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Intel's Neuromorphic Chip Scales Up (and It Smells)
Neuromorphic chips attempt to directly mimic the behavior of the human brain. Intel, which introduced its Loihi neuromorphic chip in 2017, has just announced that Loihi has been scaled up into a system that simulates over 100 million neurons. Furthermore, it announced that the chip smells. (That is to say: it's able to smell. To a nose, it probably just smells like a computer chip.)
Loihi is Intel's fifth-generation neuromorphic chip. It packs 128 cores – each of which has a built-in learning module – and a total of around 131,000 computational "neurons" that communicate with one another, allowing the chip to understand stimuli. The new system, Pohoiki Springs, contains over 100 million of those computational neurons. It consists of 768 Loihi chips, mounted on Intel Nahuku boards in a chassis that Intel describes as "the size of five standard servers," and a row of Arria10 FPGA boards. By contrast, Kapoho Bay, Intel's smallest neuromorphic device, consists of just two Loihi chips with 262,000 neurons.
"Pohoiki Springs scales up our Loihi neuromorphic research chip by more than 750 times, while operating at a power level of under 500 watts," said Mike Davies, director of Intel's Neuromorphic Computing Lab. "The system enables our research partners to explore ways to accelerate workloads that run slowly today on conventional architectures, including high-performance computing systems."
Also at The Next Platform, EE Times, and Wccftech.
(Score: 2) by FatPhil on Wednesday March 25 2020, @09:36AM (4 children)
Yes, it enables others to explore things, but has it actually *done* anything? Press releases are written by people who want to make nothing sound like something, and that grinds my gears.
Great minds discuss ideas; average minds discuss events; small minds discuss people; the smallest discuss themselves
(Score: 2) by takyon on Wednesday March 25 2020, @11:53AM (3 children)
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(Score: 0) by Anonymous Coward on Wednesday March 25 2020, @01:28PM (2 children)
What are the odds they even got the smell detecting part wrong?
https://en.wikipedia.org/wiki/Vibration_theory_of_olfaction [wikipedia.org]
(Score: 2) by takyon on Wednesday March 25 2020, @01:32PM (1 child)
If it can detect all of the compounds they throw at it correctly, then there isn't a problem. It's possible they don't need to know how it works (a common theme for machine learning and neuromorphic).
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(Score: 4, Insightful) by FatPhil on Thursday March 26 2020, @04:28AM
Great minds discuss ideas; average minds discuss events; small minds discuss people; the smallest discuss themselves
(Score: 2, Interesting) by Anonymous Coward on Wednesday March 25 2020, @03:40PM (1 child)
So what is it?
"neurons" can be anything from an FPGA LUT to an array of 16 bytes in a ram cell to a monstrous construction several megabyte in size, depending on model used and level of detail, as well as what subset of known biological features one chooses to implement.
link to whitepaper: https://www.researchgate.net/publication/322548911_Loihi_A_Neuromorphic_Manycore_Processor_with_On-Chip_Learning [researchgate.net]
"oihi is a 60 mm 2 chip fabricated in Intel’s 14nm process that advances the state-of-the-art modeling of spiking neural networks in
silicon. It integrates a wide range of novel features for the field, such as hierarchical connectivity, dendritic compartments, synaptic delays, and
most importantly programmable synaptic learning rules"
in the report:
"We adopt a variation of the well-known CUBA leaky-
integrate-and-fire model that has two internal state variables, the
synaptic response current u i (t) and the membrane potential v i (t) ."
So they model a neuron WITH 2 VARIABLES.
Sure, it can be used for fancy pattern recornition. But it aint a breakthrough, or "an attempt to directly mimic the behavior of the human brain".
To me, it resembles "an attempt to directly mimic IBM and their equally useless spiNNaker arch"
https://en.wikipedia.org/wiki/SpiNNaker [wikipedia.org]
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(Score: 0) by Anonymous Coward on Friday March 27 2020, @03:38AM (1 child)
If they can increase it by 2.5x then they have the horsepower to simulate a cat, 5x for a dog:
https://en.wikipedia.org/wiki/List_of_animals_by_number_of_neurons [wikipedia.org]
Whether you can throw a 3d simultated environment at it and have something usual created is another matter though
(Score: 2) by takyon on Saturday March 28 2020, @01:45PM
It remains to be seen how "strong" the neurons are. How closely does the number compare to real neurons? Are the amount of "synapses" important? Does the interconnect or the "neuron" density need to be beefed up before it can run in real time or faster?
Because if it does just work properly, then there is a very easy path to true "strong AI". Just add more of these chips in a larger room and you could create a machine-based life form (somehow). And a few node shrinks and 3D stacking improvements will make it much more achievable.
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