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Optical and Photonic Computing

What is Optical Computing? Using light instead of electrons to perform computations, potentially offering massive parallelism and energy efficiency.

Why Photonics for AI?

AdvantageDescription
SpeedLight speed computation
ParallelismMany wavelengths simultaneously
EnergyNo resistive heating
BandwidthHigh data rates

Optical AI Companies

CompanyApproach
LightmatterPhotonic chip (Envise)
LightelligenceOptical matrix multiply
Luminous ComputingPhotonic AI accelerator
OptalysysOptical FFT/CNN
Celestial AIPhotonic fabric

How Optical Matrix Multiply Works

Light in --> [Mach-Zehnder Interferometers] --> Light out
              |
              Encodes matrix weights

Analog multiply: Amplitude modulation
Analog add: Interference

Lightmatter Envise

Challenges

ChallengeStatus
Precision8-bit typical, improving
IntegrationComplex packaging
ProgrammingNew toolchains needed
CostCurrently expensive
Non-linear opsUse electronic for activations

Theoretical Advantages

MetricElectronicPhotonic
Speed (matmul)nsps
Energy/oppJfJ
Parallelism1000s channels100,000s wavelengths

Current State

Timeline Predictions

MilestoneEstimated
Commercial inference chips2024-2025
Widespread datacenter use2027-2030
Training systems2028+

Best Practices

photonicsoptical compute

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