Big Data

By Purna Mohanty, VP Engineering and Operations USA, Tessolve Introduction: With the latest progress in cloud-based computing, emerging data science, and real time applications for AI, deep learning, and machine learning, the way we used to develop System-on-Chip (SoC) in the late ’90s is not the same any longer. Architectural exploration has become a key ingredient of the any SoC that requires highest performance with the lowest power consumption. We need engineers that think differently, even at the implementation level, who have the ability to think beyond their normal call of duty – to think at a system level and Read More

Dr. Theo Vassilakis, Founder and CEO, Metanautix Dr. Pravin Fulay, Associate Vice President, TechMahindra Globalization has been a boon to the semiconductor industry. With Fabless on the rise and outsourced manufacturing dominated by low cost countries, the industry is experiencing critical changes.  Integrating information about the physical supply chain with information about the data supply chain will be a key differentiator.  Global visibility across the supply chain is one of the key challenges which determines the success of product manufacturing.  By performing rapid supply chain analytics across data silos, companies can collaborate effectively, work seamlessly, innovate better, reduce costs and Read More

Charlie Cheng, President and CEO, Kilopass Technology Inc. The simple demarcation of “Big Data” for large organizations and “Little Data” for individual companies seems simple enough until one examines the motivation of the data. Then it becomes quite clear that the “Big Data” problem can be solved quite elegantly through traditional branches of computer science, riding on the shoulders of semiconductor advances. Equally clear, though, is how ill-defined the “Little Data” problem is, and how much more challenging it is to solve “the” problem. The “Little Data” problem is one of artificial intelligence, with the Internet enriched (or cluttered) by Read More

Sanjay Ravi, Worldwide Managing Director for Discrete Manufacturing, Microsoft Corp. Manufacturing executives are seeing big results from big data. The capacity to mine and manage data by connecting factory floors, enterprise IT and analytics software creates one holistic, intelligent system—and it’s empowering companies around the world. Data is the new currency for manufacturers and when companies bring together four big Vs of big data—velocity, volume, variety and value—they are realizing the “Data Dividend” and can witness the transformative effect of this technology. The ability to analyze all this data is making manufacturers more productive, enabling them to transform their business Read More