- Buzz: An Extensible Programming Language for Self-Organizing Heterogeneous Robot Swarms (arXiv) — Swarm-based primitives allow for the dynamic management of robot teams, and for sharing information globally across the swarm. Self-organization stems from the completely decentralized mechanisms upon which the Buzz run-time platform is based. The language can be extended to add new primitives (thus supporting heterogeneous robot swarms), and its run-time platform is designed to be laid on top of other frameworks, such as Robot Operating System.
- Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google’s Datacenter Network (PDF) — Our datacenter networks run at dozens of sites across the planet, scaling in capacity by 100x over 10 years to more than 1Pbps of bisection bandwidth. Wow, their Wi-Fi must be AMAZING!
- Nokia’s VR Ambitions Could Restore Its Tech Lustre (Bloomberg) — the VR ecosystem map is super-interesting.
- Visualising GoogleNet Classes — fascinating to see squirrel monkeys and basset hounds emerge from nothing. It’s so tempting to say, “this is what the machine sees in its mind when it thinks of basset hounds,” even though Boring Brain says, “that’s bollocks and you know it!”
See, extract, and create value with networks.
Networks of all kinds drive the modern world. You can build a network from nearly any kind of data set, which is probably why network structures characterize some aspects of most phenomenon. And yet, many people can’t see the networks underlying different systems. In this post, we’re going to survey a series of networks that model different systems in order to understand different ways networks help us understand the world around us.
We’ll explore how to see, extract, and create value with networks. We’ll look at four examples where I used networks to model different phenomenon, starting with startup ecosystems and ending in network-driven marketing.
Networks and markets
Commerce is one person or company selling to another, which is inherently a network phenomenon. Analyzing networks in markets can help us understand how market economies operate.
Strength of weak ties
Our new research report outlines our vision for the coming-together of software and big machines.
The big machines that define modern life — cars, airplanes, furnaces, and so forth — have become exquisitely efficient, safe, and responsive over the last century through constant mechanical refinement. But mechanical refinement has its limits, and there are enormous improvements to be wrung out of the way that big machines are operated: an efficient furnace is still wasteful if it heats a building that no one is using; a safe car is still dangerous in the hands of a bad driver.
It is this challenge that the industrial internet promises to address by layering smart software on top of machines. The last few years have seen enormous advances in software and computing that can handle gushing streams of data and build nuanced models of complex systems. These have been used effectively in advertising and web commerce, where data is easy to gather and control is easy to exert, and marketers have rejoiced.
Thanks to widespread sensors, pervasive networks, and standardized interfaces, similar software can interact with the physical world — harvesting data, analyzing it in context, and making adjustments in real-time. The same data-driven approach that gives us dynamic pricing on Amazon and customized recommendations on Foursquare has already started to make wind turbines more efficient and thermostats more responsive. It may soon obviate humans as drivers and help blast furnaces anticipate changes in electricity prices. Read more…
- The Network of Global Control (PLoS One) — We find that transnational corporations form a giant bow-tie structure and that a large portion of control flows to a small tightly-knit core of financial institutions. […] From an empirical point of view, a bow-tie structure with a very small and influential core is a new observation in the study of complex networks. We conjecture that it may be present in other types of networks where “rich-get-richer” mechanisms are at work. (via The New Aesthetic)
- Using SimCity to Diagnose My Home Town’s Traffic Problems — no actual diagnosis performed, but the modeling and observations gave insight. I always feel that static visualizations (infographics) are far less useful than an interactive simulation that can give you an intuitive sense of relationships and behaviour. once I’d built East Didsbury, the strip of shops in Northenden stopped making as much money as they once were, and some were even beginning to close down as my time ran out. Walk along Northenden high street, and you’ll know that feeling.
- How the Harlem Shake Went from Viral Sideshow to Global Meme (The Verge) — interesting because again the musician is savvy enough (and has tools and connections) to monetize popularity without trying to own every transaction involving his idea. Baauer and Mad Decent have generally been happy to let a hundred flowers bloom, permitting over 4,000 videos to use an excerpt of the song but quietly adding each of them to YouTube’s Content ID database, asserting copyright over the fan videos and claiming a healthy chunk of the ad revenue for each of them.
Author Robert Faludi on the practical application of wireless sensor networks.
"Building Wireless Sensor Networks" author Robert Faludi discusses the practical application of sensor networks and how he thinks they will evolve to meet a variety of needs.
Chris Lee thinks that people don't get enough news they need, as opposed to want.
One of the basic questions in journalism these days is the one of what news consumers actually want. Chris Lee believes that today’s citizenry is getting too much of what they want, and too little of what they need. With the Tools of Change for Publishing conference approaching, it seemed appropriate to talk to Lee, who has spent his professional life in the trenches of broadcast journalism, about where the industry is going and what the future of news looks like.