- Using Monitoring Dashboards to Change Behaviour — [After years of neglect] One day we wrote some brittle Ruby scripts that polled various services. They collated the metrics into a simple database and we automated some email reports and built a dashboard showing key service metrics. We pinpointed issues that we wanted to show people. Things like the login times, how long it would take to search for certain keywords in the app, and how many users were actually using the service, along with costs and other interesting facts. We sent out the link to the dashboard at 9am on Monday morning, before the weekly management call. Within 2 weeks most problems were addressed. It is very difficult to combat data, especially when it is laid out in an easy to understand way.
- Quiet Mitsubishi Cars — noise-cancelling on phone calls by using machine learning to build the filters.
- NSF Requiring Public Access — NSF will require that articles in peer-reviewed scholarly journals and papers in juried conference proceedings or transactions be deposited in a public access compliant repository and be available for download, reading, and analysis within one year of publication.
- Filtered for Capital (Matt Webb) — It’s important to get a credit line [for hardware startups] because growing organically isn’t possible — even if half your sell-in price is margin, you can only afford to grow your batch size at 50% per cycle… and whether it’s credit or re-investing the margin, all that growth incurs risk, because the items aren’t pre-sold. There are double binds all over the place here.
"machine learning" entries
Tips on how to build effective human-machine hybrids, from crowdsourcing expert Adam Marcus.
In a recent O’Reilly webcast, “Crowdsourcing at GoDaddy: How I Learned to Stop Worrying and Love the Crowd,” Adam Marcus explains how to mitigate common challenges of managing crowd workers, how to make the most of human-in-the-loop machine learning, and how to establish effective and mutually rewarding relationships with workers. Marcus is the director of data on the Locu team at GoDaddy, where the “Get Found” service provides businesses with a central platform for managing their online presence and content.
In the webcast, Marcus uses practical examples from his experience at GoDaddy to reveal helpful methods for how to:
- Offset the inevitability of wrong answers from the crowd
- Develop and train workers through a peer-review system
- Build a hierarchy of trusted workers
- Make crowd work inspiring and enable upward mobility
What to do when humans get it wrong
It turns out there is a simple way to offset human error: redundantly ask people the same questions. Marcus explains that when you ask five different people the same question, there are some creative ways to combine their responses, and use a majority vote. Read more…