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Michael was more likely to break through his attackers with power and strength, while Kobe often tries to finesse his way through mass pileups. Michael was stronger, with bigger shoulders and a sturdier frame. He also had large hands that allowed him to control the ball better and make subtle fakes. Jordan was also more naturally inclined to let the game come to him and not overplay his hand, whereas Kobe tends to force the action, especially when the game isn’t going his way. When his shot is off, Kobe will pound away relentlessly until his luck turns. Michael, on the other hand, would shift his attention to defense or passing or setting screens to help the team win the game

—Phil Jackson points out the differences, as he sees it, between Michael Jordan and Kobe Bryant in an excerpt from his forthcoming book Eleven Rings: The Soul of Success. (via nbaoffseason)

It’s about moments in life that are great but don’t last. They don’t go on, but you always have the memory and they have an effect on you. That’s what I was thinking about.

Sofia Coppola on Lost In Translation

(via stoweboyd)

(Source: fuckyeahsofia-coppola, via stoweboyd)

101 Business Models


Selecting the right business model for your business is crucial. In this post I intend to build on some of the work of Fred Wilson and others in the exploration of web and mobile revenue models. I propose there are two major classes to revenue models: trade methods and trade objects. A trade method would be for example, “licensing”, whereas, a trade object would be the “data”. Here is a fairly exhaustive list, extended from the original collaboration on hackpad. It is fairly interesting to be aware of all the possible combinations of trade methods and objects as it can help predict new startups or guide your own business model choice.imageTrade methods:


  • Normal ads
  • Display Ads - e.g. Yahoo!
  • Search Ads - e.g. Google
  • Text Ads - e.g. Google
  • Video Ads - e.g. Hulu
  • Audio Ads - e.g. Pandora
  • Paid content links - e.g. Outbrain
  • Email Ads - as done by Yahoo, MSN
  • Classifieds - e.g. Craiglist
  • Featured listings - e.g.  Yelp, Super Pages;
  • Recruitment Ads - e.g. LinkedIn
  • Promoted Content - e.g. Twitter, Tumblr
  • Lead Generation - e.g. MoneySuperMarket, ZocDoc
  • Affiliate Fees - e.g. Amazon Affiliate Program
  • Ad Retargeting - e.g. Criteo/perfectaudience
  • Real-time Intent Ad Delivery
  • Location-based offers - ex/ Foursquare
  • Sponsorships / Site Takeovers -  e.g. Pandora


  • Retailing - e.g. Zappos
  • Marketplace - e.g. Etsy
  • Crowdsourced Marketplace - e.g. Threadless
  • Excess Capacity Markets - Uber, AirBnB
  • Vertically Integrated Commerce - e.g. Warby Parker
  • Aggregator - e.g. Lastminute.com
  • Flash Sales:  Gilt Groupe, Vente Privee
  • Group buying - e.g. Groupon
  • Digital goods / downloads - e.g. iTunes
  • Virtual goods - e.g. Zynga
  • Training - e.g. Cloudera (??), -> Coursera
  • Pay what you want - e.g. Radiohead
  • Commission - e.g. SharesPost
  • Commission per order - e.g. Seamless, GrubHub
  • Auction - e.g. eBay
  • Reverse Auction - ex Priceline
  • Barter for services e.g. SwapRight

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Donald Knuth on biology and computer science (1993)

There’s millions and millions of unsolved problems. Biology is so digital, and incredibly complicated, but incredibly useful. The trouble with biology is that, if you have to work as a biologist, it’s boring. Your experiments take you three years and then, one night, the electricity goes off and all the things die! You start over. In computers we can create our own worlds. Biologists deserve a lot of credit for being able to slug it through.

It is hard for me to say confidently that, after fifty more years of explosive growth of computer science, there will still be a lot of fascinating unsolved problems at peoples’ fingertips, that it won’t be pretty much working on refinements of well-explored things. Maybe all of the simple stuff and the really great stuff has been discovered. It may not be true, but I can’t predict an unending growth. I can’t be as confident about computer science as I can about biology. Biology easily has 500 years of exciting problems to work on, it’s at that level.

.@vineapp hits the zeitgeist. cc @dhof – View on Path.

.@vineapp hits the zeitgeist. cc @dhof – View on Path.