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Greg Linden
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Cute software teardown of Pokemon Go. Lots of details.
We have been wanting to write a blog post about reverse engineering for quite some time, but could never find the perfect app to take a look at. And then, out of nowhere, Pokémon Go took over the world in a week. We made some interesting findings ;-). For an app that was only available in 3 ...
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Cute SMBC comic today on experimentation
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Yahoo just sold to Verizon.
Verizon Communications Inc. will announce plans to buy Yahoo! Inc.’s core assets for about $4.8 billion on Monday, a move that would finally seal the fate of the iconic web pioneer after months of speculation and pressure from investors.
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Most of that is attributable to Alibaba shares though.
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Free upcoming Coursera course on NNets taught by guru Geoff Hinton:
https://www.coursera.org/learn/neural-networks

HT, Gregory Piatetsky on Twitter
https://twitter.com/kdnuggets/status/755398191441440768
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"The Valley’s new enthusiasm is troubling because it suggests an unfounded optimism similar to earlier eras in which the field overpromised and underdelivered. 'Sometimes when I hang around with A.I. enthusiasts here in the valley, I feel like an atheist at a convention of evangelicals'"


The valley has found its next shiny new thing in A.I., and financiers and entrepreneurs are digging in with remarkable exuberance.
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"Giving computers common-sense knowledge is notoriously difficult. Hand-coding knowledge is impossibly time-consuming, and it isn’t simple for computers to learn about the real world by performing statistical analysis of text."
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+Tau-Mu Yi , thanks, in my opinion Deep Learning has not yet contributed anything useful to NLP. So far its been forcing an open door.
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Nice summary of this paper on real-time data processing out of Facebook. The "Lessions Learned" section at the bottom is particularly worth a look.
Realtime Data Processing at Facebook Chen et al. SIGMOD 2016 ‘Realtime Data Processing at Facebook’ provides us with a great high-level overview of the systems Facebook have built to su…
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Yep: "The best teams respect one another’s emotions and are mindful that all members should contribute to the conversation equally ... A shared belief that it is safe to take risks and share a range of ideas without the fear of being humiliated."
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Related, teams with a wide range of experience are a bit slower to start, but yield better outcomes:
https://plus.google.com/+GregLinden/posts/C5mdfjWFAv9
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"Such a firefly would immediately collapse under its own weight and become a black hole"
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Nice example of fine-grained control of data center power and cooling using machine learning to save electricity.
 
Something interesting that we can finally talk about: the AIs are controlling their own datacenters, and it knocks about 15% off our power usage. More specifically, we designed a deep learning system to control things like cooling fans, windows, and other things related to power and cooling, with the objective of minimizing power needs. It turned out that this sort of system reliably outperformed manual control by a lot - enough that we've gradually transitioned datacenters to fully automatic operation.

This is one of those examples of how machine learning can be really useful; at any given instant, its decisions may be roughly as good as a human's would be, but it can make those decisions every few milliseconds and continually adjust things in a way a person couldn't. I expect to see technologies like these greatly increasing the efficiency of all sorts of infrastructure, from power to transport, over the next few years - with corresponding savings in both money and resource usage. 
Google just paid for part of its acquisition of DeepMind in a surprising way.
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The New York Times management column sometimes has some good tidbits: "Now I have a basic belief that almost everyone wants to contribute and do well. Some people, for a whole variety of reasons, have difficulty doing that ... try to help them ... [I want a] questioning culture, where there’s always a smarter way of doing something, and you feel a permanent dissatisfaction with obtained results. Not with a scowl. You can smile about it, but we can do everything better ... Working to simplify ... Why make it more complicated? I’ve always felt that the world is filled with smart people who love complicating stuff."


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Reminds me of something a former boss liked to say: "Nobody goes to work to deliberately do a bad job." 
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Google's re:work team has published in their blog a one-pager I wrote internally at Google a couple of years ago about one of our most successful (and less publicized) approaches to innovation.
Google’s “moonshot factory” is inspiring and ambitious, but there’s a less talked-about route to many of Google’s great achievements -- the consistent, short-term, incremental “roofshots” that make our products better year after year.
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