HN Gopher Feed (2017-09-25) - page 1 of 10
Intel Introduces Neuromorphic Test Chip
21 points by 40acreshttps://newsroom.intel.com/editorials/intels-new-self-learning-c...
CoffeeDregs - 34 minutes ago
"It?s a future where first responders using image-recognition
applications can analyze streetlight camera images and quickly
solve missing or abducted person reports."Erp. That's also known
as "a massive surveillance network", right?"It?s a future where
[your government] using image-recognition applications can analyze
streetlight camera images and quickly solve [whether you're
involved in pre-crime]."This stuff is going to happen (or is
already here) so perhaps it's time to switch to managing pervasive
surveillance rather than preventing it.
lend000 - 32 minutes ago
Looking forward to when there is more information than just a press
release (the press release for Intel's 3D X-Point memory was over
two years ago, and we still aren't seeing those in production).
Regardless, very exciting work, and I look forward to getting my
hands on the API/instruction set/manual.
profquail - 9 minutes ago
3D XPoint has been available for several months now, just not in
the DIMM form factor. E.g. the Intel
tehsauce - 7 minutes ago
This hardware is designed for running spiking neural network
models? What is the current state of the art in this field? I was
under the impression that training a spiking neural network was
somewhat of an unsolved problem, because backprop doesn't easily
apply. Anyone have information on this?
meri_dian - 49 minutes ago
>"Researchers have demonstrated learning at a rate that is a 1
million times improvement compared with other typical spiking
neural nets as measured by total operations to achieve a given
accuracy when solving MNIST digit recognition problems.">"Further,
it is up to 1,000 times more energy-efficient than general purpose
computing required for typical training systems."Wow. That is
zitterbewegung - 33 minutes ago
Comparing a system to MNIST isn't really an indicator that it
provides an actual improvement. Comparing it to VGG would be a