Data scientists can use MLPerf to see how fast their machine learning tools truly are

On Wednesday, a group of tech industry and academic leaders released a new benchmark to measure the speed of machine learning software and hardware and accelerate improvements in system performance. The benchmark--called MLPerf--was created by a number of tech companies including AMD, Baidu, Google, and Intel, as well as researchers from educational institutions including Harvard, Stanford, and the University of California Berkeley. MLPerf measures speed based on the time it takes to train deep neural networks to perform tasks such as recognizing objects, translating languages, and playing the game of Go. SEE: IT leader's guide to the future of artificial intelligence (Tech Pro Research) As machine learning and artificial intelligence (AI) efforts grow across the enterprise, systems need to evolve quickly to meet demands, Andrew Ng, founder and CEO of Landing.AI, said in a press release. "AI is transforming multiple industries, but for it to reach its full potential, we still need faster hardware and software," Ng said in the release.