Jocelyn Chen

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DT42: Bring Visual Intelligence to Edge Devices

We know that A.I. has been really smart that it can even beat human in Go. However, why A.I. is not broadly used in our life yet? The reason we believe is that, there is still a gap between the researchers developed in the lab and real applications. The A.I. computation is costly, both in money and computing resources. The key to bring intelligence to life has to be the combination of senior engineering and research energy. We want to use our expertise to eliminate the barrier and to bring A.I. to real life.

At DT42, we focus on bringing intelligence to devices. DT42 started doing embedded intelligence in 2016 and has achieved the state-of-art performance of deep learning on Raspberry Pi 3 and TX1. Our solution - Epeuva make A.I small. We provide robust visual recognition system that can run on edge devices. So devices can recognize people, faces and actions (such as violent motion). With Epeuva, we can turn internet of things into Intelligence of things.

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