8 ms·

Computers Create Recipe for Two New Magnetic Materials

112 points by type0 10y ago

CharlesW 10y ago
Site has been hugged to death for now. http://archive.is/6ZZv1 http://archive.is/6ZZv1
palad1n 10y ago
With all the hype usually flying around, a little surprised that it didn't say "AI Creates Recipe..."
- cmrx64 10y ago
  After all, every search problem is an AI waiting to break free.
aptwebapps 10y ago
I know Moore's Law is basically dead but I think that advances in applications of existing computing power like this will resurrect it, or something like it, before too long. Basically, there's a less dramatic version of the AI snowball where faster computers lead to even faster computers. Whether someone manages to build strong AI on top of that is different question.
- jacquesm 10y ago
  I think we'll see something different. We're now at 'peak datacenter' again and because there is only so much power and so much cooling and bandwidth that you can haul to a DC we'll see the pendulum swing back towards decentralization. We've gone through several of those cycles and they're not in any fundamental way tied to Moore's law.
  - aptwebapps 10y ago
    That's not really what I'm talking about. I'm just talking about new applications of datacenter computing power eventually driving research to the point where we get around some of the limitations that put the brakes on Moore's Law.
    - jacquesm 10y ago
      The limitations that put the brakes on Moore's Law are physical limitations there is no getting around those (at room temperature, using Silicon) in this universe at a cost level that consumers are willing to accept.
      - aptwebapps 10y ago
        Nice set of caveats you've got there. ;) Let's check back in ten years, see how things are going.
        jacquesm 10y ago
        > Let's check back in ten years, see how things are going. I'd have written the same thing 10 years ago and you would have written the same thing back then too. So, another 10 years then? What will happen on the chip level is more cores, not faster cores, possibly larger caches.
        aptwebapps 10y ago
        No, ten years ago I wasn't so optimistic. There are a bunch of things that can and will happen to move things along incrementally but what I think, based on no real evidence, is that there will be one or more major breakthroughs at some point that will likely be computation-assisted and we will get back to something similar to Moore's Law. Edit: typo
        jacquesm 10y ago
        I'm super curious in what area you feel these breakthroughs will be. Tunnel effects are real and very hard to reduce, even at lower temperatures. The band-gap can't get much smaller, supply voltages are about as low as we know how to get away with. There are solutions in terms of exotic materials with even more exotic fabrication methods. I linked to a nice video the other day, see if that interests you: https://www.youtube.com/watch?v=NGFhc8R_uO4 https://www.youtube.com/watch?v=NGFhc8R_uO4 That's the state of the art per 2012, not much has changed since then, though there has been some incremental improvement and optimization as well as larger dies for more cores.
  - deleted 10y ago
    [deleted]
- TeMPOraL 10y ago
  There's at least a 10x speedup potential in existing hardware if people stop doing silly things like Electron apps and shoehorning everything into web browsers.
  - afarrell 10y ago
    What is your recommended tutorial/book for learning to build well-designed desktop UIs that work on Windows, OSX, and multiple different flavours of Linux?
    - TeMPOraL 10y ago
      1) documentation of any chosen cross-platform UI framework 2) any decent software book that teaches to separate the presentation layer and platform layer from the rest of the program (that way, you have much less to port between platforms and maintaining it is not as costly as people fear)
      - afarrell 10y ago
        > of any chosen cross-platform UI framework such as... EDIT: my purpose in this line of questioning is to assert that if you are trying to persuade someone to not do a thing, you will be more effective if you can give someone a straightforward alternative. I likewise think that the folks trying to get people to stop writing python2 should pick a release of python3 to become an LTS release in the same way that in 2014 python2.7 was effectively declared an LTS release with support until 2020.
        TeMPOraL 10y ago
        https://en.m.wikipedia.org/wiki/List_of_platform-independent_GUI_libraries https://en.m.wikipedia.org/wiki/List_of_platform-independent... EDIT to parent's edit: I'm not really trying to persuade anyone; not anymore. I understand the incentives that push people toward wasteful solutions. This won't stop until we hit a resource limit. All I'm saying is that there's a lot more we can do with current hardware once Moore's law is definitely dead. The mostly untapped potential is conditioned on people not doing extremely wasteful things just to shave off a little development time.
Animats 10y ago
That's impressive. Co₂MnTi could be very useful. Cobalt, magnesium, and titanium are all easily obtainable. 665C Curie temperature, which is above neodymium magnets (400C) but below samarium-cobalt (720-800C). Any drawbacks to this material? Hard to compound? Low coercivity? Hard to cast or machine?
- hetspookjee 10y ago
  Mn is manganese, not magnesium (Mg).
  - Animats 10y ago
    Even more plentiful.
- mchannon 10y ago
  "easily obtainable" is relative. For instance, Cobalt is actually less common in the Earth's crust than either of the two rare earths we most typically associate with magnets, Neodymium and Cerium. With Cobalt demand reaching unprecedented levels due to Lithium battery demand reaching unprecedented levels, this discovery in and of itself is not a simple economic win. Also, Magnesium is 20-25 times more common than Manganese. Just as well- production of Magnesium metal is pretty small because it's so difficult to work with.
- castratikron 10y ago
  If they were able to predict the Curie temperature, I'd think they could predict the coercivity as well. However things like brittleness would probably fall outside of their domain.
praccu 10y ago
We did something pretty similar in a nearby field of materials science, using support vector machines rather than linear regression and focusing on a less specific target: http://www.nature.com/nature/journal/v533/n7601/abs/nature17439.html http://www.nature.com/nature/journal/v533/n7601/abs/nature17...
- selimthegrim 10y ago
  Nice work! Any plans to branch out to other materials?
  - praccu 10y ago
    I'm not with the lab any more, but last I heard they were soliciting data from nearby but related subfields (our lab was doing mostly vanadium templated tellurides, but there are a lot of other things to explore in the space of inorganic–organic hybrids, and there are labs working on them). The problem really is data sharing; the most active collaborators were willing to give us lab note-books as long as we paid to digitize them; it was very hard to convince other labs to digitize their own notebooks. TBH I think that's the hard part of a lot of this (collecting the data).
jtchang 10y ago
What I think we are starting to see is the beginning of widespread use of computer based discovery through essentially machine learning techniques. I think AI is pretty far off but utilizing all the computing power we have to discover new materials and create useful things isn't very far off. I wonder what will happen if we can eventually tell computers to create us a better laptop, bike, phone, or lamp.
- virmundi 10y ago
  I think we need to rename AI. It's not really intelligent. It probably won't be for a long while. The machines don't know, in an existential sense, what they are looking at or making. We need to call it Artificial Insight. They spot facts in byte streams that we don't see. We can then contextualize the info into another part of the domain, or drive it deeper.
  - SomeStupidPoint 10y ago
    In what sense do you "know" what you're looking at but a machine doesn't?
    - pavlov 10y ago
      Ask humans to tell you what "cat" means, and you'll receive as many answers as there are respondents. Some will derive from science, some from common experience; some will describe the relation of cats to their environment, others will talk about personal emotional connections with particular cats. Ask a convolutional neural network what "cat" means, and the best you can get is a probability distribution of pixels on a grid. It's not intelligence, but just an encoding of facts provided by an actual intelligence.
      - adrianN 10y ago
        Ask neural networks that were trained on different inputs what a cat is and you'll get as many answers as there are neural networks.
brain5ide 10y ago
When in doubt - use brute force.

112 points by type0 10y ago

CharlesW 10y ago

Site has been hugged to death for now. http://archive.is/6ZZv1 http://archive.is/6ZZv1

palad1n 10y ago

With all the hype usually flying around, a little surprised that it didn't say "AI Creates Recipe..."

cmrx64 10y ago
After all, every search problem is an AI waiting to break free.

aptwebapps 10y ago

I know Moore's Law is basically dead but I think that advances in applications of existing computing power like this will resurrect it, or something like it, before too long. Basically, there's a less dramatic version of the AI snowball where faster computers lead to even faster computers. Whether someone manages to build strong AI on top of that is different question.

jacquesm 10y ago
I think we'll see something different. We're now at 'peak datacenter' again and because there is only so much power and so much cooling and bandwidth that you can haul to a DC we'll see the pendulum swing back towards decentralization. We've gone through several of those cycles and they're not in any fundamental way tied to Moore's law.
- aptwebapps 10y ago
  That's not really what I'm talking about. I'm just talking about new applications of datacenter computing power eventually driving research to the point where we get around some of the limitations that put the brakes on Moore's Law.
  - jacquesm 10y ago
    The limitations that put the brakes on Moore's Law are physical limitations there is no getting around those (at room temperature, using Silicon) in this universe at a cost level that consumers are willing to accept.
    - aptwebapps 10y ago
      Nice set of caveats you've got there. ;) Let's check back in ten years, see how things are going.
      - jacquesm 10y ago
        > Let's check back in ten years, see how things are going. I'd have written the same thing 10 years ago and you would have written the same thing back then too. So, another 10 years then? What will happen on the chip level is more cores, not faster cores, possibly larger caches.
        aptwebapps 10y ago
        No, ten years ago I wasn't so optimistic. There are a bunch of things that can and will happen to move things along incrementally but what I think, based on no real evidence, is that there will be one or more major breakthroughs at some point that will likely be computation-assisted and we will get back to something similar to Moore's Law. Edit: typo
        jacquesm 10y ago
        I'm super curious in what area you feel these breakthroughs will be. Tunnel effects are real and very hard to reduce, even at lower temperatures. The band-gap can't get much smaller, supply voltages are about as low as we know how to get away with. There are solutions in terms of exotic materials with even more exotic fabrication methods. I linked to a nice video the other day, see if that interests you: https://www.youtube.com/watch?v=NGFhc8R_uO4 https://www.youtube.com/watch?v=NGFhc8R_uO4 That's the state of the art per 2012, not much has changed since then, though there has been some incremental improvement and optimization as well as larger dies for more cores.
- deleted 10y ago
  [deleted]
TeMPOraL 10y ago
There's at least a 10x speedup potential in existing hardware if people stop doing silly things like Electron apps and shoehorning everything into web browsers.
- afarrell 10y ago
  What is your recommended tutorial/book for learning to build well-designed desktop UIs that work on Windows, OSX, and multiple different flavours of Linux?
  - TeMPOraL 10y ago
    1) documentation of any chosen cross-platform UI framework 2) any decent software book that teaches to separate the presentation layer and platform layer from the rest of the program (that way, you have much less to port between platforms and maintaining it is not as costly as people fear)
    - afarrell 10y ago
      > of any chosen cross-platform UI framework such as... EDIT: my purpose in this line of questioning is to assert that if you are trying to persuade someone to not do a thing, you will be more effective if you can give someone a straightforward alternative. I likewise think that the folks trying to get people to stop writing python2 should pick a release of python3 to become an LTS release in the same way that in 2014 python2.7 was effectively declared an LTS release with support until 2020.
      - TeMPOraL 10y ago
        https://en.m.wikipedia.org/wiki/List_of_platform-independent_GUI_libraries https://en.m.wikipedia.org/wiki/List_of_platform-independent... EDIT to parent's edit: I'm not really trying to persuade anyone; not anymore. I understand the incentives that push people toward wasteful solutions. This won't stop until we hit a resource limit. All I'm saying is that there's a lot more we can do with current hardware once Moore's law is definitely dead. The mostly untapped potential is conditioned on people not doing extremely wasteful things just to shave off a little development time.

Animats 10y ago

That's impressive. Co₂MnTi could be very useful. Cobalt, magnesium, and titanium are all easily obtainable. 665C Curie temperature, which is above neodymium magnets (400C) but below samarium-cobalt (720-800C). Any drawbacks to this material? Hard to compound? Low coercivity? Hard to cast or machine?

hetspookjee 10y ago
Mn is manganese, not magnesium (Mg).
- Animats 10y ago
  Even more plentiful.
mchannon 10y ago
"easily obtainable" is relative. For instance, Cobalt is actually less common in the Earth's crust than either of the two rare earths we most typically associate with magnets, Neodymium and Cerium. With Cobalt demand reaching unprecedented levels due to Lithium battery demand reaching unprecedented levels, this discovery in and of itself is not a simple economic win. Also, Magnesium is 20-25 times more common than Manganese. Just as well- production of Magnesium metal is pretty small because it's so difficult to work with.
castratikron 10y ago
If they were able to predict the Curie temperature, I'd think they could predict the coercivity as well. However things like brittleness would probably fall outside of their domain.

praccu 10y ago

We did something pretty similar in a nearby field of materials science, using support vector machines rather than linear regression and focusing on a less specific target: http://www.nature.com/nature/journal/v533/n7601/abs/nature17439.html http://www.nature.com/nature/journal/v533/n7601/abs/nature17...

selimthegrim 10y ago
Nice work! Any plans to branch out to other materials?
- praccu 10y ago
  I'm not with the lab any more, but last I heard they were soliciting data from nearby but related subfields (our lab was doing mostly vanadium templated tellurides, but there are a lot of other things to explore in the space of inorganic–organic hybrids, and there are labs working on them). The problem really is data sharing; the most active collaborators were willing to give us lab note-books as long as we paid to digitize them; it was very hard to convince other labs to digitize their own notebooks. TBH I think that's the hard part of a lot of this (collecting the data).

jtchang 10y ago

What I think we are starting to see is the beginning of widespread use of computer based discovery through essentially machine learning techniques. I think AI is pretty far off but utilizing all the computing power we have to discover new materials and create useful things isn't very far off. I wonder what will happen if we can eventually tell computers to create us a better laptop, bike, phone, or lamp.

virmundi 10y ago
I think we need to rename AI. It's not really intelligent. It probably won't be for a long while. The machines don't know, in an existential sense, what they are looking at or making. We need to call it Artificial Insight. They spot facts in byte streams that we don't see. We can then contextualize the info into another part of the domain, or drive it deeper.
- SomeStupidPoint 10y ago
  In what sense do you "know" what you're looking at but a machine doesn't?
  - pavlov 10y ago
    Ask humans to tell you what "cat" means, and you'll receive as many answers as there are respondents. Some will derive from science, some from common experience; some will describe the relation of cats to their environment, others will talk about personal emotional connections with particular cats. Ask a convolutional neural network what "cat" means, and the best you can get is a probability distribution of pixels on a grid. It's not intelligence, but just an encoding of facts provided by an actual intelligence.
    - adrianN 10y ago
      Ask neural networks that were trained on different inputs what a cat is and you'll get as many answers as there are neural networks.

brain5ide 10y ago

When in doubt - use brute force.