In this contributed article, Mohammad Musa, Founder & CEO of Deepen AI, discusses how good data labeling leads to better results, whether it’s in autonomous cars, medical imaging, or any other industry where AI thrives. Done poorly, the entire system suffers. Inefficiencies and inaccuracies become inevitable, while major safety risks caused by poor labeling can derail an entire project.
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Industry Perspectives
Embracing and Leveraging the Data-Driven Pressure in Industry 4.0
In this special guest feature, John Joseph, CEO & Co-founder of Datanomix, explores why real-time actionable manufacturing data is needed for the entire organization to determine the true quote to cost value, how leveraging data analytics that can be learned, consumed, and responded to in seconds, not minutes or hours will set factories ahead – especially post COVID-19, and how to leverage data to make smarter business decisions and better quote to cash estimates.
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Interview: Global Technology Leader PNY
The following whitepaper download is a reprint of the recent interview with our friends over at PNY to discuss a variety of topics affecting data scientists conducting work on big data problem domains including how “Big Data” is becoming increasingly accessible with big clusters with disk-based databases, small clusters with in-memory data, single systems with in-CPU-memory data, and single systems with in-GPU-memory data. Answering our inquiries were: Bojan Tunguz, Senior System Software Engineer, NVIDIA and Carl Flygare, NVIDIA Quadro Product Marketing Manager, PNY.
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