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Comment by nightski | Hacker News Reader

While the efficiency gains are nice and definitely welcome, it would be interesting to see what the performance gains are over a GPU. The article makes the chip sound somehow superior to existing implementations but really this is just running the same neural network algorithms we know and love on top of a more optimized hardware architecture.

Meaning I have no idea how this signals the beginning of a new era of more intelligent computers as the chip provides nothing to advance the state of the art on this front. Unless I am missing something?

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I think the more optimized hardware makes a big difference, mainly in power consumption. We're talking power savings of like 99.9 percent here, which makes embedded stuff way more powerful and reduces the need for calling out to the cloud for processing, thin-client device OSes, etc.

I too would like to see a decent comparison. Also what's ultimately going to matter is up-front cost per synapse and ongoing cost per synapse-second (from power consumption). That's really all that matters if you are planning to make a cluster out of them.

Of course, there could be some new and interesting uses in embedded devices where sheer throughput doesn't matter so much as total power usage, for moderate processing power. For example, the AI in Roomba and similar robot vacuums is pretty rudimentary, so appliances like that could maybe get a boost from this.

From the article "When running the traffic video recognition demo, it consumed just 63 milliwatts of power. Server chips with similar numbers of transistors consume tens of watts of power" and "laptop that had been programed to do the same task processed the footage 100 times slower than real time, and it consumed 100,000 times as much power as the IBM chip" So if those statements are true I would say it is about 10,000 to 100,000+ more energy efficient. That is a rather large claim so we would need to see more proof...

A difference is that a GPU uses a lot of power and takes up a lot of space. I can imagine an optimized, energy-efficient chip would be useful in embedded systems. Something like a Raspberry Pi for image processing maybe?

Like Tegra K1? GPUs are more energy efficient than normal CPUs for some tasks, so getting lower absolute power consumption is just a matter of using fewer cores.

I think you're thinking of a Graphics Card, a GPU is comparable in physical dimensions to a CPU.

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