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Blog

More and more places and things are now starting to recognize you

Facial recognition is one of the popular applications of computer vision technology that deals with recognizing identity of a person. The technology has been in use for several years with varying degree of accuracy. Classic facial recognition techniques, such as SIFT (Scale Invariant Feature Transform) and SURF (Speeded Up Robust Features), relied on extracting unique features of face. These techniques relied on comparing values of the incoming picture with a reference picture to generate a match. While this worked fairly…

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Is AI the best news for semiconductor industry since microprocessors?

Note: This blog was published via Tractica in 2017. Microprocessors form the basis of any computer system. Whether the device is used for IoT, consumer or cloud, the microprocessor chip is there that acts as a brain. In fact, Semiconductor industry owes its success to microprocessor when Intel introduced 4004 back in the 70s. That later evolved into 808X series leading to widespread adaption of chips. Even today, microprocessors get more coverage than other types of chipsets in the media.…

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(More and more) Deep Learning Chipset Companies Are Coming Out of Stealth Mode

Artificial intelligence (AI) applications are hot and everyone is trying to capitalize on the buzz. It is not surprising that everyone wants better, cheaper hardware that gives them the best performance for their AI application. Ultimately, this boils down to the chipset that runs the underlying algorithms, which has sparked an intense race to win the hardware battle. Note: This was published via Tractica in 2017 Deep learning technology is, by far, the most popular type of neural network used…

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Machine Learning coming to a cloud near you

Note: This blog was published via Tractica in 2017 The popularity of artificial intelligence (AI) technology has led to application developers demanding more compute power. AI applications come in different shapes and sizes, so the need for compute performance varies quite a bit. Training and inference also have different performance requirements. The training phase requires higher compute performance capacity, while lower compute performance suffices for inference. Compute performance needs can range from a personal computer (PC) with a graphics card,…

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