Photonics is proving to be a troublesome nut to crack
Photonics is proving to be a troublesome nut to crack
The rising compute energy vital to coach subtle AI fashions reminiscent of OpenAI’s ChatGPT may finally run up in opposition to a wall with mainstream chip applied sciences.
In a 2019 evaluation, OpenAI found that from 1959 to 2012, the quantity of energy used to coach AI fashions doubled each two years, and that the ability utilization started rising seven instances quicker after 2012.
It’s already inflicting pressure. Microsoft is reportedly going through an inside scarcity of the server {hardware} wanted to run its AI, and the shortage is driving costs up. CNBC, talking to analysts and technologists, estimates the present value of training a ChatGPT-like mannequin from scratch to be over $4 million.
One resolution to the AI coaching dilemma that’s been proposed is photonic chips, which use mild to ship indicators reasonably than the electrical energy that typical processors use. Photonic chips may in idea result in larger coaching efficiency as a result of mild produces much less warmth than electrical energy, can journey quicker and is way much less vulnerable to adjustments in temperature and electromagnetic fields.
Lightmatter, LightOn, Luminous Computing, Intel and NTT are among the many corporations creating photonic applied sciences. However whereas the expertise generated a lot pleasure a couple of years in the past — and attracted a whole lot of funding — the sector has cooled noticeably since then.
There are numerous the reason why, however the common message from buyers and analysts finding out photonics is that photonic chips for AI, whereas promising, aren’t the panacea they had been as soon as believed to be.
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