Iterate or die

Here's a conclusion I've made building consumer products for many years: the speed at which a company innovates is limited by its iteration speed. I don't even mean throughput here. I just mean the cycle time.

From: Erik Bernhardsson

My issue with GPU-accelerated deep learning

I've been spending several hundred bucks renting GPU instances on AWS over the last year. The speedup from a GPU is awesome and hard to deny. GPUs have taken over the field. Maybe following the footsteps of Bitcoin mining there's some research on using FPGA (I know very little about this).

From: Erik Bernhardsson

boot-new

In my previous three blog posts about Boot -- Rebooting Clojure, Building On Boot, and Testing With Boot -- I looked at why World Singles decided to switch from Leiningen to Boot, as well discussing one of the missing pieces for us (testing).

From: Sean Corfield: An Architect's View

Testing With Boot

In Building On Boot, I gave some high level benefits we'd found with Boot, compared to Leiningen, and how it had helped up streamline our build process.

From: Sean Corfield: An Architect's View

Building On Boot

In yesterday's blog post, Rebooting Clojure, I talked about our switch from Leiningen to Boot but, as Sven Richter observed in the comments, I only gave general reasons why we preferred Boot, without a list of pros and cons.

From: Sean Corfield: An Architect's View

Rebooting Clojure

We switched from Leiningen to Boot. What is Boot and why did we switch?Leiningen

From: Sean Corfield: An Architect's View

Some more font links

My blog post about fonts generated lots of traffic – it landed on Hacker News, took down my site while I was sleeping, and then obviously vanished from HN before I woke up. But it also got retweeted by a ton of people.

From: Erik Bernhardsson

Analyzing 50k fonts using deep neural networks

For some reason I decided one night I wanted to get a bunch of fonts. A lot of them. An hour later I had a bunch of scrapy scripts pulling down fonts and a few days later I had more than 50k fonts on my computer.

From: Erik Bernhardsson

Spring MVC Get Controller & Method Name

How to get the current controller and method name Spring MVC Get Controller & Method Name

From: Dan Vega

Sending Async Emails in Spring

In this article I will walk you through how to send email asynchronously in Spring Boot.

From: Dan Vega

I believe in the 10x engineer, but...

The easiest way to be a 10x engineer is to make 10 other engineers 2x more efficient. Someone can be a 10x engineer if they do nothing for 364 days then convinces the team to change programming language to a 2x more productive language.

From: Erik Bernhardsson

Where Did 2015 Go?

I did not intend to stop blogging in 2015 but that's certainly what it looks like here!So what kept me so busy that I didn't get around to blogging anything?

From: Sean Corfield: An Architect's View

Books I read in 2015

Early last year when I left Spotify I decided to do more reading. I was planning to read at least one book per week and in particular I wanted to brush up on management, economics, and technology.

From: Erik Bernhardsson

More MCMC – Analyzing a small dataset with 1-5 ratings

I've been obsessed with how to iterate quickly based on small scale feedback lately. One awesome website I encountered is Usability Hub which lets you run 5 second tests. Users see your site for 5 seconds and you can ask them free-form questions afterwards.

From: Erik Bernhardsson

There is no magic trick

(Warning: super speculative, feel free to ignore) As Yogi Berra said, “It's tough to make predictions, especially about the future”. Unfortunately predicting is hard, and unsurprisingly people look for the Magic Trick™ that can resolve all the uncertainty.

From: Erik Bernhardsson

Using GORM in Spring Boot

Using GORM in Spring Boot

From: Dan Vega

Installing TensorFlow on AWS

Curious about Google's newly released TensorFlow? I don't have a beefy GPU machine, so I spent some time getting it to run on EC2. The steps on how to reproduce it are pretty brutal and I wouldn't recommend going through it unless you want to waste five hours of your live.

From: Erik Bernhardsson

Looking for smart people

I haven't mentioned what I'm currently up to. Earlier this year I left Spotify to join a small startup called Better. We're going after one of the biggest industries in the world that also turns out to be completely broken.

From: Erik Bernhardsson

MCMC for marketing data

The other day I was looking at marketing spend broken down by channel and wanted to compute some simple uncertainty estimates. I have data like this: <th> Total spend </th> <th> Transactions </th> Channel A <td> 2292.

From: Erik Bernhardsson

Interview with a Data Scientist: Erik Bernhardsson

I was featured in Peadar Coyle's interview series interviewing various “data scientists” – which is kind of arguable since (a) all the other ppl in that series are much cooler than me (b) I'm not really a data scientist.

From: Erik Bernhardsson

Spring Boot Application Annotation

Spring Boot Application Annotation

From: Dan Vega

Nearest neighbors and vector models – epilogue – curse of dimensionality

This is another post based on my talk at NYC Machine Learning. The previous two parts covered most of the interesting parts, but there are still some topics left to be discussed. To go back and read the meaty stuff, check out

From: Erik Bernhardsson

Nearest neighbors and vector models – part 2 – algorithms and data structures

This is a blog post rewritten from a presentation at NYC Machine Learning on Sep 17. It covers a library called Annoy that I have built that helps you do nearest neighbor queries in high dimensional spaces.

From: Erik Bernhardsson

Nearest neighbor methods and vector models – part 1

This is a blog post rewritten from a presentation at NYC Machine Learning last week. It covers a library called Annoy that I have built that helps you do (approximate) nearest neighbor queries in high dimensional spaces.

From: Erik Bernhardsson

Presentations about Spotify music recommendations

A couple of people in my old team have been around talking about how Spotify does music recommendations and put together some quite good presentations. First one is Neville Li's presentation about Scala Data Pipelines @ Spotify:

From: Erik Bernhardsson