Part of a collaboration between IBM, Empire State Development (ESD), and NY CREATES, the eight petaflop IBM POWER9-equipped AI supercomputer is configured to help enable users to explore new AI applications and accelerate economic development from New York's smallest startups to its largest enterprises. Named AiMOS (short for Artificial Intelligence Multiprocessing Optimized System in honor of Rensselaer co-founder Amos Eaton, the machine will serve as a test bed for the New York State - IBM Research AI Hardware Center, which opened on the SUNY Polytechnic Institute (SUNY Poly) campus in Albany earlier this year. The AI Hardware Center aims to advance the development of computing chips and systems that are designed and optimized for AI workloads to push the boundaries of AI performance. AiMOS will provide the modeling, simulation, and computation necessary to support the development of this hardware. "Computer artificial intelligence, or more appropriately, human augmented intelligence (AI), will help solve pressing problems, from healthcare to security to climate change. In order to realize AI's full potential, special purpose computing hardware is emerging as the next big opportunity," said Dr. John E. Kelly III, IBM Executive Vice President.

In case you missed the first round of our AI Assistants vs Chatbots blog series, here's a brief recap of the bout. With the rise of artificial intelligence, we have seen the widespread use of two automated conversation tools: AI assistants and chatbots. The differences might not be clear on first glance, but they are vast. Let's look at what happened in the first round. On the one hand, we have the chatbots.

Lines of light ranged in the nonspace of the mind, clusters and constellations of data.

Posted by Jean Ho Jean covers medicine, wellness, and mental health. Combination therapies have become a standard treatment of several complex diseases. High-throughput screening (HTS) makes it possible to profile phenotypic effects of thousands of drug combinations in patient-derived cells and other pre-clinical model systems. However, due to the massive number of potential drug and dose combinations, large-scale multi-dose combinatorial screening requires extensive resources and instrumentation, beyond the capability of most academic laboratories. Testing of hundreds of combinations is also impossible in limited cell numbers from patient samples.

Robots and artificial intelligence haven't taken over -- yet. But machines still have human-like needs, needs that, when fulfilled, can improve payments and commerce and, according to some, usher in what's sometimes being called in smart circles a new industrial revolution. The key to that future is emerging 5G mobile network technology. Sure, retailers, healthcare providers and other operations with firm footing in the digital economy are seeking, finding and crafting use cases for 5G, which, above all, promises speedier and more robust information flows among people and businesses. But machine-to-machine communication promises to play as great a role or even greater in 5G, at least according to some observers and studies.

What's New: This week at the annual Neural Information Processing Systems (NeurIPS) conference in Vancouver, British Columbia, Intel is contributing almost three dozen conference, workshop and spotlight papers covering deep equilibrium models, imitation learning, machine programming and more. "Intel continues to push the frontiers in fundamental and applied research as we work to infuse AI everywhere, from low-power devices to data center accelerators. This year at NeurIPS, Intel will present almost three dozen conference and workshop papers. We are fortunate to collaborate with excellent academic communities from around the world on this research, reflecting Intel's commitment to collaboratively advance machine learning." Research topics span the breadth of artificial intelligence (AI) topics, from fundamental understanding of neural networks to applying machine learning to software programming to particle physics.

IoT Evolution Keynoter, Schneider Electric, with Avnet and Iceotope, announce the creation of the industry's first commercially-available integrated rack with chassis-based, immersive liquid cooling. Optimized for compute-intensive applications, the solution combines a high-powered GPU server with Iceotope's liquid cooling technology to increase energy efficiency. The system is EcoStruxure Ready since the solution is available with next-generation data center management software, EcoStruxure IT Expert and digital service EcoStruxure Asset Advisor. This solution is ideal for applications such as big data analytics, artificial intelligence, and machine-learning algorithm training development, where high compute demands more energy use. In a recent report published by Gartner, liquid cooling was identified as a technology to watch.

This week marks the kickoff of Neural Information Processing Systems (NeurIPS), one of the largest AI and machine learning conferences globally. NeurIPS 2017 and NeuIPS 2018 received 3,240 and 4,854 research paper submissions, respectively, and this year's event -- which takes place from December 8 to December 14 in Vancouver -- is on track to handily break those records. Researchers from Intel will be in attendance, as will those from tech giants like Google, Facebook, Apple, Uber, Alibaba, Baidu, and countless others. For its part, the Santa Clara, California-based chipmaker said it intends to host three dozen conference, workshop, and spotlight sessions covering topics like deep equilibrium models, imitation learning, machine programming, and more. "Intel is making significant strides in advancing and scaling neural network technologies to handle increasingly complex and dynamic workloads -- from tackling challenges with memory to researching new adaptive learning techniques," wrote Dr. Rich Uhlig, senior fellow and managing director of Intel Labs, in a blog post.

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In recent years, natural language processing (NLP) has become a part of our everyday lives. Smartphones now come equipped with NLP-powered voice assistants that interpret and understand human speech in order to provide relevant responses to user queries. NLP also helps translation apps break down communication barriers by analyzing input in one language and transforming it into another language. Even word processors rely on NLP to check the grammar, logic, and syntax of written input. And NLP is now an integral part of customer service; it's used to guide people to the right representative through verbal commands. Yet, few people actually understand how NLP plays a role in making them possible.