- TweetNLP — CMU open source natural language parsing tools for making sense of Tweets.
- Interview with Google X Life Science’s Head (Medium) — I will have been here two years this March. In nineteen months we have been able to hire more than a hundred scientists to work on this. We’ve been able to build customized labs and get the equipment to make nanoparticles and decorate them and functionalize them. We’ve been able to strike up collaborations with MIT and Stanford and Duke. We’ve been able to initiate protocols and partnerships with companies like Novartis. We’ve been able to initiate trials like the baseline trial. This would be a good decade somewhere else. The power of focus and money.
- Schooloscope Open Data Post-Mortem — The case of Schooloscope and the wider question of public access to school data challenges the belief that sunlight is the best disinfectant, that government transparency would always lead to better government, better results. It challenges the sentiments that see data as value-neutral and its representation as devoid of politics. In fact, access to school data exposes a sharp contrast between the private interest of the family (best education for my child) and the public interest of the government (best education for all citizens).
- M-Lab Observatory — explorable data on the data experience (RTT, upload speed, etc) across different ISPs in different geographies over time.
"open source" entries
Nate Oostendorp on manufacturing and the industrial Internet, and Tim O'Reilly and Rod Smith discuss emerging tech.
The Industrial Revolution had a profound effect on manufacturing — will the industrial Internet’s effect be as significant? In this podcast episode, Nate Oostendorp, co-founder and CTO of Sight Machine, says yes — where mechanization ruled the Industrial Revolution, data-driven automation will rule this next revolution:
“I think that when you think about manufacturing 20 years from now, the computer and the network is going to be much more fundamental. Your factories are going to look a lot more like data centers do, where there’s a much greater degree of automation that’s driven by the fact that you have good data feeds off of it. You have a lot of your administration of the factory that will be done remotely or in a back office. You don’t necessarily need to have engineers on a floor watching a machine in order to know what’s going on. I think fundamentally, the number of players in a factory will be much smaller. You’ll have much more technical expertise but a fewer number of people overall in a factory setting.”
According to Oostendorp, we’re already seeing the early effects today in an increased focus on quality and efficiency. Read more…
Your data is telling you what you need to know about turnover and age
To really grasp a free/open source software project, you need to know how the community that develops and supports it is evolving. Attracting lots of new members will be a reason for celebrating success in a young project — but you should also check whether they stick around for a long time. In mature projects, however, you can afford not attracting many new members, as long as you are retaining old ones. The ratio of experienced, long-term members to recent ones also tells you about the quality of the code and need to support members.