Bose is known for its high-end speakers, but now it’s putting its tech into sunglasses.
This video is the eleventh in a multi-part series discussing computing. In this video, we’ll be discussing what cognitive computing is and the impact it will have on the field of computing.
[0:28–5:09] Starting off we’ll discuss, what cognitive computing is, more specifically – the difference between current computing Von Neuman architecture and more biologically representative neuromorphic architecture and how these two paired together will yield massive performance and efficiency gains!
[5:09–10:46] Following that we’ll discuss, the benefits of cognitive computing systems further as well as current cognitive computing initiatives, TrueNorth and Loihi.
[10:46–17:11] To conclude we’ll extrapolate and discuss the future of cognitive computing in terms of brain simulation, artificial intelligence and brain-computer interfaces!
For a humble, microscopic worm with only 302 neurons, C. elegans has had a lot of firsts. It was the first multicellular animal to have its whole genome sequenced. It was also the spark that lit the connectome fire—the revolutionary idea that mapping the entirety of connections among neurons will unveil secrets of our minds, memory, and consciousness. And if the connectomists are to be believed, a map of individual brains may be the blueprint that will one day hurtle AI into human-level intelligence, or reconstruct an entire human mind in digital form.
More than 30 years ago, a pioneering group of scientists painstakingly traced and reconstructed the roundworm’s neural wiring by hand. The “heroic” effort, unaided by modern computers and brain-mapping algorithms, resulted in the first connectome in 1986.
Yet the “mind of the worm” map had significant lapses. For one, it only focused on one sex, the hermaphrodite—a “female” equivalent that can self-fertilize. This makes it hard to tell which connections are universal for the species, and which are dependent on sex and reproduction. For another, because the effort relied entirely on human beings who get tired, bored, and mess up, the map wasn’t entirely accurate. Even with multiple rounds of subsequent refinements, errors could linger, which would royally screw up any interpretation of results using these maps.
Conventional computers need orders of magnitude more energy than the “computer” in our heads. Neural networks made of superconducting nanowires might come much closer to the real thing.
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Aired on Gadget Lab Podcast: buddy Elon Musk because it’s always fun to talk about Elon Musk and this time the man wants to put a computer in your brain this past Tuesda.
Law enforcement needs to be innovative and act now in order to keep face with near future criminal threats, warns ‘Do criminals dream of electric sheep’ paper.
The race is on to create new ways to protect data and communications from the threat posed by super-powerful quantum computers.