June 20, 2020 • #
Martin Gurri is one of the best minds we have for the current moment. Make sure to subscribe to his essays on the Mercatus Center’s “The Bridge.”
The American people appear to be caught in the grip of a psychotic episode. Most of us are still sheltering in place, obsessed with the risk of viral infection, primly waiting for someone to give us permission to shake hands with our friends again. Meanwhile, online and on television, we watch, as in a dream, crowds of our fellow citizens thronging into the streets of our cities, raging at the police and the established order generally, with some engaged in arson, looting, and violence.
On one side, a reflexive obedience to authority. On the other, a near-absolute repudiation of the rules of the system—for some, of any restraint whatever. The future will be determined by the uncertain relationship between these two extremes.
My friend and former colleague Kevin Stofan wrote the launch post for DataRobot’s latest product additions for spatial AI. Pretty amazing additions to their platform.
Good to see the Mapillary team add their computer vision tech and work with OpenStreetMap to Facebook. Big congrats to the team!
August 3, 2019 • #
A list of broad laws that apply to all fields. Thoughtful stuff as always from Morgan Housel:
6. Parkinson’s Law: Work expands to fill the time available for its completion.
In 1955 historian Cyril Parkinson wrote in The Economist:
IT is a commonplace observation that work expands so as to fill the time available for its completion. Thus, an elderly lady of leisure can spend the entire day in writing and despatching a postcard to her niece at Bognor Regis. An hour will be spent in finding the postcard, another in hunting for spectacles, half-an-hour in a search for the address, an hour and a quarter in composition, and twenty minutes in deciding whether or not to take an umbrella when going to the pillar-box in the next street. The total effort which would occupy a busy man for three minutes all told may in this fashion leave another person prostrate after a day of doubt, anxiety and toil.
His point was that resources can exceed needs without people noticing. The number of employees in an organization is not necessarily related to the amount of work that needs to be done in that organization. Workers will find something to do – or the appearance of doing something – regardless of what needs to be done.
This is a neat collaboration tool for distributed teams that just launched. It’s built on Slack and has integrations built for many of the common productivity tools that modern remote teams are familiar with. I’m keen to take a look at this for doing more real-time work with my remote co-workers.
As computer vision continues its advance, machines are getting better and better at converting images and video into structured data. Computers have historically had sensor data feeds through text, binary data streams, and user inputs; eventually they’ll all have visual inputs, as well.
January 12, 2019 • #
This excellent guide shows how to combine take imagery from OpenAerialMap and buildings from OpenStreetMap, and combine to train a model for automated feature extraction. It uses an open source tool from Mapbox called RoboSat combined to compare a GeoTIFF from OAM with a PBF extracts from OSM. Very cool to have a generalized tool for doing this with open data.
An excellent roundup (with tons of ancillary linked sources) on the state of various parts of computer security, from programming, to browsers, to social engineering.
From Tom Patterson, the Equal Earth map uses the equal earth projection to show countries with their true relative sizes. No more ginormous Russia or Africa-sized Greenland.
November 30, 2018 • #
This week was Amazon’s annual re:Invent conference, where they release n + 10 new products for AWS (where n is the number of products launched at last year’s event). It’s mind-boggling how many new things they can ship each year.
SageMaker was launched last year as a platform for automating machine learning pipelines. One of the missing pieces was the ability to build training datasets with your own custom data. That’s the intent with Ground Truth. It supports building your dataset in S3 (like a group of images), creating a labeling task, and distributing it to a team to annotate to train a model. It integrates with Mechanical Turk, Amazon’s network of third-party vendors, or your own private team. This is awesome for anyone with massive datasets but no easy-to-use system to build the training info.
This, combined with their Rekognition product open up some interesting possibilities for image recognition use cases I’d like to test out.
