There’s a new computer chip called the Cerebras Wafer-Scale Engine which is massive.
Chips are usually the size of a postage stamp, and you get faster computers by linking a bunch of them together. A different approach: the Cerebras is the size of an iPad.
The Cerebras has 1.2 trillion transistors, 20 times bigger than the world’s next largest chip, and 75 times bigger than the new Apple M1 chip. Singularity Hub has all the details: The Trillion-Transistor Chip That Just Left a Supercomputer in the Dust.
Anyway, this line from the announcement caught my eye:
it can tell you what is going to happen in the future faster than the laws of physics produce that same result.
Faster than real-time simulation.
I mean, that’s what physics does anyway, right? We can figure out the position of the planets in the solar system for a thousand years in the future without having to run the calculation for a thousand years.
And yet… something provocative about this.
One of the challenges with nuclear fission, the holy grail of clear energy generating, is the plasma going out of control, and the magnetic fields in the torus can’t be adjusted fast enough to contain it. The physics is too hard; nobody’s “solved” the plasma problem yet. But if the entire thing can be simulated from the bottom up, faster than realtime, you don’t need a model. You just run the simulation.
What are the civilian applications?
I can imagine a wearable device that continuously snapshots the world around you, runs the simulation in fast forward, and pre-emptively warns you about a mugging, or a bike going off course. Call it augmented apprehension.
Or how about intelligent fire extinguishers that simulate the fire in faster-than-realtime and dynamically direct the spray to uncannily effective spots.
I think it’s that uncanniness that draws me the most. Fluid dynamics and chaotic systems generally are weird and interesting. I think of the weird interference patterns you get in a pool of water if you get ripples to meet up in specific ways, or the strange behaviours of inverted pendulums that stand upright if you vibrate them at the right frequency. (Human skeletons are basically realtime adjusted inverted pendulums.)
So, with powerful simulation, could you figure out how to hit a mass of water with puffs of air so that it rises up and moves around the room, washing the windows; or robots with reed-thin jointed limbs that should never be able to hold themselves up, but with motors at each joint running at just the right vibration to keep the thing moving?
The general algorithm would seem to be:
sense and simulate the system
solve for the most energy-efficient intervention that leads to a improbable yet desired outcome, faster than that outcome can occur in real time
perform that action
rinse and repeat
…which is how dolphins swim and bumblebees fly.
Just as machine learning is getting into everything, and changing all software to the point that we don’t really know what will happen, unlocked by Google’s efforts with TensorFlow really, which componentised the technology, what is the equivalent path for faster than real-time simulation?
If somebody can turn faster than real-time simulation into a new hammer, what nails could we hit?
‘Yes, we’ll see them together some Saturday afternoon then,’ she said. ‘I won’t have any hand in your not going to Cathedral on Sunday morning. I suppose we must be getting back. What time was it when you looked at your watch just now?’ "In China and some other countries it is not considered necessary to give the girls any education; but in Japan it is not so. The girls are educated here, though not so much as the boys; and of late years they have established schools where they receive what we call the higher branches of instruction. Every year new schools for girls are opened; and a great many of the Japanese who formerly would not be seen in public with their wives have adopted the Western idea, and bring their wives into society. The marriage laws have been arranged so as to allow the different classes to marry among[Pg 258] each other, and the government is doing all it can to improve the condition of the women. They were better off before than the women of any other Eastern country; and if things go on as they are now going, they will be still better in a few years. The world moves. "Frank and Fred." She whispered something to herself in horrified dismay; but then she looked at me with her eyes very blue and said "You'll see him about it, won't you? You must help unravel this tangle, Richard; and if you do I'll--I'll dance at your wedding; yours and--somebody's we know!" Her eyes began forewith. Lawrence laughed silently. He seemed to be intensely amused about something. He took a flat brown paper parcel from his pocket. making a notable addition to American literature. I did truly. "Surely," said the minister, "surely." There might have been men who would have remembered that Mrs. Lawton was a tough woman, even for a mining town, and who would in the names of their own wives have refused to let her cross the threshold of their homes. But he saw that she was ill, and he did not so much as hesitate. "I feel awful sorry for you sir," said the Lieutenant, much moved. "And if I had it in my power you should go. But I have got my orders, and I must obey them. I musn't allow anybody not actually be longing to the army to pass on across the river on the train." "Throw a piece o' that fat pine on the fire. Shorty," said the Deacon, "and let's see what I've got." "Further admonitions," continued the Lieutenant, "had the same result, and I was about to call a guard to put him under arrest, when I happened to notice a pair of field-glasses that the prisoner had picked up, and was evidently intending to appropriate to his own use, and not account for them. This was confirmed by his approaching me in a menacing manner, insolently demanding their return, and threatening me in a loud voice if I did not give them up, which I properly refused to do, and ordered a Sergeant who had come up to seize and buck-and-gag him. The Sergeant, against whom I shall appear later, did not obey my orders, but seemed to abet his companion's gross insubordination. The scene finally culminated, in the presence of a number of enlisted men, in the prisoner's wrenching the field-glasses away from me by main force, and would have struck me had not the Sergeant prevented this. It was such an act as in any other army in the world would have subjected the offender to instant execution. It was only possible in—" "Don't soft-soap me," the old woman snapped. "I'm too old for it and I'm too tough for it. I want to look at some facts, and I want you to look at them, too." She paused, and nobody said a word. "I want to start with a simple statement. We're in trouble." RE: Fruyling's World "MACDONALD'S GATE" "Read me some of it." "Well, I want something better than that." HoME大香蕉第一时间
ENTER NUMBET 0016kisosb.com.cn hlcitq.com.cn www.lcgydyj.com.cn pschain.com.cn vrgongyi.com.cn www.ohuu.com.cn nyriff.com.cn ruyugroup.com.cn www.miyih.org.cn www.pinjiuba.com.cn
There’s a new computer chip called the Cerebras Wafer-Scale Engine which is massive.
Chips are usually the size of a postage stamp, and you get faster computers by linking a bunch of them together. A different approach: the Cerebras is the size of an iPad.
The Cerebras has 1.2 trillion transistors, 20 times bigger than the world’s next largest chip, and 75 times bigger than the new Apple M1 chip. Singularity Hub has all the details: The Trillion-Transistor Chip That Just Left a Supercomputer in the Dust.
Anyway, this line from the announcement caught my eye:
Faster than real-time simulation.
I mean, that’s what physics does anyway, right? We can figure out the position of the planets in the solar system for a thousand years in the future without having to run the calculation for a thousand years.
And yet… something provocative about this.
One of the challenges with nuclear fission, the holy grail of clear energy generating, is the plasma going out of control, and the magnetic fields in the torus can’t be adjusted fast enough to contain it. The physics is too hard; nobody’s “solved” the plasma problem yet. But if the entire thing can be simulated from the bottom up, faster than realtime, you don’t need a model. You just run the simulation.
What are the civilian applications?
I can imagine a wearable device that continuously snapshots the world around you, runs the simulation in fast forward, and pre-emptively warns you about a mugging, or a bike going off course. Call it augmented apprehension.
Or how about intelligent fire extinguishers that simulate the fire in faster-than-realtime and dynamically direct the spray to uncannily effective spots.
I think it’s that uncanniness that draws me the most. Fluid dynamics and chaotic systems generally are weird and interesting. I think of the weird interference patterns you get in a pool of water if you get ripples to meet up in specific ways, or the strange behaviours of inverted pendulums that stand upright if you vibrate them at the right frequency. (Human skeletons are basically realtime adjusted inverted pendulums.)
So, with powerful simulation, could you figure out how to hit a mass of water with puffs of air so that it rises up and moves around the room, washing the windows; or robots with reed-thin jointed limbs that should never be able to hold themselves up, but with motors at each joint running at just the right vibration to keep the thing moving?
The general algorithm would seem to be:
…which is how dolphins swim and bumblebees fly.
Just as machine learning is getting into everything, and changing all software to the point that we don’t really know what will happen, unlocked by Google’s efforts with TensorFlow really, which componentised the technology, what is the equivalent path for faster than real-time simulation?
If somebody can turn faster than real-time simulation into a new hammer, what nails could we hit?