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Kurt Laitner

How Particle Physics Is Improving Recommendation Engines | MIT Technology Review - 0 views

  • how to deal with recommendations for objects whose value diminishes with the number of people who use it.
  • Clearly the resulting distribution of these different types of particles is entirely different.
  • The analogy here is with goods that any number of people can share or that only one person can have.
  • ...4 more annotations...
  • explore the space between these extremes
  • a single object/state can be shared with a relatively small number of users/particles
  •  Preventing oversubscription ensures that the population of users sample a wider range of DVDs, which in turn provides a broader range of recommendations.
  • Retailers are not just interested in renting DVDs or selling books or whatever. They want to maximise profits.
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    Interesting discussion of rival and nov-rival goods recommendations engine. Goes to scarcity vs abundance, how to manage deamnd for scarce goods.
Kurt Laitner

Graphene supercapacitors: Small, cheap, energy-dense replacements for batteries. - Slat... - 0 views

  • Then something unexpectedly amazing happened. Maher El-Kady, a graduate student in chemist Richard Kaner’s lab at UCLA, wondered what would happen if he placed a sheet of graphite oxide—an abundant carbon compound—under a laser. And not just any laser, but a really inexpensive one, something that millions of people around the world already have—a DVD burner containing a technology called LightScribe, which is used for etching labels and designs on your mixtapes. As El-Kady, Kaner, and their colleagues described in a paper published last year in Science, the simple trick produced very high-quality sheets of graphene, very quickly, and at low cost.
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    old article I thought I had shared, anybody care to try this out? LOL
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