The AI arms race spawns new hardware architectures

#News(IoTStack) [ via IoTGroup ]

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Some recent breakthroughs in this race include new chip architectures that perform computations in ways that are fundamentally different from what we’ve seen before.
But traditional computers are not optimized for neural network operations.
Neuromorphic computers use an alternative chip architecture to physically represent neural networks.
The concept behind neuromorphic computing has existed since the 1980s, but it did not get much attention because neural networks were mostly dismissed as too inefficient.
With renewed interest in deep learning and neural networks in the past few years, research on neuromorphic chips has also received new attention.
In July, a group of Chinese researchers introduced Tianjic, a single neuromorphic chip that could solve a multitude of problems, including object detection, navigation, and voice recognition.
While there’s no direct evidence that neuromorphic chips are the right path to creating artificial general intelligence, they will certainly help create more efficient AI hardware.
Neural networks and deep learning computations require huge amounts of compute resources and electricity.
Several companies and research labs have turned to optical computing to find solutions to the speed and electricity challenges of the AI industry.
Optical computers are also especially suitable for fast matrix multiplication, one of the key operations in neural networks.
The past months have seen the emergence of several working prototypes of optical AI chips.
Boston-based Lightelligence has developed an optical AI accelerator that is compatible with current electronic hardware and can improve performance of AI models by one or two orders of magnitude by optimizing some of the heavy neural network computations.
Lightelligence’s engineers say advances in optical computing will also reduce the costs of manufacturing AI chips.
More recently, a group of researchers at Hong Kong University of Science and Technology developed an all-optical neural network

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