Hinton说以后都是mortal computer
发表于 ： 2022年 12月 3日 22:26
https://www.zdnet.com/article/we-will-s ... mputation/
"Mortal computation" means analog computers marrying AI closely to hardware will put GPT-3 in your toaster for $1 running on a few watts of power.
Hinton, offering the closing keynote Thursday at this year's Neural Information Processing Systems conference, NeurIPS, in New Orleans, said that the machine learning research community "has been slow to realize the implications of deep learning for how computers are built."
He continued, "What I think is that we're going to see a completely different type of computer, not for a few years, but there's every reason for investigating this completely different type of computer."
All digital computers to date have been built to be "immortal," where the hardware is engineered to be reliable so that the same software runs anywhere. "We can run the same programs on different physical hardware … the knowledge is immortal."
That requirement means digital computers have missed out, Hinton said, on "all sorts of variable, stochastic, flakey, analog, unreliable properties of the hardware, which might be very useful to us." Those things would be too unreliable to let "two different bits of hardware behave exactly the same way at the level of the instructions."
Future computer systems, said Hinton, will be take a different approach: they will be "neuromorphic," and they will be "mortal," meaning that every computer will be a close bond of the software that represents neural nets with hardware that is messy, in the sense of having analog rather than digital elements, which can incorporate elements of uncertainty and can develop over time.
"Now, the alternative to that, which computer scientists really don't like because it's attacking one of their foundational principles, is to say we're going to give up on the separation of hardware and software," explained Hinton.
"We're going to do what I call mortal computation, where the knowledge that the system has learned and the hardware, are inseparable."
These mortal computers could be "grown," he said, getting rid of expensive chip fabrication plants.
"If we do that, we can use very low power analog computation, you can have trillion way parallelism using things like memristors for the weights," he said, referring to a decades-old kind of experimental chip that is based on non-linear circuit elements.
"And also you could grow hardware without knowing the precise quality of the exact behavior of different bits of the hardware."
The new mortal computers won't replace traditional digital computers, Hilton told the NeurIPS crowd. "It won't be the computer that is in charge of your bank account and knows exactly how much money you've got," said Hinton.
"It'll be used for putting something else: It'll be used for putting something like GPT-3 in your toaster for one dollar, so running on a few watts, you can have a conversation with your toaster."
"Mortal computation" means analog computers marrying AI closely to hardware will put GPT-3 in your toaster for $1 running on a few watts of power.
Hinton, offering the closing keynote Thursday at this year's Neural Information Processing Systems conference, NeurIPS, in New Orleans, said that the machine learning research community "has been slow to realize the implications of deep learning for how computers are built."
He continued, "What I think is that we're going to see a completely different type of computer, not for a few years, but there's every reason for investigating this completely different type of computer."
All digital computers to date have been built to be "immortal," where the hardware is engineered to be reliable so that the same software runs anywhere. "We can run the same programs on different physical hardware … the knowledge is immortal."
That requirement means digital computers have missed out, Hinton said, on "all sorts of variable, stochastic, flakey, analog, unreliable properties of the hardware, which might be very useful to us." Those things would be too unreliable to let "two different bits of hardware behave exactly the same way at the level of the instructions."
Future computer systems, said Hinton, will be take a different approach: they will be "neuromorphic," and they will be "mortal," meaning that every computer will be a close bond of the software that represents neural nets with hardware that is messy, in the sense of having analog rather than digital elements, which can incorporate elements of uncertainty and can develop over time.
"Now, the alternative to that, which computer scientists really don't like because it's attacking one of their foundational principles, is to say we're going to give up on the separation of hardware and software," explained Hinton.
"We're going to do what I call mortal computation, where the knowledge that the system has learned and the hardware, are inseparable."
These mortal computers could be "grown," he said, getting rid of expensive chip fabrication plants.
"If we do that, we can use very low power analog computation, you can have trillion way parallelism using things like memristors for the weights," he said, referring to a decades-old kind of experimental chip that is based on non-linear circuit elements.
"And also you could grow hardware without knowing the precise quality of the exact behavior of different bits of the hardware."
The new mortal computers won't replace traditional digital computers, Hilton told the NeurIPS crowd. "It won't be the computer that is in charge of your bank account and knows exactly how much money you've got," said Hinton.
"It'll be used for putting something else: It'll be used for putting something like GPT-3 in your toaster for one dollar, so running on a few watts, you can have a conversation with your toaster."