Data?, Data!, Data...

  • Mathematicians Discover Prime Conspiracy

    • '솟수'에 대한 이야기
    • 'Random Primes'에 관한 부분은 읽어 볼 만함

    Prime numbers, of course, are not really random at all — they are completely determined. Yet in many respects, they seem to behave like a list of random numbers, governed by just one overarching rule: The approximate density of primes near any number is inversely proportional to how many digits the number has.

  • DeepMind founder Demis Hassabis on how AI will shape the future

    • 'Demis Hassabis'의 인터뷰
    • 뭐든 학습할 수 있는 '방법'을 고민하고 있다는 점에서 확실히 '챔피언'은 다르다는 것을 느낌

    we think it’s possible to ground it all the way to pure learning.

    • 게임이 얼마나 중요한 것인지...

    [...] I’d been planning it for more than 20 years, in a way. If you view all the things I’ve done through a prism of eventually starting an AI effort, then it kind of makes sense what I chose to do. If you’re familiar with my stuff at Bullfrog and so on, you’ll know that AI was a core part of everything I wrote and was involved with, and obviously Peter Molyneux’s games are all AI games as well. Working on Theme Park when I was 16 or 17 years old was quite a seminal moment for me in terms of realizing how powerful AI could be if we really tried to extend it. We sold millions of copies, and so many people enjoyed playing that game, and it was because of the AI that adapted to the way you played. We took that forward and I tried to extend that for the rest of my games career, and then I switched out of that back to academia and neuroscience because I felt around the mid-2000s that we’d gone as far as we could trying to sneak in AI research through the back door while you’re actually supposed to be making a game. And that’s hard to do, because publishers just want the game, right?

  • Introduction to Scikit Flow

    • 'TensorFlow'를 잘 사용하기 위한 Scikit Flow' 튜토리얼
  • Insightful applications: The next inflection in big data

    • Big Data의 'Key' 정보를 잘 활용해야 한다는 것을 잘 설명하고 있음

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