Google has announced that its custom-made tensor processing units (TPUs) have been made available for rent on the Google Cloud Platform:
A few years ago, Google created a new kind of computer chip to help power its giant artificial intelligence systems. These chips were designed to handle the complex processes that some believe will be a key to the future of the computer industry. On Monday, the internet giant said it would allow other companies to buy access to those chips through its cloud-computing service. Google hopes to build a new business around the chips, called tensor processing units, or T.P.U.s.
[...] In addition to its T.P.U. chips, which sit inside its data centers, the company has designed an A.I. chip for its smartphones.
Right now, Google's new service is focused on a way to teach computers to recognize objects, called computer vision technology. But as time goes on, the new chips will also help businesses build a wider range of services, Mr. Stone said. At the end of last year, hoping to accelerate its work on driverless cars, Lyft began testing Google's new chips. Using the chips, Lyft wanted to accelerate the development of systems that allow driverless cars to, say, identify street signs or pedestrians. "Training" these systems can take days, but with the new chips, the hope is that this will be reduced to hours. "There is huge potential here," said Anantha Kancherla, who oversees software for the Lyft driverless car project.
T.P.U. chips have helped accelerate the development of everything from the Google Assistant, the service that recognizes voice commands on Android phones, to Google Translate, the internet app that translates one language into another. They are also reducing Google's dependence on chip makers like Nvidia and Intel. In a similar move, it designed its own servers and networking hardware, reducing its dependence on hardware makers like Dell, HP and Cisco.
Also at The Next Platform, TechCrunch, and CNBC.
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Google has designed a low-power version of its homegrown AI math accelerator, dubbed it the Edge TPU, and promised to ship it to developers by October. Announced at Google Next 2018 today, the ASIC is a cutdown edition of its Tensor Processing Unit (TPU) family of in-house-designed coprocessors. TPUs are used internally at Google to power its machine-learning-based services, or are rentable via its public cloud. These chips are specific[ally] designed for and used to train neural networks and perform inference.
Now the web giant has developed a cut-down inference-only version suitable for running in Internet-of-Things gateways. The idea is you have a bunch of sensors and devices in your home, factory, office, hospital, etc, connected to one of these gateways, which then connects to Google's backend services in the cloud for additional processing.
Inside the gateway is the Edge TPU, plus potentially a graphics processor, and a general-purpose application processor running Linux or Android and Google's Cloud IoT Edge software stack. This stack contains lightweight Tensorflow-based libraries and models that access the Edge TPU to perform AI tasks at high speed in hardware. This work can also be performed on the application CPU and GPU cores, if necessary. You can use your own custom models if you wish.
The stack ensures connections between the gateway and the backend are secure. If you wanted, you could train a neural network model using Google's Cloud TPUs and have the Edge TPUs perform inference locally.
Google announcement. Also at TechCrunch, CNBC, and CNET.
Related: Google's New TPUs are Now Much Faster -- will be Made Available to Researchers
Google Renting Access to Tensor Processing Units (TPUs)
Nvidia V100 GPUs and Google TPUv2 Chips Benchmarked; V100 GPUs Now on Google Cloud
(Score: 0) by Anonymous Coward on Tuesday February 13 2018, @06:54AM (4 children)
The true silicon neural computing being done by Intel and IBM should lead to better results, eventually.
(Score: 1, Interesting) by Anonymous Coward on Tuesday February 13 2018, @01:08PM (1 child)
As discrete processing cards.
One of the biggest reasons that desktops are going away is the lack of available hardware you can use with them. These would have been a perfect example of a device to make all those expansion slots the average desktop has unused into something useful.
Sad really.
(Score: 3, Insightful) by Nerdfest on Tuesday February 13 2018, @03:13PM
They're going the IBM lameframe, music streaming, and software route though ... why sell when you can rent.
(Score: 2) by takyon on Tuesday February 13 2018, @02:17PM (1 child)
IBM's TrueNorth and Intel's what again?
[SIG] 10/28/2017: Soylent Upgrade v14 [soylentnews.org]
(Score: 0) by Anonymous Coward on Tuesday February 13 2018, @08:16PM
Loihi
(Score: 2) by stretch611 on Tuesday February 13 2018, @08:07AM
SKYNET is alive...
All we can hope for is that John Connor comes from the future to destroy this evil.
Oh, wait, the last movie was fricking awful... and the decent TV series ended up on Fox, which cancels anything that requires more brain power than a 5 year old can muster....
I guess we are doomed!!! DOOOOOOOOOOOOOOOOOOOOMMMEEEDDD!!!!!!!!!!!
Now with 5 covid vaccine shots/boosters altering my DNA :P