Four short links: 9 March 2015

Shareable Audio, Designing Robot Relationships, Machine Learning for Programming, and Geospatial Databases

  1. Four Types of Audio That People Share (Nieman Lab) — Audio Explainers, Whoa! Sounds, Storytellers, and Snappy Reviews, the results of experiments with NPR stations.
  2. Designing the Human-Robot Relationship (O’Reilly) — We can use those same principles [Jakob Nielsen’s usability heuristics] and look for implications of robots serving our higher ordered needs, as we move from serving needs related to convenience or performance to actually supporting our decision making to emerging technologies, moving from being able to do anything or be magic in terms of the user interface to being more human in the user interface.
  3. Machine Learning for General Programming — Peter Norvig talk. What more do you need to know?
  4. Why Are Geospatial Databases So Hard To Build?Algorithms in computer science, with rare exception, leverage properties unique to one-dimensional scalar data models. In other words, data types you can abstractly represent as an integer. Even when scalar data types are multidimensional, they can often be mapped to one dimension. This works well, as the majority of [what] data people care about can be represented with scalar types. If your data model is inherently non-scalar, you enter an algorithm wasteland in the computer science literature.
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