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Scientists clear major roadblocks in mission to build powerful AI photonic chips
- Manufacturers are facing challenges in making electronic microchips more powerful and efficient due to cost, complexity, and physical limits, just as demand for increased computing power for AI is rising.
- Photonic chips, which use light instead of electricity, offer higher performance potential but face obstacles. Two recent papers in Nature discuss advancements in photonic computing, such as a new processor called Photonic Arithmetic Computing Engine (Pace) with 16,000+ photonic components for real-world applications.
- Photonic computing offers benefits like higher speeds, greater bandwidths, and suitability for AI tasks like matrix multiplications. However, challenges include integration with electronic systems, slower processing times when converting photons to electrical signals, and limitations in scalability, precision, and compatibility.
- Researchers are making progress in addressing hurdles to advance photonic computing capabilities, aiming to create next-generation hardware that can support AI applications by utilizing more effective materials and designs.
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