“The recent announcement of HDR InfiniBand included the three required network elements to achieve full end-to-end implementation of the new technology: ConnectX-6 host channel adapters, Quantum switches and the LinkX family of 200Gb/s cables. The newest generations of InfiniBand bring the game changing capabilities of In-Network Computing and In-Network Memory to further enhance the new paradigm of Data-Centric data centers – for High-Performance Computing, Machine Learning, Cloud, Web2.0, Big Data, Financial Services and more – dramatically increasing network scalability and introducing new accelerations for storage platforms and data center security.”
In This Week in Machine Learning podcast, Xavier Amatriain from Quora discusses the process of engineering practical machine learning systems. Amatriainis a former machine learning researcher who went on to lead the recommender systems team at Netflix, and is now the vice president of engineering at Quora, the Q&A site. “What the heck is a multi-arm bandit and how can it help us.”
In this presentation from Nvidia, top AI experts from the world’s most influential companies weigh in on predicted advances for AI in 2017. “In 2017, intelligence will trump speed. Over the last several decades, nations have competed on speed, intent to build the world’s fastest supercomputer,” said Ian Buck, VP of Accelerated computing at Nvidia. “In 2017, the race will shift. Nations of the world will compete on who has the smartest supercomputer, not solely the fastest.”
In this a16z Podcast, Murray Shanahan, Azeem Azhar, and Tom Standage discuss the past, present, and future of A.I. as well as how it fits (or doesn’t fit) with machine learning and deep learning. “Where are we now in the A.I. evolution? What players do we think will lead, if not win, the current race? And how should we think about issues such as ethics and automation of jobs without descending into obvious extremes? All this and more, including a surprise easter egg in Ex Machina shared by Shanahan, whose work influenced the movie.”
The 3rd annual International Workshop on High-Performance Big Data Computing (HPBDC) has issued its Call for Papers. Featuring a keynote by Prof. Satoshi Matsuoka from Tokyo Institute of Technology, the event takes place May 29, 2017 in Orlando, FL.
“The AI is going to flow across the grid — the cloud — in the same way electricity did. So everything that we had electrified, we’re now going to cognify. And I owe it to Jeff, then, that the formula for the next 10,000 start-ups is very, very simple, which is to take x and add AI. That is the formula, that’s what we’re going to be doing. And that is the way in which we’re going to make this second Industrial Revolution. And by the way — right now, this minute, you can log on to Google and you can purchase AI for six cents, 100 hits. That’s available right now.”
In this AI Podcast, Bob Bond from Nvidia and Mike Senese from Make magazine discuss the Do It Yourself movement for Artificial Intelligence. “Deep learning isn’t just for research scientists anymore. Hobbyists can use consumer grade GPUs and open-source DNN software to tackle common household tasks from ant control to chasing away stray cats.”
In this Intel Chip Chat, Doug Fisher from Intel describes the company’s efforts to accelerate innovation in artificial intelligence. “Fisher talks about Intel’s upstream investments in academia and open source communities. He also highlights efforts including the launch of the Intel Nervana AI Academy aimed at developers, data scientists, academia, and startups that will broaden participation in AI. Additionally, Fisher reports on Intel’s engagements with open source ecosystems to optimize the performance of the most-used AI frameworks on Intel architecture.”
“The Materials Project is harnessing the power of supercomputing together with state-of-the-art quantum mechanical theory to compute the properties of all known inorganic materials and beyond, design novel materials and offer the data for free to the community together with online analysis and design algorithms. The current release contains data derived from quantum mechanical calculations for over 60,000 materials and millions of properties.”
With the advent of heterogeneous computing systems that combine both main CPUs and connected processors that can ingest and process tremendous amounts of data and run complex algorithms, artificial intelligence (AI) technologies are beginning to take hold in a variety of industries. Massive datasets can now be used to drive innovation in industries such as autonomous driving systems, controlling power grids and combining data to arrive at a profitable decision, for example. Read how AI can now be used in various industries using the latest hardware and software.