Hinton说以后都是mortal computer

[TheMatrix]

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."

[hci]

Nonsense.

Neuro-chip developed my colleague next door was indeed analogy, and it indeed consumed little power.

The problem is that, its programming is completely different, i.e. the whole of computer science has to be thrown out.

Deep learning is not like that.

[FoxMe]

Neuromorphic最近是不是很火？要用memristor，这是华人科学家蔡少棠发明的，够拿诺贝尔奖的。听他讲过，全忘了。

蔡少棠（英语：Leon Ong Chua，1936年6月28日－），生于菲律宾，籍贯福建泉州晋江塘东村，美国电机工程学者，现为加州大学伯克利分校电机工程与计算机科学系教授，IEEE会士（英语：IEEE Fellow）。他提出了忆阻器、蔡氏电路和细胞式类神经网路（CNN）等理论。他被认为是非线性电路分析理论（nonlinear-circuit theory）之父。在他预测忆阻器存在的三十七年后，在惠普公司由R.斯坦利·威廉斯（英语：R. Stanley Williams）领导的研究小组开发出能工作的固态忆阻器。[1]

要说蔡少棠早就搞神经网络了。

[Caravel]

Neuromorphic最近是不是很火？要用memristor，这是华人科学家蔡少棠发明的，够拿诺贝尔奖的。听他讲过，全忘了。

蔡少棠（英语：Leon Ong Chua，1936年6月28日－），生于菲律宾，籍贯福建泉州晋江塘东村，美国电机工程学者，现为加州大学伯克利分校电机工程与计算机科学系教授，IEEE会士（英语：IEEE Fellow）。他提出了忆阻器、蔡氏电路和细胞式类神经网路（CNN）等理论。他被认为是非线性电路分析理论（nonlinear-circuit theory）之父。在他预测忆阻器存在的三十七年后，在惠普公司由R.斯坦利·威廉斯（英语：R. Stanley Williams）领导的研究小组开发出能工作的固态忆阻器。[1]

要说蔡少棠早就搞神经网络了。

电脑里面大部分能量都耗在搬运内存里面的东西了，神经网络都放在local快速存储应该是可以的，只是这种计算机只有比较单一的用途。可以作为协处理器。