Blog AF

• Broken Promises: The Housing Market in SF (And Ten Ideas to Fix It)
  Zac Townsend
  

  A clear economic analysis of the housing market in San Francisco, its history, its distortions, and its intricacies. Zac makes good arguments, proposes attainable solutions, and brings examples of other cities arount the U.S. that have solved similar housing crises before.

• The Weird Redemption of SF's Most Reviled Tech Bro
  Lauren Smiley - Backchannel
  

  While the city officials’ skepticism is understandable, their stubbornness to work with a capable person due to his background is not. Two very unexpected things I learned from this piece: 1) San Francisco’s homeless population has been around 6000 for over 25 years. 2) between nonprofits and city departments, $241M/year are spent on supporting San Francisco’s homeless population. That is, roughly $40k per person.

• Declining Mobility and Restrictions on Land Use
  Alex Tabarrok - Marginal Revolution
  
• A 26-Story History of San Francisco
  Alexis Madrigal - The Atlantic
  

  I went to a meetup at 140 New Montgomery this week. The event was unremarkable, but the venue was odd. This essay tells its story.

• On your marks. Get set. Go. The fourth Facebook goldrush just started.
  Jeremy Liew - Lightspeed Venture Partners
  

  Everyone is talking about bots.

• Why Kik Thinks Chatbots Will Kill Webpages
  Cliff Kuang - Fast Company
  
• What the iPhone has done to cameras is completely insane
  Roberto A. Ferdman - The Washington Post
  
• Stop Voter Suppression
  Robert Reich
  
• What Bernie Sanders Gets Right
  Mark Thoma - The Fiscal Times
  

  As usual, Thoma asks the right questions. I am particularly interested in the “how is the social interest is defined?” aspect of his article. When companies, and identities, span across the world, our definitions of society change too.

• Losing Money
  Fred Wilson - AVC
  
• Film Dialogue
  Hanah Anderson and Matt Daniels - Polygraph
  

Between researching camera lenses and teaching myself machine learning, there hasn’t been much reading lately.

• How to Hack an Election
  Jordan Robertson, Michael Riley, and Andrew Willis - Bloomberg
  
• Cities for Everyone
  Paul Krugman - The New York Times
  
• The time that Tony Fadell sold me a container of hummus.
  Arlo Gilbert - Medium
  
• The Lamborghini and The Dingbat
  Let's Go LA
  

  As the source name implies, this is not about San Francisco, but Los Angeles. “…we can’t solve society’s mobility problems by trying to ensure that everyone gets a $250,000 car. We don’t need subsidized Lamborghinis, we need Honda Civics.”

• Mathematicians mapped out every "Game of Thrones" relationship to find the main character
  Adam Epstein - Quartz
  

  Unsurprisingly, its Tyrion.

• Apple at 40: The forgotten founder who gave it all away
  Dave Lee - BBC News
  
• Agility Requires Safety
  Yevgeniy (Jim) Brikman - The Macro
  
• The Future of Capital Mobility
  Samuel Hammond - Plain Text — Medium
  
• Techies
  Helena Price
  

I have been thinking of buying a new 24mm lens, so this weekend I challenged myself to only take pictures with that focal distance. Not zooming is hard, especially when taking photos of strangers you don’t want to get too close to. Here is the outcome: More...

I have spent a lot of time lately trying to understand, and playing around with, computer vision, deep learning, reinforcement learning, and other machine learning models. Between Stanford’s Convolutional Neural Networks for Visual Recognition course, Trask’s neural stack explanation, playing snake with Keras and creating image analogies, I have spent a lot more time than usual coding and training machine learning models after work. More accurately, I have spent hours poring over complex equations I don’t yet fully understand, and waiting for models to converge.

Even if you are not a computer scientist, you should read the intro to reinforcement learning linked below. With some understanding of economic modeling, and a bit of effort, you’ll get the basics of how a system like AlphaGo works. Machine, or otherwise, learning is fun.

• Snapchat's Ladder
  Ben Thompson - Stratechery
  
• Amazon Sent Me Lumber as a Prank
  Ian Bogost - The Atlantic
  
• Your iPhone just got less secure. Blame the FBI.
  Bruce Schneier - The Washington Post
  
• Chat bots, conversation and AI as an interface
  Benedict Evans
  
• How to reduce the cognitive load of your code
  Christian Maioli Mackeprang
  
• Demystifying Deep Reinforcement Learning
  Tambet Matiisen - Computational Neuroscience Lab, University of Tartu
  

• Relationships Are More Important Than Ambition
  Emily Esfahani Smith - The Atlantic
  

  I was born and raised in an extremely tight knit community. With time, we have drifted apart, and I continue to distance myself from it, both in terms of my day-to-day experiences, as well as my expectations from the future. This article’s ideas ring very true: those who stayed back home are probably happier than me.

• Blockchain Technology and Progress in Science
  Albert Wenger - Continuations
  
• Uber efficiency
  James Hamilton - Econbrowser
  
• Review: The Oculus Rift
  Lucas Matney - TechCrunch
  

  While VR seems really interesting, I am way more excited about AR. Much more of a question mark.

• The rise of the ‘gentleman’s A’ and the GPA arms race
  Catherine Rampell - The Washington Post
  
• How to Avoid Brittle Code
  David Rice
  
• Ethereum, a Virtual Currency, Enables Transactions That Rival Bitcoin’s
  Nathaniel Popper - The New York Times
  
• Toy example of deep reinforcement model playing the game of snake
  Ben Meijering - Github
  

  This makes me want to play with Keras. Happy that python is the language of choice for much of Machine Learning.