Thomas LaRock wrote up a post about AI, Deep Learning, and Machine Learning. These sophisticated tools allow for automation of a lot of work we thought might only ever be done by humans. But Thomas outlines why he’s not waiting for SkyNet quite yet.
Need to do some neural network inferencing on the edge? Intel just released the Intel Neural Compute Stick 2, a $99 USB-powered device with a 16-core vision processing unit.
The terms training and inferencing get thrown around a lot with machine learning, but what do they actually mean? This video by Thomas Henson breaks down the concepts.
Let’s face it, AI gets thrown around a lot in the enterprise these days. It often gets conflated with Machine Learning, Deep Learning, and neural networks. But does the term actually mean anything? Are there solutions out there that actually qualify as AI? The roundtable debates.
Neural networks use immense datasets to train against. While these are very sophisticated, they also prove to be brittle against outliers. A recent piece by researcher Janelle Shane shows just how problematic the presence (or lack thereof) of humble sheep can prove.
It’s become common now for IT companies to list deep learning algorithms as a major platform feature, from analytics to automation. But home does deep learning compare to actual human intelligence? Ray Lucchesi looked at some of its issues in the context of the MIT Intelligence Quest.