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A few years back, DeepMind’s Demis Hassabis famously prophesized that AI and neuroscience will positively feed into each other in a “virtuous circle.” If realized, this would fundamentally expand our insight into intelligence, both machine and human.

We’ve already seen some proofs of concept, at least in the brain-to-AI direction. For example, memory replay, a biological mechanism that fortifies our memories during sleep, also boosted AI learning when abstractly appropriated into deep learning models. Reinforcement learning, loosely based on our motivation circuits, is now behind some of AI’s most powerful tools.

Hassabis is about to be proven right again.

A little over a year ago, Caltech’s Lihong Wang developed the world’s fastest camera, a device capable of taking 10 trillion pictures per second. It is so fast that it can even capture light traveling in slow motion.

But sometimes just being quick is not enough. Indeed, not even the fastest camera can take pictures of things it cannot see. To that end, Wang, Bren Professor of Medical Engineering and Electrical Engineering, has developed a that can take up to 1 trillion pictures per second of transparent objects. A paper about the camera appears in the January 17 issue of the journal Science Advances.

The technology, which Wang calls phase-sensitive compressed ultrafast photography (pCUP), can take video not just of transparent objects but also of more ephemeral things like shockwaves and possibly even of the signals that travel through neurons.

Advancements in neurotechnology are blurring the line between biology and technology. There is an emerging push to implant electronic devices inside the human body, hardwire them to our brains, and allow us to not only overcome disadvantages or injury but open up entirely new avenues of human experience.

VICE’s Thomas Morton got an inside look at what might be the next evolutionary step for humankind.

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