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Google Developers Day US - Theorizing from Data

GoogleDeveloperDay · talk · Watch on YouTube

Machine learning & deep learningComputer vision, speech & NLPData science & statistics

What it is

Peter Norvig's 2007 Google talk on theorizing from data, covering what huge datasets can do for language understanding, translation, information extraction and inference. It argues that more data often beats cleverer models.

Why Hacker News recommends it

HN recommends it as the clear explanation of why Google's statistical, data-first approach works.

  • 3 people recommended it
  • 3 different months
  • 1 strong recommendations
  • first 2007, last 2009

What HN commenters said

  1. “You should definitely watch it if you haven't seen it before.”

    Norvig on why more data beats better algorithms.

    henning, 2008-03 · Strong recommendation · in “More data usually beats better algorithms”

  2. “Its a good talk”

    Norvig talk on theorizing from massive amounts of data.

    dood, 2007-12 · Recommendation · in “Google Is All About Large Amounts of Data”

  3. “Peter Norvig does a better job explaining some of it than I ever could.”

    Norvig explains the subtle sophistication of Google's data work.

    timcederman, 2009-08 · Recommendation · in “Ask HN: Access to the Corpus - What Would You Do?”

Excerpts from Hacker News comments, linked to the originals. Summaries and labels were written by a language model from those comments.

Topics: peter norvig, big data, statistical nlp, machine translation, google

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