DeepMind Has Trained an AI To Control Nuclear Fusion (wired.com) 75
The Google-backed firm taught a reinforcement learning algorithm to control the fiery plasma inside a tokamak nuclear fusion reactor. From a report: The inside of a tokamak -- the doughnut-shaped vessel designed to contain a nuclear fusion reaction -- presents a special kind of chaos. Hydrogen atoms are smashed together at unfathomably high temperatures, creating a whirling, roiling plasma that's hotter than the surface of the sun. Finding smart ways to control and confine that plasma will be key to unlocking the potential of nuclear fusion, which has been mooted as the clean energy source of the future for decades. At this point, the science underlying fusion seems sound, so what remains is an engineering challenge.
That's where DeepMind comes in. The artificial intelligence firm, backed by Google parent company Alphabet, has previously turned its hand to video games and protein folding, and has been working on a joint research project with the Swiss Plasma Center to develop an AI for controlling a nuclear fusion reaction. In stars, which are also powered by fusion, the sheer gravitational mass is enough to pull hydrogen atoms together and overcome their opposing charges. On Earth, scientists instead use powerful magnetic coils to confine the nuclear fusion reaction, nudging it into the desired position and shaping it like a potter manipulating clay on a wheel. The coils have to be carefully controlled to prevent the plasma from touching the sides of the vessel: this can damage the walls and slow down the fusion reaction. (There's little risk of an explosion as the fusion reaction cannot survive without magnetic confinement).
But every time researchers want to change the configuration of the plasma and try out different shapes that may yield more power or a cleaner plasma, it necessitates a huge amount of engineering and design work. Conventional systems are computer-controlled and based on models and careful simulations, but they are, Ambrogio Fasoli, director of the Swiss Plasma Center at Ecole Polytechnique Federale de Lausanne in Switzerland. says, "complex and not always necessarily optimized." DeepMind has developed an AI that can control the plasma autonomously. A paper published in the journal Nature describes how researchers from the two groups taught a deep reinforcement learning system to control the 19 magnetic coils inside TCV, the variable-configuration tokamak at the Swiss Plasma Center, which is used to carry out research that will inform the design of bigger fusion reactors in the future.
That's where DeepMind comes in. The artificial intelligence firm, backed by Google parent company Alphabet, has previously turned its hand to video games and protein folding, and has been working on a joint research project with the Swiss Plasma Center to develop an AI for controlling a nuclear fusion reaction. In stars, which are also powered by fusion, the sheer gravitational mass is enough to pull hydrogen atoms together and overcome their opposing charges. On Earth, scientists instead use powerful magnetic coils to confine the nuclear fusion reaction, nudging it into the desired position and shaping it like a potter manipulating clay on a wheel. The coils have to be carefully controlled to prevent the plasma from touching the sides of the vessel: this can damage the walls and slow down the fusion reaction. (There's little risk of an explosion as the fusion reaction cannot survive without magnetic confinement).
But every time researchers want to change the configuration of the plasma and try out different shapes that may yield more power or a cleaner plasma, it necessitates a huge amount of engineering and design work. Conventional systems are computer-controlled and based on models and careful simulations, but they are, Ambrogio Fasoli, director of the Swiss Plasma Center at Ecole Polytechnique Federale de Lausanne in Switzerland. says, "complex and not always necessarily optimized." DeepMind has developed an AI that can control the plasma autonomously. A paper published in the journal Nature describes how researchers from the two groups taught a deep reinforcement learning system to control the 19 magnetic coils inside TCV, the variable-configuration tokamak at the Swiss Plasma Center, which is used to carry out research that will inform the design of bigger fusion reactors in the future.
Let me be the first to say (Score:4, Funny)
Just Noooo!
Re: Let me be the first to say (Score:1)
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AI may be useful for pointing out if something looks out of whack (beyond normal checks), but controlling operations itself is too risky, at least until the technology becomes time and road tested as a critical component.
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If you make it to the end of the summary, the AI is merely helping set up test scenarios. Once they find a design that works, they'll be able to design a static system that just works. Classical physics ought to be enough to finish the design, so it would be a fairly predictable reaction.
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In that case, the headline is misleading: "DeepMind Has Trained an AI To Control Nuclear Fusion"
Perhaps it should be, "DeepMind AI Helps Design Nuclear Fusion Controller".
Using AI to help design a car engine is very different than using AI to drive the car itself. But few expect headlines to be accurate these days, because click-bait sells ads, and the scary version does that better.
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It would be controlling the magnets on the prototype, so the headline would be correct. They just probably won't need the AI when they go to manufacturing.
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Most readers would interpret the headline as being intended for "live" control. It's still possible to be technically accurate but misleading.
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You just need to define the parameters of the controls so even if Deep Mind goes crazy and produces the worst possible outputs, then it won't cause a disaster. Inside those parameters, it's fine to let an AI control things.
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> You just need to define the parameters of the controls so even if Deep Mind goes crazy and produces the worst possible outputs, then it won't cause a disaster. Inside those parameters, it's fine to let an AI control things.
For complex systems there's often ways to bleep things up that can't be anticipated. Maybe some odd feedback loop can create unexpected vibrations or bubbles in the pipes or who knows what.
And don't forget Stuxnet: it wore out parts without being detected for a long time using creati
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Yeah but "self destruction" isn't a serious problem with fusion.
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By some accounts they can spew radiation far and wide under certain malfunctions. The first "batch" will probably have unexpected bugs; it is rocket science.
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The first "batch" will probably have unexpected bugs; it is rocket science.
True point. Strictly speaking it's much, much harder than rocket science.
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Or, as Randall Munroe writes about astatine in "What If?"...
"There’s no material safety data sheet... If there were, it would just be the word “NO” scrawled over and over in charred blood".
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You're just in a race to get the first joke in, eh?
But the joke I was looking for would have been something around "What could possibly go wrong?", but at a higher level. That one is obviously hanging too low. And the funniest jokes are the ones you weren't looking for. (The recent story about Metamates had a number of good ones.)
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Faceplant (Score:2)
Gee. What could could go wrong?
On the upside, millions might end up suffering, but I got a good chuckle out of the idea.
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Next upgrade (Score:2, Funny)
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Dude, put down your jporn
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combined AI (Score:2)
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I see what you did there. And so did they.
Wheres the line (Score:5, Insightful)
I mean, this makes sense, we've been using computers to control processes that operate faster than human reflexes can handle for, well, almost as long as computers have been around.
I know I am in "old man yells at cloud" territory but at what point is this an "AI" and not just a really, really advanced PID controller?
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https://en.wikipedia.org/wiki/... [wikipedia.org]
As with all acronyms, it may or may not be very obscure depending on your own knowledge.
Re: Wheres the line (Score:2)
PID controllers are used in almost 100% of everything using sensors to control things. It's a mathematical technique by which a sensor's readings are reapplied to the system in a feedback to alter the process, which alters the sensor's readings etc. In analog versions its 3 dials setting voltages, flows or whatever. In digital ones it's three numbers. Each acts as the factor in a linear equation (P = proportional), in an Integral equation, and in a Differential equation. This is usually enough to solve most
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Re:Wheres the line (Score:4, Insightful)
I know I am in "old man yells at cloud" territory but at what point is this an "AI" and not just a really, really advanced PID controller?
AI is the standard industry term for "machine learning" - millions of weighted variables and deep reinforcement learning. Get over it.
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...at what point is this an "AI" and not just a really, really advanced PID controller?
If you define a cost function and use a search algorithm to tune the gains, by most definitions a PID controller is AI.
The flip side is, we can use the tools of "AI" to make some really nice controllers.
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To a large extent, a PID controller is deterministic. That is, with a bit of math you can show what the frequency response of the system will be. You can spot where you may encounter resonances, and avoid them. You can demonstrate what your stability margin is.
With most of what they call AI these days (neural nets of one sort or another), it's a black box. You
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but at what point is this an "AI"
It is an AI when it stars in a Gibson novel; until then you're just an idiot.
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Humans cannot process information as fast as a computer can. Some computer control systems can have latencies under 1ms for making decisions (that means from input to controller to actuator). A human? F1 drivers (which have some of the fastest reaction times have 200ms to respond to decisions.
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That's what we need in charge of a fusion reactor - the wrong decision made really, really fast.
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A human? F1 drivers (which have some of the fastest reaction times have 200ms to respond to decisions.
It is more 100ms, and below.
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Unless they say "Strong AI" or something similar, it's just a really advanced PID controller.
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Most people don't realize that what you see in a movie is the acting computers getting instructions from the director to keep it slow so the humans can see what's going on. But when it comes to coffee, you better make sure the AI is already e
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Well it is an advanced controller by definition. What makes you think it's a PID controller. That's a precise type of model with various limitations.
Indeed (Score:2)
"but at what point is this an "AI" and not just a really, really advanced PID controller?"
Indeed, what this does is to use many many simulation data points to approximate a value function, so in the end it is really a nonlinear optimal controller synthesized in a different way.
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at what point is this an "AI" and not just a really, really advanced PID controller?
At the point where they trained a neural network to accomplish the goal.
Could you implement a PID controller using a neural network? Yes. Does that mean it's merely a PID controller? No because it's not based on the same concept even though it has the same result.
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If Google, Apple, Facebook or Microsoft really gave a $hit about the climate they'd invest a few tens of billions in their own moonshot program to develop a working fusion reactor in a timeframe sooner than the "10-20 years away" we've had for the past 70 years. If fusion can really ever truly work, that would be by far the most effective way they could spend that chump change they have sitting in offshore bank accounts collecting dust.
Or maybe this is yet another industry too incompetent to support itself
Oblig. Spider Man 2 reference (Score:1)
"Keep calm! It's only a spike! It'll soon stabilize!"
AI is not the answer to everything! (Score:2)
Never a perfect choice.
To control such facilities, fully deterministic software is needed:
GOOD: Number in -> algorithm with proper physics equations -> decision out.
Not:
BAD: Number in -> something that seems to do a good job 99% of the time, because it scanned a polynomial space and found a decent local optimum -> decision out.
Why is fusion so hard! (Score:3)
-Q.
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Shut up, Q.
Signed,
Q.
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Skynet (Score:2)
Do you want a fusion powered Skynet? 'cause this is how you get fusion powered Skynet!
Self sharpening knife (Score:2)
These computers with the ability to refine their algorithms is akin to self-sharpening knives. The knife can keep itself sharp and performs a task very well. However, it is not aware of the items it is cutting nor is it aware of the purpose for cutting the item. Cutting a carrot is no different than cutting a steak or a finger or a head of cow.
The day it asks the question why, may be too late.
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Well I for one welcome our self-sharpening AI overlords!
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Haha! I see what you did there! ;-)
What's next? (Score:2)
Re: What's next? (Score:2)
I assume (Score:2)
its all similar to the way that Doc Ock controlled nuclear fusion. Let's just hope deepmind doesn't escape and start attacking the city.
Thanks Wired, but ... (Score:3)
Hydrogen atoms are smashed together at unfathomably high temperatures, ...
This is science, we can fathom that.
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Yes, they should be talking in megafathoms or gigafathoms, to be more in line with scientific standards.
Boom! (Score:1)
Neutrons (Score:2)
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On an industrial scale you recycle the damaged walls if you don't want industrial scale radioactive waste.
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"Recycling" and "radioactive waste" aren't terms that coexist easily, unfortunately.
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