终极算法

• 私

  2018-02-21
  A living cell is a quintessential example of a non-linear system. The cell performs all of its functions by turning raw materials into end products through a complex web of chemical reactions. We can discover the structure of this network using symbolist methods like inverse deduction [...] this is difficult because there is no simple linear relationship between these quantitiaes. Rather, the cell maintains its stability through interlocking feedback loops, leading a very complex behavior. Backpropagation is well suited to this problem because of its ability to efficiently learn nonlinear functions.
• 私

  2018-02-18
  Overfitting happens when you have too many hypotheses and not enough data to tell them apart.
• 私

  2018-02-18
  Besides, knowledge is not just a long list of facts. Knowledge is general, and has structure.
• 私

  2018-02-18
  The future belongs to those who understand at a very deep level how to combine their unique expertise with what algorithms do best.
• andrea

  2018-12-27
  The first big worry, as with any technology, is that AI could fall into the wrong hands. … The second worry is that humans will voluntarily surrender control. It starts with robot rights, which seem absurd to me but not to everyone. After all, we already give rights to animals, who never asked for them. –– Google + Master Algorithm = Skynet?
• andrea

  2018-12-27
  In the early days of AI, the common view was that computers would replace blue-collar workers before white-collar ones, because white-collar work requires more brains. But that’s not quite how things turned out. Robots assemble cars, but they haven’t replaced construction workers. On the other hand, machine-learning algorithms have replaced credit analysts and direct marketers. … The common theme is that narrowly defined tasks are easily learned from data, but tasks that require a broad combination of skills and knowledge aren’t. Most of your brain is devoted to vision and motion, which is a sign that walking around is much more complex than it seems; we just take it for granted because, having been honed to perfection by evolution, it’s mostly done subconsciously. ––A neural network stole...
• andrea

  2018-12-27
  Privacy is only one aspect of the larger issue of data sharing, and if we focus on it to the detriment of the whole, as much of the dabate to date has, we risk reaching the wrong conclusions. ... When people have to trade off privacy against other benefits, as when filling out a profile on a website, the implied value of privacy that comes out is much lower than if you ask them abstract questions like “Do you care about your privacy?” But privacy debates are more often framed in terms of the latter. … Privacy is not a zero-sum game, even though it’s often treated like one. ––To share or not to share, and how and where