All this study says is that there's a correlation of Mensa membership to a higher likelihood of certain disorders. It does _NOT_ establish any causal links, or even that Mensa membership is representative of the much much larger population of people who can get a 98th percentile score on an IQ test. Perhaps disorders cause people to join Mensa? Who knows.
Just because correlation doesn't imply causation doesn't mean you should negate it causation. You need correlation to exist to even have causation so correlation is evidence for causation.
Head of engineering at Foursquare here. Thanks for all the enthusiasm around our story. I’ve been at Foursquare since 2010 and can share some additional insight.
If you're an engineer building out a location-based product, and you’re curious how you can play around with our location data, we do have one of the world's most robust place databases. Twitter, Microsoft, Samsung, Snapchat, Apple, Uber, Pinterest —some of the world’s biggest tech companies— are building products on top of our Places database and API. We have a good-size free tier, and it's easy to get started: https://developer.foursquare.com/
The fact that it’s considered to be one of the most accurate databases, and that it’s widely trusted (used by more than 100K developers), didn’t come easily. The accuracy of our our place search API has been steadily improving over the past seven years. To do it well is a really challenging engineering problem. The sensor signals available from iOS/Android location services in today’s phones are often only accurate to tens of meters—especially when indoors. And this is an improvement! So we've taken the billions of check-ins we've collected since 2009 to basically create a model of what physical places look like from the perspective of a mobile device.
We continue to capture training label data from Foursquare City Guide and Foursquare Swarm usage, which allows us to continuously improve our place search model. A lot of complex machine learning and infrastructure goes into solving this problem. And by the way, Place search is just one of Foursquare’s many engineering challenges. We've been innovating and building new products over the past eight years. In March, we launched our Pilgrim SDK. There are even bigger challenges and opportunities ahead...
I know this because I've been here almost since the beginning: Right now is the most exciting time in the company's evolution.
It's important to mention that we take our user data privacy extremely seriously. Some of the products we're currently working on, including the ones that are mentioned by the Entrepreneur article, are built on anonymized and aggregated visit data. The products that we're building don't expose any individual visitation data at any point. We are forthcoming with our community about how we use our data, and we work hard to create engaging apps that make cities easier to use through search & discovery and checking in.
As we continue to rapidly scale and grow we are hiring in both SF and NYC for almost every area of engineering. We're especially interested in experienced iOS, Android, data pipeline (kafka, hadoop, spark, scalding), and ML engineers.
Hi. Since you brought up privacy.. Where exactly does Foursquare gather its location data from for these enterprise reports? Is it exclusively from "checkins" on Foursquare apps, or does it include locations provided via lookups to the Foursquare API places database from various 3rd party apps?
I've always wondered how deep the data could be if it was just Foursquare checkins, given the decline in usage of the apps. Yet I only ever hear about "billions of checkins" as the source. Not billions of queries. It doesn't quite add up for me.
I kind of feel that if Foursquare is tracking user locations via apps that use its API, that should be more clearly stated. Is it? Thanks.
We make the Foursquare and Swarm apps. Foursquare is a place recommendation engine with worldwide coverage. Swarm is an app for checking in to places you go to share with friends, life log, get perks and win prizes, or just for quirky fun.
Built on the foundation of our apps, we also have suite of location intelligence products. Our venue database powers products by Apple, Microsoft, Uber, Samsung, Twitter and more.
We're hiring for a variety of positions in NYC and SF:
- Infrastructure Engineers - distributed systems in Scala and Go
- Ad Tech Engineers - real time bidding at 100k QPS. Ad effectiveness measurement based on Foursquare/Swarm place visits
- Android/iOS Engineers - Foursquare and Swarm apps
