Υπολογισμοί AI με φως
Οι Φωτονικοί Επεξεργαστές είναι η κατεύθυνση Ε&Α της POLCERO: η επιτάχυνση του συμπερασμού AI στα ρομπότ μας χρησιμοποιώντας φως αντί μόνο ηλεκτρονικής. Ο οπτικός πολλαπλασιασμός πινάκων - η θεμελιώδης πράξη στα νευρωνικά δίκτυα - μπορεί να εκτελεστεί σε ένα μόνο πέρασμα του φωτός μέσα από ένα φωτονικό τσιπ, προσφέροντας καθυστέρηση της τάξης του υπο-νανοδευτερολέπτου και τάξεις μεγέθους χαμηλότερη ενέργεια ανά πράξη σε σχέση με τα τσιπ GPU/ASIC.
R&D
R&D direction
A research direction: accelerating AI inference in our robots using light instead of electronics alone - lower power, higher throughput.
One optical pass vs thousands of clock cycles
Neural-network inference is dominated by matrix-vector multiplication (GEMM). Photonic chips perform it with light passing through Mach-Zehnder interferometer meshes - doing in a single optical pass what electronics need thousands of clock cycles to compute.
Optical math, electronic activations
Photonic chips excel at linear operations (matrix math) but not nonlinear ones (activation functions). The consensus architecture pairs optical cores for matrix math with electronic units for activations - a hybrid design taking the best of both.
A fast-growing accelerator market
The global photonic AI-accelerator market, 2025 to 2034 (CAGR 26.3%). As of 2026 we track 52 photonic-computing companies worldwide.
Swap the substrate, keep the intelligence
As photonic accelerators reach maturity (a 2027-2031 window for datacenter-class products), the POLCERO AI-brain architecture is built to absorb them - the abstraction layer lets us swap the compute substrate without retraining the task intelligence.
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