7 ms·

Finland’s plan to train its population in artificial intelligence

128 points by imartin2k 8y ago

sqldba 8y ago
It wasn’t clear if this is the Elements of AI course or another course.
- leke 8y ago
  I remember signing up for this a while back, but never found the time to take it. I assume it's the same course because I remember the website looking so "trendy"
sakoht 8y ago
Perhaps they can use their new found AI skills to detect and flag propaganda from the tech industry.
- sergioisidoro 8y ago
  So when it's some silicon valley tech company releasing something as part of their tech marketing strategy it's fine, but when it's from Europe it's "Propaganda"?
  - dmos62 8y ago
    I don't think grandparent's attempt at humour suggested that, but it's good that you drew that parallel.
    - sergioisidoro 8y ago
      Well, it's not a secret that a lot of the content in HN is marketing content. Usually from companies who want to market themselves among the tech community. I'm not complaining. I learn a lot, and most of the times everyone wins. But it's not the first time I find this US/Rest of the world double standard. Maybe this was a knee jerk reaction from me to that pre existing notion
high_derivative 8y ago
Controversial opinion as a machine learning researcher: Well roundedness (or teaching basic elements to many) will not pay off as much, it would likely yield better results for the country to invest heavily at the top. Observation based on success of machine learning research in highly concentrated organisations (certain universities in the US, DeepMind, etc) versus countries with scattered expertise and resources (e.g. Germany). If you can afford to, do both, but observationally, this does not seem to happen. Not for a lack of resources but rather the mindset and a society's perspective.
- deleted 8y ago
  [deleted]
- PandaRider 8y ago
  If the objective is for applied research (research for the benefit of the economy), I disagree. My main argument is that we need domain experts outside of academia. Moreover, theoretical research in AI is very open and countries with limited resources are better off stand on the shoulders of giants than try and be number 1 themselves. Finland might never beat Russia/China/US AI arms race but they just need to defend themselves should any of these 3 countries monopolize or weaponize on AI.
  - jbottoms 8y ago
    I have a more informed perspective. First, Finland introduced a browser (Erwise) two years before the W3c browser. Second, the U.S. is stumbling in terms of getting beyond analytic and ANN designs, and AGI is an area where few in the U.S. work. I have worked with Finland on cutting-edge tech in the past, and I wouldn't be surprised if they made some serious breakthroughs. It does not take a lot of researchers to excell in AGI, it only takes one bricoleur. (source, inventor of the Internet browser.)
- openIce 8y ago
  Well I'm surprised you are a researcher if you can't see the benefits of educating non-IT people with domain knowledge what tools IT people can provide in order for both to work together on solving real world issues with AI.
imhoguy 8y ago
That is ideal direction - educating the non-IT people with domain knowledge what tools the IT people can provide then both can work on solving real world issues with AI. I predict lots of serious start-ups comming out of this effort.
xte 8y ago
Oh yeaaaaaah... Like modern "coding mania" at school... Guys IT world is as complex as a society: you can't train anyone to be a prime minister in such society before train in being an educated citizen. Most Finnish child can type on a Window PC with some proprietary (cr)app. They can probably play games, watch porn sites, social networks etc and that's for some older people seems to be like magic so they think that "programming" is only a small subsequent step like you can study integrals just after derivatives. And that's the ideal way to put people far from computer disgusted by obscene software and absurd training.
- tuukkah 8y ago
  > they think that "programming" is only a small subsequent step No, they think programming is a basic skill (like reading, writing and arithmetics) included from 1st to 9th grade in the national core curriculum: https://www.theatlantic.com/education/archive/2017/02/teaching-computer-science-without-computers/517548/ https://www.theatlantic.com/education/archive/2017/02/teachi... Details: https://legroup.aalto.fi/2015/11/coding-in-school-finland-takes-lead-in-europe/ https://legroup.aalto.fi/2015/11/coding-in-school-finland-ta...
  - xte 8y ago
    Thanks for the link however the point is simple: people who write those norms have no idea what programming means and how it can be done in modern desktops. If, and only of, we have modern Alto or LispM perhaps we can teach few "programming" concept to let most scholarized people able to script/design their own "home environment" on a desktop otherwise it's only a waste of time especially if is done as classic high schools in Italy or Sweden (starting with some Pascal dialect end try to offer C or JS after).
    - tuukkah 8y ago
      Finland doesn't do it like Italy or Sweden (let alone how they did it 20 years ago). Instead, kids are more likely to start with Scratch or similar: https://scratch.mit.edu https://scratch.mit.edu
Mortiffer 8y ago
Machine Learning is Alchemy https://youtu.be/x7psGHgatGM https://youtu.be/x7psGHgatGM . We need to understand optimization to advance this field not train thousands of monkeys to press play and hope for a nice result. Also, why did they not decide to teach 1% of the population basic coding. Now that could transform a society.
- bemmu 8y ago
  Basic programming skills have been a part of the Finnish primary school curriculum since 2016. By sixth grade students are expected to "create working programs in a graphical programming environment". Junior high includes "basic algorithmic thinking", more programming and embedded programming. Likely in practice means trying out Scratch in primary school and creating robots in junior high. Source: https://peda.net/ulvila/peruskoulut/harjunp%C3%A4%C3%A4n-koulu/opetus/ol2/tjvs/oo2/oop https://peda.net/ulvila/peruskoulut/harjunp%C3%A4%C3%A4n-kou...
goldenkey 8y ago
Most machine learning models are nothing but souped up regression that swaps out standard polynomials for matrix-valued polynomials with some x'es replaced by non-linear activation functions like tanh(x) The magic is in the toolkits that allow one to build these complex expressions through net chain composition, and provide symbolic differentiation to easily calculate gradient on hugely complex net chain graphs. The avg person isn't going to benefit from ML unless you also teach them the old-hat statistical fitting methods that worked well enough before ML came on the scene. Things like SVD, MPCA: https://en.wikipedia.org/wiki/Singular_value_decomposition https://en.wikipedia.org/wiki/Singular_value_decomposition https://en.wikipedia.org/wiki/Multilinear_principal_component_analysis https://en.wikipedia.org/wiki/Multilinear_principal_componen... Old stats techniques like: https://en.wikipedia.org/wiki/Elastic_net_regularization https://en.wikipedia.org/wiki/Elastic_net_regularization Its not worth training a bunch of folk who cant go deep into the heavy mathematics, statistics, and epistomology of what ML really is in terms of manifolds. Just show them what ML can and cannot do, if its not possible to give them the comprehensive education. And besides, most people, once they find out ML is a shit ton of math and as profound and based as the theory of functions, shakes their head and trods off. They wanted magic soup and you gave them the biggest questions about existence..about patterns..forms..things..about consciousness, intelligence, and life, about meaning. Don't expect the avg lowbrow person to want to explore ML once they get hit with the reality of its implications, rigor, and depth.
- zozbot123 8y ago
  > Most machine learning models are nothing but souped up regression that swaps out standard polynomials for matrix-valued polynomials with some x'es replaced by non-linear activation functions like tanh(x) Well, not quite. The non-linear activation feature is found already in "generalized linear models" (as a 'link function'). The typical "deep learning" model is a hierarchical/multi-level version of the same - and just like any other hierarchical/multi-level model, the point of that is to account in a parsimonious way for increasingly-complicated interactions among the regressors/features. But I think your broader point is right; there is a lot of hype in ML that derives purely from a lack of familiarity with basic statistical principles.
hyperpallium 8y ago
Is AI settled enough that today's state-of-the-art is a stable foundation that can be reliably built upon... or are revolutionary changes just around the corner? Or, it is that the application of some generic AI, that can use any upcoming changes? Perhaps we have a few more twenty year hype-winter cycles of NN before we know what we're doing...
- hyperpallium 8y ago
  > intention to "support democracy," ... raise awareness about the opportunities and risks of AI ... where they want their government to invest. > "That’s how society works — if enough people say they don’t like it, then we regulate it,” Agree, democracy needs uninformed voters. But the above was just the origin. Now the course seems more like encouraging people to see applications of AI in their regular work. Like pure vs applied maths. Agree: technology transfer/commercialization of AI will be the richest industry the world has ever seen. [ Though it's a bit like applications of computers [funfact: many software ideas were initally called AI... like how subjects moved from philosophy to science when they got actual facts]. Although computers are an "industry", their applications are considered vertical, i.e. as part of the industry they are applied to. Same thing happened to physics. So AI applications won't be "an industry", but in every industry. ] Another question is whether the application best starts from the AI end or the application end. You need both, but at this early stage, it's still requires an intertwined "integrated" collaboration. I don't think we're yet at the point where you just add magic AI pixie dust to a problem. But it can't hurt getting people introduced to it and thinking about it; and the democratic point remains true.
roel_v 8y ago
Can someone explain what is in this 'Elements of AI' course, since that doesn't seem to be described in the article? I'm just having a hard imagining what can be taught in a few months to e.g. the dentist in the article and still be 'practical'.
- anttipoi 8y ago
  https://www.elementsofai.com https://www.elementsofai.com It's not a course where you learn how to implement algorithms, but a general introduction to the concepts and problems that typically are treated under the label 'AI'.
  - YeGoblynQueenne 8y ago
    As usual, this is a course that completely ignores the first, oh, 60 or so years of artificial intelligence research which were dominated by logic-based AI, and places most of the focus on deep learning, as the only kind of machine learning that it talks about at any length. Sometimes, I despair. It's like AI started in 2012 - and was wrapped up the same year. Deep neural nets, problem solved, AI is all done and dusted.
    - jks 8y ago
      Did you click through to the course? Chapter 2 is about search algorithms and planning, albeit not in very much depth.
      - YeGoblynQueenne 8y ago
        Yes, of course I did. The relative attention given to the majority of work on AI and the last six years or so is disproportionate, to say the least.
ekswisey 8y ago
This is rather old news already by now. It's been a few months
deleted 8y ago
[deleted]
vidoc 8y ago
That's why we should all vape !
MrTonyD 8y ago
I've always admired Sweden for committing to robotics (it was back in the 90's I think, at a time when I was doing robotics work for Fanuc and GE). They went from nothing to becoming a major robotics player over decades. In contrast, I think committing to AI is a mistake - the market is fundamentally different. To put it simply - there is lots and lots of work to be done in robotics, over decades, while, in contrast, there is a big burst of work to be done in AI, followed by relatively little work (compared to the scale of robotics.) I admire Finland, and I hope somebody out there figures out the business difference before they lose decades to opportunity cost.

128 points by imartin2k 8y ago

sqldba 8y ago

It wasn’t clear if this is the Elements of AI course or another course.

leke 8y ago
I remember signing up for this a while back, but never found the time to take it. I assume it's the same course because I remember the website looking so "trendy"

sakoht 8y ago

Perhaps they can use their new found AI skills to detect and flag propaganda from the tech industry.

sergioisidoro 8y ago
So when it's some silicon valley tech company releasing something as part of their tech marketing strategy it's fine, but when it's from Europe it's "Propaganda"?
- dmos62 8y ago
  I don't think grandparent's attempt at humour suggested that, but it's good that you drew that parallel.
  - sergioisidoro 8y ago
    Well, it's not a secret that a lot of the content in HN is marketing content. Usually from companies who want to market themselves among the tech community. I'm not complaining. I learn a lot, and most of the times everyone wins. But it's not the first time I find this US/Rest of the world double standard. Maybe this was a knee jerk reaction from me to that pre existing notion

high_derivative 8y ago

Controversial opinion as a machine learning researcher: Well roundedness (or teaching basic elements to many) will not pay off as much, it would likely yield better results for the country to invest heavily at the top. Observation based on success of machine learning research in highly concentrated organisations (certain universities in the US, DeepMind, etc) versus countries with scattered expertise and resources (e.g. Germany). If you can afford to, do both, but observationally, this does not seem to happen. Not for a lack of resources but rather the mindset and a society's perspective.

deleted 8y ago
[deleted]
PandaRider 8y ago
If the objective is for applied research (research for the benefit of the economy), I disagree. My main argument is that we need domain experts outside of academia. Moreover, theoretical research in AI is very open and countries with limited resources are better off stand on the shoulders of giants than try and be number 1 themselves. Finland might never beat Russia/China/US AI arms race but they just need to defend themselves should any of these 3 countries monopolize or weaponize on AI.
- jbottoms 8y ago
  I have a more informed perspective. First, Finland introduced a browser (Erwise) two years before the W3c browser. Second, the U.S. is stumbling in terms of getting beyond analytic and ANN designs, and AGI is an area where few in the U.S. work. I have worked with Finland on cutting-edge tech in the past, and I wouldn't be surprised if they made some serious breakthroughs. It does not take a lot of researchers to excell in AGI, it only takes one bricoleur. (source, inventor of the Internet browser.)
openIce 8y ago
Well I'm surprised you are a researcher if you can't see the benefits of educating non-IT people with domain knowledge what tools IT people can provide in order for both to work together on solving real world issues with AI.

imhoguy 8y ago

That is ideal direction - educating the non-IT people with domain knowledge what tools the IT people can provide then both can work on solving real world issues with AI. I predict lots of serious start-ups comming out of this effort.

xte 8y ago

Oh yeaaaaaah... Like modern "coding mania" at school... Guys IT world is as complex as a society: you can't train anyone to be a prime minister in such society before train in being an educated citizen. Most Finnish child can type on a Window PC with some proprietary (cr)app. They can probably play games, watch porn sites, social networks etc and that's for some older people seems to be like magic so they think that "programming" is only a small subsequent step like you can study integrals just after derivatives. And that's the ideal way to put people far from computer disgusted by obscene software and absurd training.

tuukkah 8y ago
> they think that "programming" is only a small subsequent step No, they think programming is a basic skill (like reading, writing and arithmetics) included from 1st to 9th grade in the national core curriculum: https://www.theatlantic.com/education/archive/2017/02/teaching-computer-science-without-computers/517548/ https://www.theatlantic.com/education/archive/2017/02/teachi... Details: https://legroup.aalto.fi/2015/11/coding-in-school-finland-takes-lead-in-europe/ https://legroup.aalto.fi/2015/11/coding-in-school-finland-ta...
- xte 8y ago
  Thanks for the link however the point is simple: people who write those norms have no idea what programming means and how it can be done in modern desktops. If, and only of, we have modern Alto or LispM perhaps we can teach few "programming" concept to let most scholarized people able to script/design their own "home environment" on a desktop otherwise it's only a waste of time especially if is done as classic high schools in Italy or Sweden (starting with some Pascal dialect end try to offer C or JS after).
  - tuukkah 8y ago
    Finland doesn't do it like Italy or Sweden (let alone how they did it 20 years ago). Instead, kids are more likely to start with Scratch or similar: https://scratch.mit.edu https://scratch.mit.edu

Mortiffer 8y ago

Machine Learning is Alchemy https://youtu.be/x7psGHgatGM https://youtu.be/x7psGHgatGM . We need to understand optimization to advance this field not train thousands of monkeys to press play and hope for a nice result. Also, why did they not decide to teach 1% of the population basic coding. Now that could transform a society.

bemmu 8y ago
Basic programming skills have been a part of the Finnish primary school curriculum since 2016. By sixth grade students are expected to "create working programs in a graphical programming environment". Junior high includes "basic algorithmic thinking", more programming and embedded programming. Likely in practice means trying out Scratch in primary school and creating robots in junior high. Source: https://peda.net/ulvila/peruskoulut/harjunp%C3%A4%C3%A4n-koulu/opetus/ol2/tjvs/oo2/oop https://peda.net/ulvila/peruskoulut/harjunp%C3%A4%C3%A4n-kou...

goldenkey 8y ago

Most machine learning models are nothing but souped up regression that swaps out standard polynomials for matrix-valued polynomials with some x'es replaced by non-linear activation functions like tanh(x) The magic is in the toolkits that allow one to build these complex expressions through net chain composition, and provide symbolic differentiation to easily calculate gradient on hugely complex net chain graphs. The avg person isn't going to benefit from ML unless you also teach them the old-hat statistical fitting methods that worked well enough before ML came on the scene. Things like SVD, MPCA: https://en.wikipedia.org/wiki/Singular_value_decomposition https://en.wikipedia.org/wiki/Singular_value_decomposition https://en.wikipedia.org/wiki/Multilinear_principal_component_analysis https://en.wikipedia.org/wiki/Multilinear_principal_componen... Old stats techniques like: https://en.wikipedia.org/wiki/Elastic_net_regularization https://en.wikipedia.org/wiki/Elastic_net_regularization Its not worth training a bunch of folk who cant go deep into the heavy mathematics, statistics, and epistomology of what ML really is in terms of manifolds. Just show them what ML can and cannot do, if its not possible to give them the comprehensive education. And besides, most people, once they find out ML is a shit ton of math and as profound and based as the theory of functions, shakes their head and trods off. They wanted magic soup and you gave them the biggest questions about existence..about patterns..forms..things..about consciousness, intelligence, and life, about meaning. Don't expect the avg lowbrow person to want to explore ML once they get hit with the reality of its implications, rigor, and depth.

zozbot123 8y ago
> Most machine learning models are nothing but souped up regression that swaps out standard polynomials for matrix-valued polynomials with some x'es replaced by non-linear activation functions like tanh(x) Well, not quite. The non-linear activation feature is found already in "generalized linear models" (as a 'link function'). The typical "deep learning" model is a hierarchical/multi-level version of the same - and just like any other hierarchical/multi-level model, the point of that is to account in a parsimonious way for increasingly-complicated interactions among the regressors/features. But I think your broader point is right; there is a lot of hype in ML that derives purely from a lack of familiarity with basic statistical principles.

hyperpallium 8y ago

Is AI settled enough that today's state-of-the-art is a stable foundation that can be reliably built upon... or are revolutionary changes just around the corner? Or, it is that the application of some generic AI, that can use any upcoming changes? Perhaps we have a few more twenty year hype-winter cycles of NN before we know what we're doing...

hyperpallium 8y ago
> intention to "support democracy," ... raise awareness about the opportunities and risks of AI ... where they want their government to invest. > "That’s how society works — if enough people say they don’t like it, then we regulate it,” Agree, democracy needs uninformed voters. But the above was just the origin. Now the course seems more like encouraging people to see applications of AI in their regular work. Like pure vs applied maths. Agree: technology transfer/commercialization of AI will be the richest industry the world has ever seen. [ Though it's a bit like applications of computers [funfact: many software ideas were initally called AI... like how subjects moved from philosophy to science when they got actual facts]. Although computers are an "industry", their applications are considered vertical, i.e. as part of the industry they are applied to. Same thing happened to physics. So AI applications won't be "an industry", but in every industry. ] Another question is whether the application best starts from the AI end or the application end. You need both, but at this early stage, it's still requires an intertwined "integrated" collaboration. I don't think we're yet at the point where you just add magic AI pixie dust to a problem. But it can't hurt getting people introduced to it and thinking about it; and the democratic point remains true.

roel_v 8y ago

Can someone explain what is in this 'Elements of AI' course, since that doesn't seem to be described in the article? I'm just having a hard imagining what can be taught in a few months to e.g. the dentist in the article and still be 'practical'.

anttipoi 8y ago
https://www.elementsofai.com https://www.elementsofai.com It's not a course where you learn how to implement algorithms, but a general introduction to the concepts and problems that typically are treated under the label 'AI'.
- YeGoblynQueenne 8y ago
  As usual, this is a course that completely ignores the first, oh, 60 or so years of artificial intelligence research which were dominated by logic-based AI, and places most of the focus on deep learning, as the only kind of machine learning that it talks about at any length. Sometimes, I despair. It's like AI started in 2012 - and was wrapped up the same year. Deep neural nets, problem solved, AI is all done and dusted.
  - jks 8y ago
    Did you click through to the course? Chapter 2 is about search algorithms and planning, albeit not in very much depth.
    - YeGoblynQueenne 8y ago
      Yes, of course I did. The relative attention given to the majority of work on AI and the last six years or so is disproportionate, to say the least.

ekswisey 8y ago

This is rather old news already by now. It's been a few months

deleted 8y ago

[deleted]

vidoc 8y ago

That's why we should all vape !

MrTonyD 8y ago

I've always admired Sweden for committing to robotics (it was back in the 90's I think, at a time when I was doing robotics work for Fanuc and GE). They went from nothing to becoming a major robotics player over decades. In contrast, I think committing to AI is a mistake - the market is fundamentally different. To put it simply - there is lots and lots of work to be done in robotics, over decades, while, in contrast, there is a big burst of work to be done in AI, followed by relatively little work (compared to the scale of robotics.) I admire Finland, and I hope somebody out there figures out the business difference before they lose decades to opportunity cost.