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John Carmack Proposes Fiber-Optic Loops as High-Speed AI Cache
John Carmack proposes fiber-optic loops as high-speed AI cache [techspot.com]
Light, not silicon, could someday define how artificial intelligence stores and recalls its knowledge. That's the idea that recently surfaced when John Carmack – the engineer known for his work on Doom and Meta's virtual reality projects – proposed using fiber-optic loops as a form of high-speed data cache for AI models. His brief post on X turned into a dense technical conversation among researchers and technologists intrigued by the blend of classic computing theory and modern optical networking.
The thought experiment began with a number. Single-mode fiber optics can now transmit data at 256 terabits per second over 200 kilometers. Based on that capacity, Carmack estimated that about 32 gigabytes of information are stored in the cable at any given moment.
Light, not silicon, could someday define how artificial intelligence stores and recalls its knowledge. That's the idea that recently surfaced when John Carmack – the engineer known for his work on Doom and Meta's virtual reality projects – proposed using fiber-optic loops as a form of high-speed data cache for AI models. His brief post on X turned into a dense technical conversation among researchers and technologists intrigued by the blend of classic computing theory and modern optical networking.
The thought experiment began with a number. Single-mode fiber optics can now transmit data at 256 terabits per second over 200 kilometers. Based on that capacity, Carmack estimated that about 32 gigabytes of information are stored in the cable at any given moment.
The underlying physics of such an approach isn't new. Commenters quickly connected Carmack's speculation to delay-line memory, a mid-20th-century technique that stored information as pulses traveling through mercury tubes. Even Alan Turing once joked about experimenting with gin as a medium.
While those early systems were abandoned due to instability and practical limitations, fiber optics has rekindled the concept with modern precision. Compared with volatile DRAM, light offers predictability, low power draw, and enormous bandwidth potential.
The potential efficiency benefits are part of what makes the proposal enticing. Dynamic RAM demands constant electrical refreshing to preserve bit states, consuming substantial energy in large-scale AI servers. Fiber, by contrast, requires minimal power to maintain optical signals.
As Carmack observed, fiber transmission may follow a more favorable growth curve than DRAM, particularly as component miniaturization slows. Yet he acknowledged a major barrier – 200 kilometers of high-grade fiber would be costly, and the amplifiers and digital signal processors needed to sustain transmission could offset any power savings.
