Tag: machine learning
The latest scientific evidence indicates that the universe is expanding at an accelerating rate and that so-called dark energy is the driver behind this growth. Even though it comprises roughly two-thirds of the universe, not much is known about dark energy because it cannot be directly observed.
A new report from the Office of Science Technology Policy (OSTP) addresses the fast-growing field of artificial intelligence (AI), which is increasingly poised to reshape the way we live and work. Titled “Preparing for the Future of Artificial Intelligence,” the report makes 23 policy recommendations on a number of topics concerned with the best way to harness the power of machine learning and algorithm-driven intelligence for the benefit of society.
Amazon Web Services has seeded its cloud with Nvidia Tesla K80 GPUs to meet the growing demand for accelerated computing across an increasingly-diverse range of workloads. The P2 instance family is a welcome addition for compute- and data-focused users who were growing frustrated with the performance limitations of Amazon’s G2 instances, which are backed by three-year-old Nvidia GRID K520 graphics cards.
Stanford researchers are leveraging GPU-based machines in the Amazon EC2 cloud to run deep learning workloads with the goal of improving diagnostics for a chronic eye disease, called diabetic retinopathy. The disease is a complication of diabetes that can lead to blindness if blood sugar is poorly controlled. It affects about 45 percent of diabetics and 100 million people worldwide, many in developing nations.
If we needed another sign that Intel is serious about mining AI market opportunities, it came today when the chip company announced it had inked a “definitive agreement” to acquire artificial intelligence and deep learning company Nervana Systems. Financial terms haven’t been disclosed yet, but a source familiar with the deal told Recode it’s worth more Read more…
From ISC 2016 in Frankfurt, Germany, this week, Intel Corp. announced that its new Xeon Phi product family, formerly code-named Knights Landing, is now shipping for high-performance computing and machine learning workloads. The company had been shipping to early customers for the last six months and was waiting to ramp up production before making the product generally available. The window also gave OEMs time to complete their readiness, said Intel’s Charlie Wuischpard.
Greg Diamos, senior researcher, Silicon Valley AI Lab, Baidu, is on the front lines of the reinvigorated frontier of machine learning. Before joining Baidu, Diamos was in the employ of NVIDIA, first as a research scientist and then an architect (for the GPU streaming multiprocessor and the CUDA software). Given this background, it’s natural that Diamos’ research is focused on advancing breakthroughs in GPU-based deep learning. Ahead of a paper he is presenting at the 33rd International Conference on Machine Learning, Diamos answered questions about his research and his vision for the future of machine learning.
Developing effective tools against cancer has been a long, complicated endeavor with successes and disappointments. Despite all, cancer remains the leading cause of death worldwide. Now, machine learning and data analytics are being recruited as tools in the effort fight the disease and show significant promise according to two recent papers. In one paper – An Analytics Approach to Designing Combination Chemotherapy Regimens for Cancer – researchers from MIT and Stanford “propose models that use machine learning and optimization to suggest regimens to be tested in phase II and phase III trials.”
Recently, the 2016 GPU Technology Conference (GTC16) was held in Silicon Valley. Inspur released the Caffe-MPI, a multi node parallel version open source framework for Deep Learning. Meanwhile, Inspur also announced its plan to launch a Deep Learning Speedup Program(DLSP), aiming at facilitating the accelerated development and efficient application of Deep Learning – from the Read more…
Deep learning has inspired a gold rush of technology innovation across a wide range of markets from Internet search, to social media, to real-time robotics, self-driving vehicles, drones and more. Spanning the gamut of machine performance, deep learning (and machine learning in general) encompasses floating-point-, network- and data-intensive ‘training’ plus real-time, low-power ‘prediction’ operations. Intel® Read more…