Peter Norvig at Startup School 08
Why Hacker News recommends it
HN points to it as a source for Norvig's 'unreasonable effectiveness of data' argument and for his views on image search and the semantic web.
What it is
Peter Norvig, then Director of Research at Google, talks at Startup School 2008 about leveraging large amounts of data and about technical challenges in Google projects such as image search. A central idea is that data can beat hand-written programming.
Recommended by 2 HN commenters across 2 different months, 2009 to 2014.
What Hacker News said
Recommends mindcrime · 2011-07 · on “Ask HN: What are the best videos to watch about building startups?”
[LINK] - (Steve Blank / Eric Ries - part 1) [LINK] - (Steve Blank / Eric Ries - part 2) [LINK] - (Steve Blank / Eric Ries - part 3) [LINK] - (Steve Blank at the Startup Lessons Learned conference) [LINK] - (Steve Blank: The Democratization of Entrepreneurship) [LINK] - (Alexander Osterwalder speaking @ Google) [LINK] - (Eric Ries speaking @ Google) [LINK] - (pg at Startup School '08) [this video] - (Peter Norvig at Startup School '08)
Recommends brandonb · 2014-10 · on “Ask HN: Is the semantic web still a thing?”
Peter Norvig put it best: "The semantic web is the future of the web, and always will be." (For what it's worth, the startup school video that quote comes from is worth watching: [this video] )
Cites presty · 2009-03 · on “Official Google Research Blog: The Unreasonable Effectiveness of Data”
This line of thought follows previous posts on the same subject. It's very Norvig-esq ( [this video] ), but there's also [LINK] and also Chris Anderson and Wired's flame bait [LINK] (that month's wired was dedicated to this subject) And like someone at the previous discussions has said, this is the base of the scientific method, not it's death
Cites apu · 2011-10 · on “Peter Norvig talks how search is evolving, thanks to AI algorithms”
Norvig's talk at Startup School '08 went into more details on this: [this video] They do use SIFT (or at least a variant thereof) for finding and describing interest points, but by itself, there is no geometric matching in SIFT. There are various competing approaches on how do it, although in many cases, you can get very good results even without it. (It's very slow to do geometric matching so people often skip that step, or only apply it to the best matches.) Landmark detection is a recent "hot topic" in computer vision, and given a large enough dataset, it essentially works now for the most part.
Cites marshallp · 2012-10 · on “How Long Will Programmers Be So Well-Paid?”
Programming bubble will pop. Automated Machine learning is taking over. Even at google, Jeff Dean has recently stated that his Perceptual AI project is aimed at reducing feature engineering in their machine learning projects. In plain terms this means eliminating the need for programming in their search engines and other machine learning focused projects like google now and google goggles (the mobile app, not google glass). The only programmers left will be to manage cloud computing infrastructure and front end programmers. As things like siri and google now take off, front end programmers will also be in less demand. Microsoft, Apple, and Amazon are also increasingly focusing on machine lea