of complex neuroimaging data to measure different perspectives on brain structures and functions. This information-rich data offers incredible potential to investigate neurological and psychiatric diseases, trace neural network changes of various disorders and understand the inner workings of the human brain--helping lay the foundation for a future with more precise, patient-specific medical treatment options. Some of the more complicated problems involve integrating complementary sources of information--such as those that arise from studies that collect data using multiple neuroimaging modalities simultaneously, or studies that aim to combine brain imaging with genomics.

This article is about the launch of a new SaaS offering called Synference. It is a combination of machine learning and A/B testing. In a nutshell, it will run your A/B tests through their API and use basic user data garnered from IP addresses and user agents to help you make decisions about what to charge your customers or clients. As the API receives user feedback -- was the banner clicked, did the customer pay, etc -- Synference detects patterns of user behavior and updates its statistical model accordingly.

As artificial intelligence sweeps across the technology landscape, NVIDIA unveiled today at its annual GPU Technology Conference a series of new products and technologies focused on deep learning, virtual reality and self-driving cars.

What's striking in these discussions is regardless of whether you fear or love AI bots, our future with them is inevitable. People are excited about Bots, both physical and digital, because they are the next wave of industrial revolution. Industrial revolutions are not defined by individual technological improvements, but changes in labor and distribution. During the 1st and 2nd industrial revolutions, many things were invented; from looms to steam engines to new smelting iron techniques. It was an Industrial Revolution because goods were no longer produced by human hands, but could be primarily outsourced to machines and manufacturing processes.

The sophisticated neural networks underlying systems like Google's Deep Dream and all manner of interesting experiments require a great deal of computing power. NVIDIA proposes to put all that horsepower in a single box, specially engineered to meet the needs of AI researchers. NVIDIA already has GPUs specializing in deep learning applications, so this was a logical next step. It's called the DGX-1, and it's basically a fancy enclosure for an 8-GPU supercomputing cluster. There are 8 Tesla P100 cards in there with 16 GB of RAM each, plus 7 TB of storage for all the raw data you'll be training your networks on.

George Hotz, the latest Silicon Valley startup founder to get a multimillion-dollar check from venture capitalists, went for a ride in a Rolls-Royce around San Francisco on Monday. At 26, Hotz thinks he could teach the legendary vehicle a few tricks. Braking should be smoother, he says. The vehicle should run each time as if the best limo driver in the world was behind the wheel. "You don't want the champagne to spill," Hotz says.

The move from humans working with computers to computers working without humans is almost upon us, and some are already calling it Industry 4.0 – or the fourth industrial revolution. For those not keeping up with your industrial revolutions, the first was considered launched by the use of steam and water power, the second by the use of electricity, and the third by the introduction of computers in the workplace. The name Industry 4.0 was first coined by the German Government, and represents the implementation of artificial intelligence, big data, and the industrial Internet of Things (IIoT) in the factories. It might be the first revolution where humans are not required, according to some. Once computers can talk to each other and automate the assembly line, and AI can understand issues and address them ahead of time, there might be no need for humans.