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IBM touts improved distributed training time for visual recognition models

Published August 8, 2017

 Two months ago, Facebook’s AI Research Lab (FAIR) published some impressive training times for massively distributed visual recognition models. Today IBM is firing back with some numbers of its own. IBM’s research groups says it was able to train ResNet-50 for 1k classes in 50 minutes across 256 GPUs — which is just the polite way of saying “my model trains faster than… Read More

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Facebook finishes its move to neural machine translation

Published August 3, 2017

 Facebook announced this morning that it had completed its move to neural machine translation — a complicated way of saying that Facebook is now using convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to automatically translate content across Facebook. Read More

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A discussion about AI’s conflicts and challenges

Published June 17, 2017

 “The competition for talent at the moment is absolutely ferocious,” agrees Professor Andrew Blake, whose computer vision PhD was obtained in 1983, but who is now, among other things, a scientific advisor to UK-based autonomous vehicle software startup, FiveAI, which is aiming to trial driverless cars on London’s roads in 2019… Read More

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Facebook is speeding up training for visual recognition models

Published June 8, 2017

 Every minute spent training a deep learning model is a minute not doing something else, and in today’s fast-paced world of research, that minute is worth a lot. Facebook published a paper this morning detailing its personal approach to this problem. The company says it has managed to reduce the training time of a ResNet-50 deep learning model on ImageNet from 29 hours to one. Read More

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Google is giving a cluster of 1,000 Cloud TPUs to researchers for free

Published May 17, 2017

 At the end of Google I/O, the company unveiled a new program to give researchers access to the company’s most advanced machine learning technologies for free. The TensorFlow Research Cloud program, as it will be called, will be application based and open to anyone conducting research, rather than just members of academia. If accepted, researchers will get access to a cluster of 1,000… Read More

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Riminder uses deep learning to better match people to jobs

Published May 15, 2017

 There’s nothing efficient about sorting through 30,000 resumes by hand. Recruiters spend months evaluating applicants only to have great prospective candidates get lost in the pile. At TechCrunch’s Startup Battlefield, French startup Riminder made the case for how its deep learning-powered platform could augment recruiters — helping them better surface ideal contenders for… Read More

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Bitfusion raises $5M for its AI lifecycle management platform

Published May 2, 2017

 When Bitfusion launched in 2015, its focus was on helping developers speed up their applications by giving them pre-compiled libraries that made better use of GPUs, FPGAs and other co-processing technologies. That was then. Today, the hottest market for these technologies is in training deep learning models. Unsurprisingly, that’s exactly what Bitfusion is focusing now. Read More

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Gamalon leverages the work of an 18th century reverend to organize unstructured enterprise data

Published February 15, 2017

Red and white dice casting shadows on grey surface It’s hard to fathom that the work of Reverend Thomas Bayes is still coming back to drive cutting edge advancements in AI, but that’s exactly what’s happening. DARPA-backed Gamalon is the latest carrier of the Bayesian baton, launching today with a solution to help enterprises better manage their gnarly unstructured data. The world of enterprise is full of… Read More

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