- 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!”
"networks" entries
Mark Burgess on a CS narrative, orders of magnitude, and approaching biological scale
The O'Reilly Radar Podcast: "In Search of Certainty," Promise Theory, and scaling the computational net.
Subscribe to the O’Reilly Radar Podcast to track the technologies and people that will shape our world in the years to come.
In this week’s Radar Podcast episode, Aneel Lakhani, director of marketing at SignalFx, chats with Mark Burgess, professor emeritus of network and system administration, former founder and CTO of CFEngine, and now an independent technologist and researcher. They talk about the new edition of Burgess’ book, In Search of Certainty, Promise Theory and how promises are a kind of service model, and ways of applying promise-oriented thinking to networks.
Here are a few highlights from their chat:
We tend to separate our narrative about computer science from the narrative of physics and biology and these other sciences. Many of the ideas of course, all of the ideas, that computers are based on originate in these other sciences. I felt it was important to weave computer science into that historical narrative and write the kind of book that I loved to read when I was a teenager, a popular science book explaining ideas, and popularizing some of those ideas, and weaving a story around it to hopefully create a wider understanding.
I think one of the things that struck me as I was writing [In Search of Certainty], is it all goes back to scales. This is a very physicist point of view. When you measure the world, when you observe the world, when you characterize it even, you need a sense of something to measure it by. … I started the book explaining how scales affect the way we describe systems in physics. By scale, I mean the order of magnitude. … The descriptions of systems are often qualitatively different with these different scales. … Part of my work over the years has been trying to find out how we could invent the measuring scale for semantics. This is how so-called Promise Theory came about. I think this notion of scale and how we apply it to systems is hugely important.
You’re always trying to find the balance between the forces of destruction and the forces of repair.
Four short links: 31 July 2015
Robot Swarms, Google Datacenters, VR Ecosystem, and DeepDream Visualised
Graphs in the world: Modeling systems as networks
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
Mark Granovetter famously researched job hunting and discovered the Strength of Weak Ties. Read more…
Four short links: 7 October 2014
Chinese Makers, Code Projects, Distributed Data Structures, and Networked Games
- On the Maker Movement in China (Clay Shirky) — Hardware hacking hasn’t become a hot new thing in China because it never stopped being a regular old thing.
- A History of Apache Storm and Lessons Learned (Nathan Marz) — his lessons on building, promoting, releasing, maintaining, governance … all worth reading.
- Tango: Distributed Data Structures Over a Shared Log — provides developers with the abstraction of a replicated, in-memory data structure (such as a map or a tree) backed by a shared log. (via paper summary)
- Making Fast-Paced Multiplayer Networked Games is Hard (Gamasutra) — This may all sound like smoke and mirrors because that is exactly what it is – we are just maintaining the illusion the game is playing out in wall clock time even though updates are arriving from the past.
The coming of the industrial internet
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…
Four short links: 20 February 2013
Corporate Networks, SimCity Analysis, Monetizing Memes, and Javascript Autocomplete
- 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.
- typeahead.js (GitHub) — Javascript library for fast autocomplete.
Wireless sensor networks can see and shape the world
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.
When it Comes to News, Why Won't People Eat Their Vegetables?
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.