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research laboratory of electronics
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Futurology
Jun 05, 2019
Chip design drastically reduces energy needed to compute with light. Simulations suggest photonic chip could run optical neural networks 10 million times more efficiently than its electrical counterparts.
ai
ai accelerators
algorithms
artificial intelligence
balanced homodyne detection
data
data centers
eecs
electronics
energy
light
mach-zehnder interferometers
machine learning
matrix multiplication
mit
mit computer science and technology
mit electrical engineering and computer science
mit engineering
mit news
mit physics
mit research
mit science
ml
nanoscience
nanotechnology
neural network accelerators
neural networks
optical neural networks
optoelectronics
photonic accelerators
photonics
quantum photonics laboratory
research laboratory of electronics
rle
Futurology
Jun 05, 2019
Researchers at MIT have designed a chip that can compute with light, drastically reducing the power required to compute.
ai
ai accelerators
algorithms
artificial intelligence
balanced homodyne detection
data
data centers
eecs
electronics
energy
light
mach-zehnder interferometers
machine learning
matrix multiplication
mit
mit computer science and technology
mit electrical engineering and computer science
mit engineering
mit news
mit physics
mit research
mit science
ml
nanoscience
nanotechnology
neural network accelerators
neural networks
optical neural networks
optoelectronics
photonic accelerators
photonics
quantum photonics laboratory
research laboratory of electronics
rle
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