Only 7 percent of patients live five years after diagnosis of pancreatic cancer, the lowest rate for any cancer, according to the American Cancer Society. Elliot K. Fishman, MD, a researcher and radiologist at Johns Hopkins, is on the forefront of trying to change this statistic, and he's using artificial intelligence to do it. Fishman aims to spot pancreatic cancers far sooner than humans alone can by applying GPU-accelerated deep learning artificial intelligence to the task. Johns Hopkins is suited to developing a deep learning system because it has the massive amounts of data on pancreatic cancer needed to teach a computer to detect the disease in a CT scan. Hospital researchers also have NVIDIA's DGX-1 AI Supercomputer.

Next week, scientists working on artificial intelligence (AI) and games will be watching the latest human-machine matchup. But instead of a single pensive player squaring off against a computer, a team of five top video game players will be furiously casting magic spells and lobbing (virtual) fireballs at a team of five AIs called OpenAI Five. They'll be playing the real-time strategy game Dota 2 at The International in Vancouver, Canada, an annual e-sports tournament that draws professional gamers who compete for millions of dollars. In 1997, IBM's Deep Blue AI bested chess champion Garry Kasparov. In 2016, DeepMind's AlphaGo AI beat Lee Sedol, a world master, at the traditional Chinese board game Go.

Intel has an ambition to bring more artificial intelligence technology into all aspects of its business, and today is stepping up its game a little in the area with an acquisition. The computer processing giant has acquired Vertex.AI, a startup that had a mission of making it possible to develop "deep learning for every platform", and had built a deep learning engine called PlaidML to do this. Terms of the deal have not been disclosed but Intel has provided us with the following statement, confirming the deal and that the whole team -- including founders Choong Ng and Brian Retford -- will be joining Intel. "Intel has acquired Vertex.AI, a Seattle-based startup focused on deep learning compilation tools and associated technology. The seven-person Vertex.AI team joined the Movidius team in Intel's Artificial Intelligence Products Group. With this acquisition, Intel gained an experienced team and IP to further enable flexible deep learning at the edge. Additional details and terms are not being disclosed."

Tensorflow, developed by Google, has become the most popular framework for deep learning, and now operates on a variety of devices including multicore CPUs, general purpose GPUs, mobile devices, and custom ASICs. In this on-demand webinar hosted by Intel and ActiveState, you'll get a general introduction to working with Tensorflow and its surrounding ecosystem, general problem classes, where you can get big acceleration, and why you should be running on a CPU.

Vertex.AI is now part of Intel's Artificial Intelligence Products Group. Intel plans to continue developing PlaidML as an open source project, and we will shortly transition it to the Apache 2.0 license. Supporting a variety of hardware will continue to be a priority for the PlaidML project, which Intel will further develop as an Intel nGraph backend. We are excited to advance flexible deep learning for edge computing as part of Intel. If you are interested in joining us, Intel is hiring AI experts, including here in Seattle.

The team achieved a peak rate between 11.73 and 15.07 petaflops (single-precision) when running its data set on the Cori supercomputer. Machine learning, a form of artificial intelligence, enjoys unprecedented success in commercial applications. However, the use of machine learning in high performance computing for science has been limited. Why? Advanced machine learning tools weren't designed for big data sets, like those used to study stars and planets. A team from Intel, National Energy Research Scientific Computing Center (NERSC), and Stanford changed that.

Google's AI division is making artificial intelligence more alien, a copy of Fahrenheit 451 you need to burn to read and the arrival of Windows Mixed Reality headsets - this is what you might have missed this week in tech news.Oct.21.2017

Deep learning is much more like the human brain than is machine learning. Consider the way your brain interprets faces, for example. Your conscious self recognizes the whole face as a distinct person by interpreting the relationships between the parts at an astounding pace. You can't label each relationship it has identified, or even quantify and write out the variables your brain is interpreting. These things happen without your knowledge, so to speak.

Artificial intelligence can diagnose eye disease as accurately as some leading experts, research suggests. A study by Moorfields Eye Hospital in London and the Google company DeepMind found that a machine could learn to read complex eye scans and detect more than 50 eye conditions. Doctors hope artificial intelligence could soon play a major role in helping to identify patients who need urgent treatment. They hope it will also reduce delays. A team at DeepMind, based in London, created an algorithm, or mathematical set of rules, to enable a computer to analyse optical coherence tomography (OCT), a high resolution 3D scan of the back of the eye.

Supercomputer manufacturer Cray has introduced a new set of four artificial intelligence (AI) products to accelerate the adoption of deep learning in science and enterprise. The new products include Cray Accel AI Lab, which aims to advance the development of deep learning technologies and workflows, and Cray Accel AI Offerings, featured with NVIDIA Tesla V100 GPU accelerators. The new Cray Urika-XC software suite, which brings graph analytics, deep learning, and big data analytics tools the Cray XC supercomputers, will now include the TensorFlow computational framework and enhancements to the Cray software environment that are particularly designed to accelerate machine learning frameworks. Also included is a collaboration agreement with Intel. The Cray-Intel team up will deliver a productised software stack for deep learning at scale on Cray systems and leverage Intel's AI technologies to advance the state-of-the-art in distributed deep learning and machine learning.