HPE Launches Vertical AI Solutions, Dramatically Accelerates Deep Learning Training
PALO ALTO, Calif., March 21, 2018 (GLOBE NEWSWIRE) — @Hewlett Packard Enterprise (NYSE:HPE) today announced new offerings to help customers ramp up, optimize and scale artificial intelligence ( #AI) usage across business functions to drive outcomes such as better demand forecasting, improved operational efficiency and increased sales. The new offerings include: HPE Digital Prescriptive Maintenance Services, the first in a series of AI-enabled industry offerings from HPE Pointnext, which automates problem prevention and increases productivity of industrial equipment HPE Artificial Intelligence Transformation Workshop, providing consulting expertise from HPE Pointnext to help customers get started with AI, evolve their strategic data and analytics initiatives and prioritize AI use cases HPE Apollo 6500 Gen10 System, a next-generation high performance computing system purpose-built for deep learning that delivers a 3x faster model training than previous generations(1) HPE has also extended its AI partner ecosystem through a reseller agreement with WekaIO to deliver optimized storage performance in AI environments PricewaterhouseCoopers predicts the global GDP to grow 14 percent – the equivalent of $15.7 trillion – by 2030 as a result of AI, with increased labor productivity and consumer demand being the most impactful business outcomes.(2) However, while AI holds great promise, current adoption rates are low. According to Gartner’s 2018 CIO Agenda Survey, four percent of CIOs globally have implemented AI, while a further 46 percent have developed plans to do so.(3) “Global tech giants are investing heavily in AI, but the majority of enterprises are struggling both with finding viable AI use cases and with building technology environments that support their AI workloads. As a result, the gap between leaders and laggards is widening,” said Beena Ammanath, Global Vice President, Artificial Intelligence, HPE Pointnext. “HPE is best positioned to help customers make AI work for their enterprise, regardless of where they are in their AI adoption. While others provide AI components, we provide complete AI solutions from strategic advisory to purpose-built technology, operational support and a strong AI partner ecosystem to tailor the right AI solution for each organization.” AI advances maintenance from predictive to prescriptive The new HPE offerings enable customers to explore, evolve and expand AI applications aligned to their business and industry needs, accelerating time to value. HPE is introducing a series of AI industry solutions for predefined use cases, starting with HPE Digital Prescriptive Maintenance Services, delivered by HPE Pointnext. While predictive maintenance detects when an industrial equipment is likely to fail, prescriptive maintenance predicts, suggests and automates the right action to fix the problem before it causes harm. According to McKinsey Global Institute, AI-enabled asset maintenance can lead to up to 20 percent EBIT improvement in industries like electric utilities by increasing capital productivity.(4) HPE Digital Prescriptive Maintenance combines services from HPE Pointnext – such as consulting, proof of value and implementation – with technologies and reference architectures from HPE and select partners. The solution captures all relevant data sources in the enterprise, including real-time and batch data from IoT devices, data centers and the cloud. Based on both supervised learning for failure prediction and unsupervised learning for anomaly detection, HPE Digital Prescriptive Maintenance prescribes and automates actions to prevent industrial equipment failure and optimize its productivity. HPE also introduced the new HPE Artificial Intelligence Transformation Workshop that helps enterprises get started rapidly with the identification of AI use cases aligned to their business priorities. In this highly interactive one-day workshop, HPE Pointnext AI experts work with the customer’s business and technology decision makers to assess their data and advanced analytics needs and create a tailored high-level plan to accelerate the AI exploration phase towards a set of AI use case implementations.