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Difference to CERN would be that no company is financing high energy physics while AI is frenzily funded. But getting new models and insights (in the public do

Difference to CERN would be that no company is financing high energy physics while AI is frenzily funded. But getting new models and insights (in the public domain) is a good idea.

loufe 3y ago
Great point. I think the next couple years will see private money dry up for all but a few companies, unless there are further massive breakthroughs. A publically funded group would be great to incubate talent in the EU and help keep AI research free and open.
mrd3v0 3y ago
Yeah, it will be interesting to see how they are going to avoid an "OpenAI" situation.
impossiblefork 3y ago
Yes, but just as you need commercial stuff you also need research, and those are different things. I think something like this will be great. It'll be fantastic to go there for a conference, it'll be fantastic to work there for two years even if you eventually go into industry, etc. I think the problem for commercialisation is the cost of DL accelerators and I think this is what creates the enormous VC reliance, and this in turn leads to many firms being in the US. The EU probably needs some effort to bring DL accelerators closer to the semiconductor production cost-- it shouldn't be 40x what TSMC charges to make the chips, it should be maybe 2x or 3x. I don't know if that's realistic, but considering that chips are so expensive that the electricity costs aren't a big fraction of the cost anymore, I think even badly designed chips, if you get them cheaply, will do. I think there should be a centralised location though, or well two. One for summer and one for winter, one here in Sweden, the other in Southern France or in Spain.
- BlueTemplar 3y ago
  Didn't big hospitals start to get their own accelerators ? (Or what do you mean by "DL"-oh, Deep Learning, my bad, in context I thought it was something like Direct Linear particle accelerators...)
mrtksn 3y ago
See, the AI funding frenzy is about extracting much more money from it in the future. IMHO it's like the 2000s internet when everything was funded by the VC and the internet was amazing, only to turn into this money extraction racket of a few apps and websites dominating %90 of everything with no fun left. They banked on rent seeking by locking down everything, to the point that nothing new is being made in SV anymore and the only new big thing in that space came from China(TikTok) and Russia(Telegram). Would suck badly if the people who fund the current AI revolution decide that it's time to recoup their investment. It's not that they are bad people, it's just that they are not doing it as a charity. Also, OpenAI's rationalisation for switching from non-profit to for-profit revolves around the idea that AI research is very expensive because it requires huge amount of hardware and it's not feasible to raise the required capital for this as a non-profit. There's the solution for OpenAI becoming open: CERN for AI. Money is provided with expectation of open research.
toxik 3y ago
That is because nobody expects HEP to produce commercially viable products. People do expect that of AI. I think it sounds like a great idea, both to stop a bit of AI brain drain to the US, as well as to develop AI for things that aren't immediately profitable to businesses.
- arethuza 3y ago
  Well, nobody expected it, but by funding HEP we got the Web.
- bluish29 3y ago
  That's a very good reason why CERN produced a lot of things that lead to many viable products at the end. The R&D work is usually a rich source of knowledge in itself.
alephnerd 3y ago
> no company is financing high energy physics Medical Technology (eg. Siemens Healthcare, GE Healthcare, Abbott, Medtronics, Phillips) all sponsor high energy physics due to it's applications in medical imaging and some nuclear therapies. HPC firms like Nvidia, AMD, Intel, Huawei, etc are also major hirers due to the applications of simulations in machine learning (and vice versa). Most ML innovations were sparked out of research that arose from nuclear simulation research after the NTBT was enforced. And finally, ML R&D companies themselves have funded research in adjacent spaces of High Energy Physics that also had concurrent applications in the ML space. The issue with CERN (and much of Europe's R&D ecosystem) is organizational.

Difference to CERN would be that no company is financing high energy physics while AI is frenzily funded. But getting new models and insights (in the public domain) is a good idea.

loufe 3y ago

Great point. I think the next couple years will see private money dry up for all but a few companies, unless there are further massive breakthroughs. A publically funded group would be great to incubate talent in the EU and help keep AI research free and open.

mrd3v0 3y ago

Yeah, it will be interesting to see how they are going to avoid an "OpenAI" situation.

impossiblefork 3y ago

Yes, but just as you need commercial stuff you also need research, and those are different things. I think something like this will be great. It'll be fantastic to go there for a conference, it'll be fantastic to work there for two years even if you eventually go into industry, etc. I think the problem for commercialisation is the cost of DL accelerators and I think this is what creates the enormous VC reliance, and this in turn leads to many firms being in the US. The EU probably needs some effort to bring DL accelerators closer to the semiconductor production cost-- it shouldn't be 40x what TSMC charges to make the chips, it should be maybe 2x or 3x. I don't know if that's realistic, but considering that chips are so expensive that the electricity costs aren't a big fraction of the cost anymore, I think even badly designed chips, if you get them cheaply, will do. I think there should be a centralised location though, or well two. One for summer and one for winter, one here in Sweden, the other in Southern France or in Spain.

BlueTemplar 3y ago
Didn't big hospitals start to get their own accelerators ? (Or what do you mean by "DL"-oh, Deep Learning, my bad, in context I thought it was something like Direct Linear particle accelerators...)

mrtksn 3y ago

See, the AI funding frenzy is about extracting much more money from it in the future. IMHO it's like the 2000s internet when everything was funded by the VC and the internet was amazing, only to turn into this money extraction racket of a few apps and websites dominating %90 of everything with no fun left. They banked on rent seeking by locking down everything, to the point that nothing new is being made in SV anymore and the only new big thing in that space came from China(TikTok) and Russia(Telegram). Would suck badly if the people who fund the current AI revolution decide that it's time to recoup their investment. It's not that they are bad people, it's just that they are not doing it as a charity. Also, OpenAI's rationalisation for switching from non-profit to for-profit revolves around the idea that AI research is very expensive because it requires huge amount of hardware and it's not feasible to raise the required capital for this as a non-profit. There's the solution for OpenAI becoming open: CERN for AI. Money is provided with expectation of open research.

toxik 3y ago

That is because nobody expects HEP to produce commercially viable products. People do expect that of AI. I think it sounds like a great idea, both to stop a bit of AI brain drain to the US, as well as to develop AI for things that aren't immediately profitable to businesses.

arethuza 3y ago
Well, nobody expected it, but by funding HEP we got the Web.
bluish29 3y ago
That's a very good reason why CERN produced a lot of things that lead to many viable products at the end. The R&D work is usually a rich source of knowledge in itself.

alephnerd 3y ago

> no company is financing high energy physics Medical Technology (eg. Siemens Healthcare, GE Healthcare, Abbott, Medtronics, Phillips) all sponsor high energy physics due to it's applications in medical imaging and some nuclear therapies. HPC firms like Nvidia, AMD, Intel, Huawei, etc are also major hirers due to the applications of simulations in machine learning (and vice versa). Most ML innovations were sparked out of research that arose from nuclear simulation research after the NTBT was enforced. And finally, ML R&D companies themselves have funded research in adjacent spaces of High Energy Physics that also had concurrent applications in the ML space. The issue with CERN (and much of Europe's R&D ecosystem) is organizational.