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1. They are not teaching CS people, but a random 1% slice of the population. 2. Where did I not condone? I made an observation what I think leads to better out

1. They are not teaching CS people, but a random 1% slice of the population. 2. Where did I not condone? I made an observation what I think leads to better outcomes. I said both is desirable but culturally only one thing seems to happen. Before you angrily accuse me of "Delusional gatekeeping", maybe re-read (or maybe for the first time read) both the article and my comment. Your confrontational tone does not help the discussion and is not in the spirit of hackernews to assume the best intentions.

fermienrico 8y ago
I apologize for my tone but no one is accusing you. I am criticizing your thinking and your argument. Photography is democratized to the point where there is so much noise. Everyone has a camera with them at all times. If you want to be a professional photographer today, it is almost impossible barring journalism or wedding photography. I feel like ML researchers (again, not particularly you so don't take it personally) feel threatened by the mass adoption, marketing buzz and the whole ML/AI enchilada. Everyone is getting on it including the topic of this thread - i.e. the Finnish government. This is honestly what I see when I read your parent comment. If you're offended by it, then may be you can balance your argument so it doesn't appear to be gate-keeping elitism. In fact, you've admitted it is controversial!
- high_derivative 8y ago
  Thank you. Well here is a potential counterpoint: I think one could also imagine a world where there will be a cannibalization/consolidation on the lower end of the market because of the democratization (which I am not saying is bad or good because I am not sure about the effects ML has on people and democracies, but that is another discussion). Rather, I observe that nobody today would hire someone to (in essence) build numpy functionality. Yet there are a lot of jobs in ML/AI currently which amount to building things that will be commoditized within years (and be used by everyone like numpy today). So in my opinion learning AI basics will not necessarily lead to more AI jobs or startups because these basic features are commoditized via big tech open source. Second, on applications: My research is actually in the applied domain and that's where my argument mostly stems from. Doing novel, valuable applications in AI requires concentrated resources and expertise. For example, if you think about self-driving cars as an extremely high-value application, they require highly specialized domain expertise in various domains and machine learning combined with massive compute resources. Simple applications (e.g. applying basic machine learning tools to common workflows and processes) are prone to undergo commoditization precisely because they are obvious. So I do not think the gatekeeping argument holds because there is no way around obtaining deep and wide expertise to generate valuable application IP. So for a country wanting to focus on applications, I still think there is a good argument that concentrating resources is a more successful approach.
  - petra 8y ago
    >> Simple applications (e.g. applying basic machine learning tools to common workflows and processes) are prone to undergo commoditization precisely because they are obvious Yes, Simple ML will be a commodity. Like Arduino, Ruby-on-Rails, WordPress, etc. But in the right hands, having such tools years before the competition, could be a great thing, one that could lead to real competitive advantages. For example, in Israel ~15% think about starting a business. That's not that far from the whole population. So if you offered them the right education, and they played with the tools, maybe it would lead to new businesses. And in the end, it's impossible to tell who will come with that great idea.

fermienrico 8y ago

I apologize for my tone but no one is accusing you. I am criticizing your thinking and your argument. Photography is democratized to the point where there is so much noise. Everyone has a camera with them at all times. If you want to be a professional photographer today, it is almost impossible barring journalism or wedding photography. I feel like ML researchers (again, not particularly you so don't take it personally) feel threatened by the mass adoption, marketing buzz and the whole ML/AI enchilada. Everyone is getting on it including the topic of this thread - i.e. the Finnish government. This is honestly what I see when I read your parent comment. If you're offended by it, then may be you can balance your argument so it doesn't appear to be gate-keeping elitism. In fact, you've admitted it is controversial!

high_derivative 8y ago
Thank you. Well here is a potential counterpoint: I think one could also imagine a world where there will be a cannibalization/consolidation on the lower end of the market because of the democratization (which I am not saying is bad or good because I am not sure about the effects ML has on people and democracies, but that is another discussion). Rather, I observe that nobody today would hire someone to (in essence) build numpy functionality. Yet there are a lot of jobs in ML/AI currently which amount to building things that will be commoditized within years (and be used by everyone like numpy today). So in my opinion learning AI basics will not necessarily lead to more AI jobs or startups because these basic features are commoditized via big tech open source. Second, on applications: My research is actually in the applied domain and that's where my argument mostly stems from. Doing novel, valuable applications in AI requires concentrated resources and expertise. For example, if you think about self-driving cars as an extremely high-value application, they require highly specialized domain expertise in various domains and machine learning combined with massive compute resources. Simple applications (e.g. applying basic machine learning tools to common workflows and processes) are prone to undergo commoditization precisely because they are obvious. So I do not think the gatekeeping argument holds because there is no way around obtaining deep and wide expertise to generate valuable application IP. So for a country wanting to focus on applications, I still think there is a good argument that concentrating resources is a more successful approach.
- petra 8y ago
  >> Simple applications (e.g. applying basic machine learning tools to common workflows and processes) are prone to undergo commoditization precisely because they are obvious Yes, Simple ML will be a commodity. Like Arduino, Ruby-on-Rails, WordPress, etc. But in the right hands, having such tools years before the competition, could be a great thing, one that could lead to real competitive advantages. For example, in Israel ~15% think about starting a business. That's not that far from the whole population. So if you offered them the right education, and they played with the tools, maybe it would lead to new businesses. And in the end, it's impossible to tell who will come with that great idea.