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Getting a Grip on Artificial Intelligence

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This explains why corporations like Google, Facebook, Baidu, and other search engines and social networks with millions of users and almost limitless data have a distinct advantage when it comes to machine learning. Because a lot of the tools being used to develop AI are currently opensource, the possibility of both large and small businesses taking advantage of them to solve very specific problems by optimizing very specific tasks with AI has become a possibility. It also stands to reason that for any positive advantage AI might give honest government administrators, businesses, or individuals, an equally negative advantage could be lent to dishonest organizations or individuals. In terms of an independent, sentient AI system more intelligent than humans, Elon Musk has compared it to knowing that an advanced race of aliens was coming to Earth in the next 10-20 years.


We need to talk about data science skills. Real talk about AI, deep and machine learning - Enterprise Irregulars

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To Bardin's point Silicon Valley firms have a halo, and the fact they're held to very different standards by equities analysts means they can spend a lot more on compensation. Google and Facebook are making money with machine learning, not for machine learning. So far the model is kind of similar to open source in that respect – Web companies are making money with open source. Before going back to the skills shortage a couple of conversations with IBM and Google recently are worth noting, with respect to the AI/ML market.


Getting a Grip on Artificial Intelligence

#artificialintelligence

This explains why corporations like Google, Facebook, Baidu, and other search engines and social networks with millions of users and almost limitless data have a distinct advantage when it comes to machine learning. Because a lot of the tools being used to develop AI are currently opensource, the possibility of both large and small businesses taking advantage of them to solve very specific problems by optimizing very specific tasks with AI has become a possibility. Keeping AI and Minds Open is Our Best Defense Making sure that no single corporation or government acquires such an advantage, negating the temptation to exploit a monopoly of technology as has been done countless other times throughout human history, requires the playing field to remain as even as possible. The Elephant in the Room: The Rise of Sentient AI In terms of an independent, sentient AI system more intelligent than humans, Elon Musk has compared it to knowing that an advanced race of aliens was coming to Earth in the next 10-20 years.


Flipboard on Flipboard

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If machines, robots, and technology are to make better, more contextual judgments of human behaviors, the next step is ultimately Emotion AI. Think of it like this – if you bring good to emotion AI, it will bring good to you. Emotion AI services will lose trust, receive negative perceptions and ultimately fail. To capitalize on the use of emotion AI, whether that's in advertising, entertainment, sports & performance or health & well being, it must be done with trust and transparency.


A new hope for personal privacy

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However, as we have seen from an earlier article in this series, consent, in the modern context, is structurally flawed. What if, instead of protecting privacy through the data subject's consent, we make the controller responsible for ensuring no harm is visited on the subject as a result of its processing? This is particularly true, as was discussed in an earlier article in this series, when the programming choices based upon which the algorithms are built allowed bias to creep into the algorithms. Just as companies subject themselves to an annual financial audit, they will, to the extent that they collect and process data, have to undergo a regular data audit to assess the extent to which their data processes cause harm to the individual data subjects whose data they process.