During the talk, Prof. Takenaka shared how recent advances in silicon-based programmable photonic circuits—made possible through the integration of heterogeneous materials – are unlocking novel device concepts, circuit architectures, and experimental methods. These developments highlight silicon photonics as a scalable, energy‑efficient platform for next‑generation AI hardware. 

Key takeaways included:  

• Photonic processors that enable low-energy multiply–accumulate (MAC) operations.

• Hybrid systems utilizing light for weight distribution and progressing toward fully photonic architectures, with an engaging discussion on achieving the optimal balance between optical and electronic processing.

• The critical role of electronic–photonic integration as a foundation for practical quantum systems.

• The potential for large-scale integration beyond the 128×128 threshold.

The talk drew an extremely strong turnout and was overwhelmingly well received on the floor, culminating in an energetic, extended questions and answers session. The session closed with clear interest in collaborations and follow-up demonstrations, underscoring the momentum behind silicon photonics for next-generation AI and quantum hardware.