Our latest polls-only forecast gives Clinton an 86% chance to win the presidency: https://t.co/2uB2oqpXy4 pic.twitter.com/rhNJpfOxCt
— FiveThirtyEight (@FiveThirtyEight) October 25, 2016
Tuesday, October 25, 2016
Crunch time, Capt.
Monday, September 12, 2016
Sunday, August 14, 2016
Moonshot calculations
Catching up with some reading (They promised us jet packs, New York Times Sunday, July 24, 2016). It is discussing Google’s (Alpha’s) shifting strategy regarding Moonshot VC research endeavors. Scattered about in accompanying pictures are erector sets, oscilloscopes, physical things.
Where fail fast once was the mantra it now is fail faster yet.
Head Xman Astro Teller says: “If you actually want to make the world better – then do what actually makes the world better – and the technology will take care of itself.”
Mr. teller speaks https://m.youtube.com/watch?v=2t13Rq4oc7Aat Ted
The key to technology assessment is to segment according to technology employed, vendor
And end use application. Must important may be end use application. But it is not wholly logical. For Google the end use application of the Killer Kilwauskee variety is still advertising. Which is so very based on psychology, or voodoo economics.
Where fail fast once was the mantra it now is fail faster yet.
Head Xman Astro Teller says: “If you actually want to make the world better – then do what actually makes the world better – and the technology will take care of itself.”
Mr. teller speaks https://m.youtube.com/watch?v=2t13Rq4oc7Aat Ted
The key to technology assessment is to segment according to technology employed, vendor
And end use application. Must important may be end use application. But it is not wholly logical. For Google the end use application of the Killer Kilwauskee variety is still advertising. Which is so very based on psychology, or voodoo economics.
Sunday, July 24, 2016
Notes for a future article on Mahout
Mahout is changing. Its changed over the years from recommender to core engine for the math part.. What users do is put a surface on it, and tweak the algorithms. Contrast that to using a product like Datameer. It may relatively be a black box in terms of how it does what it does. But there is some assurity that it is a path that is tested and you should have less of an adventure in implementing it. Just as you may enlist vendor field engineers in order to do the implementation, you may get to a place in your Mahout build, and opt to bring in a consultant.
Let's look http://www.slideshare.net/chrishalton/build-vs-buy-strategy at build v buy basics.
Let's look http://www.slideshare.net/chrishalton/build-vs-buy-strategy at build v buy basics.
Tuesday, July 12, 2016
Monday, July 4, 2016
Simplexity kilt the cat
Simplexity by Jeffrey Kluger (subtitled Why Simple Things Become Complex and how complex things can be made simple). The book by the then (2008) Time reporter describes a ''newly emerging Science"(Maybe si, maybe no) meant to provide a cross disciplinary view on systems ranging from ant colonies to stock market. The "SFI" San Jose Instituite is the sort of anchor source (let by Prof Gell-Mann). Along the way (p31) he speaks w Brandeis economist Blake Lebaron who has been studying simulations of stock market trading. He has seen repeating patterns: 1-Traders wobble about; 2-one finds a useful stratagem; 3-the others mimic it; 4-diminishing returns set in. THe repeating patterns I think may be relevant to the general flow of the tech bubble that many of us live within. Whether it is ASPs or Deep Learning or Hadoop - a scatter occurs in the discover stage, then, a coalescence around a mean ensues, until a new scatter occurs in a new discovery stage. Think Whac-A-Mole.
Simplexity kilt the cat
Simplexity by Jeffrey Kluger (subtitled Why Simple Things Become Complex and how complex things can be made simple). The book by the then (2008) Time reporter describes a ''newly emerging Science"(Maybe si, maybe no) meant to provide a cross disciplinary view on systems ranging from ant colonies to stock market. The "SFI" San Jose Instituite is the sort of anchor source (let by Prof Gell-Mann). Along the way (p31) he speaks w Brandeis economist Blake Lebaron who has been studying simulations of stock market trading. He has seen repeating patterns: 1-Traders wobble about; 2-one finds a useful stratagem; 3-the others mimic it; 4-diminishing returns set in. THe repeating patterns I think may be relevant to the general flow of the tech bubble that many of us live within. Whether it is ASPs or Deep Learning or Hadoop - a scatter occurs in the discover stage, then, a coalescence around a mean ensues, until a new scatter occurs in a new discovery stage. Think Whac-A-Mole.
https://www.amazon.com/Simplexity-Simple-Things-Become-https://www.amazon.com/Simplexity-Simple-Things-Become-Complex/dp/B002YNS18EComplex/dp/B002YNS18E
https://www.amazon.com/Simplexity-Simple-Things-Become-https://www.amazon.com/Simplexity-Simple-Things-Become-Complex/dp/B002YNS18EComplex/dp/B002YNS18E
Thursday, June 30, 2016
The nature of field data gathering has changed
The nature of field data gathering has changed, as mobile devices and notepad computers find wider circulation. Surveys that once went through arduous roll-up processes are now gathered and digitized quickly. Now, a new stage of innovation is underway, as back-end systems enable users to employ field data for near-real-time decision making. An example in the geographic information system (GIS) space is ESRI's Survey123 for ArcGIS, which was formally introduced at ESRI's annual user conference, held this week in San Diego. To read the rest of the story.
See also Be there when the GIS plays Hadoop
See also Be there when the GIS plays Hadoop
Subscribe to:
Posts (Atom)