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January 15 2014

Four short links: 15 January 2014

  1. Hackers Gain ‘Full Control’ of Critical SCADA Systems (IT News) — The vulnerabilities were discovered by Russian researchers who over the last year probed popular and high-end ICS and supervisory control and data acquisition (SCADA) systems used to control everything from home solar panel installations to critical national infrastructure. More on the Botnet of Things.
  2. mclMarkov Cluster Algorithm, a fast and scalable unsupervised cluster algorithm for graphs (also known as networks) based on simulation of (stochastic) flow in graphs.
  3. Facebook to Launch Flipboard-like Reader (Recode) — what I’d actually like to see is Facebook join the open web by producing and consuming RSS/Atom/anything feeds, but that’s a long shot. I fear it’ll either limit you to whatever circle-jerk-of-prosperity paywall-penetrating content-for-advertising-eyeballs trades the Facebook execs have made, or else it’ll be a leech on the scrotum of the open web by consuming RSS without producing it. I’m all out of respect for empire-builders who think you’re a fool if you value the open web. AOL might have died, but its vision of content kings running the network is alive and well in the hands of Facebook and Google. I’ll gladly post about the actual product launch if it is neither partnership eyeball-abuse nor parasitism.
  4. Map Projections Illustrated with a Face (Flowing Data) — really neat, wish I’d had these when I was getting my head around map projections.

March 05 2013

February 28 2013

New vision in old industry

Nathan Oostendorp thought he’d chosen a good name for his new startup: “Ingenuitas,” derived from Latin meaning “freely born” — appropriate, he thought, for a company that would be built on his own commitment to open-source software.

But Oostendorp, earlier a co-founder of Slashdot, was aiming to bring modern computer vision systems to heavy industry, where the Latinate name didn’t resonate. At his second meeting with a salty former auto executive who would become an advisor, Oostendorp says, “I told him we were going to call the company Ingenuitas, and he immediately said, ‘bronchitis, gingivitis, inginitis. Your company is a disease.’”

And so Sight Machine got its name — one so natural to Michigan’s manufacturers that, says CEO and co-founder Jon Sobel, visitors often say “I spent the afternoon down at Sight” in the same way they might say “down at Anderson” to refer to a tool-and-die shop called Anderson Machine.

Sight Machine is adapting the tools and formulations of the software industry to the much more conservative manufacturing sector. Changing its name was the first of several steps the company took to find cultural alignment with its clients — the demanding engineers who run giant factories that produce things like automotive bolts.

At its heart is something of a crossover group — programmers and designers who are comfortable with Silicon Valley-style fast innovation, but who have deep roots in Midwestern industry. Sight Machine’s founders quickly realized that they needed to sell their software as a simple, effective, and modular solution and downplay the stack of open-source and proprietary software, developed by young programmers working late hours, that might make tech observers take notice.

Sight Machine staff with a full-scale mockup of an auto-plant inspection station that they use to test their system.Sight Machine staff with a full-scale mockup of an auto-plant inspection station that they use to test their system.
Sight Machine staff in the Ann Arbor warehouse where they built a full-scale mockup of an auto-plant quality-control station to test their system

“Nate saw these big bottlenecks in the way things were being done” in industrial computer vision, says Sobel. “There were no high-level frameworks like Ruby on Rails, and everything is set up to be pass-fail; there are no higher-level analytics.” Sight Machine set out to build what they hope will become “Rails for vision.”

Sight Machine’s co-founders built much of SimpleCV, an open-source computer vision library that’s designed to be accessible to people who aren’t experts in the field. (O’Reilly has published a book on SimpleCV, written by four of Sight Machine’s principals.)

Sight Machine's software measures grain-flow characteristics in a fastener, using little more than a commercial flat-bed scanner.Sight Machine's software measures grain-flow characteristics in a fastener, using little more than a commercial flat-bed scanner.
Sight Machine’s software measures grain-flow characteristics in a fastener, using little more than a commercial flat-bed scanner.

Anthony Oliver, the company’s CTO and co-founder, worked on automation at a big car plant in Toledo, Ohio, before being laid off during the recession and deciding to switch tracks. “They had 200 cameras at the plant, but they were treating them like black boxes — after the picture was done, they’d throw it out. They weren’t collecting trending patterns, doing self-correction,” he says. The plant had bought computer vision systems from integrators that weren’t making much data available for higher-level analytics.

“There’s a huge disconnect [in heavy industry] from the Internet way of doing things,” says co-founder Kurt DeMaagd, also a Slashdot co-founder. “Process engineers are very data-driven, but they haven’t tried these new tools, and they’re not working in real-time.” Oliver says the goal was to build a system that would raise immediate flags, “as opposed to saying, ‘hey, a week ago we were having quality-control problems.’”

Their system puts a clear emphasis on the value of software rather than hardware (though a few of the industrial-quality components, in particular the CCD cameras they use, remain expensive). It can stand on its own as a module in an automated factory; no system integrator necessary. And, in the modern form, it emphasizes data retention and high-level analytics.

Sight Machine’s first client manufactures bolts — fasteners, as they’re called by industrial insiders — checking the integrity of their steel at the beginning and end of each batch by slicing one open and scanning it on a cheap flatbed scanner. Software discerns the dimensions of the steel’s grain (compression lines that form when the head of the bolt is pounded out) and provides an instantaneous quantitative measure of quality. The previous method had involved employees looking at bolts through microscopes.

Swarming in a tank at a fish farm. Sight Machine's object: to signal the feeding system to stop putting food in the tank once the fish had eaten enough to be satisfied. Photo: courtesy Sight MachineSwarming in a tank at a fish farm. Sight Machine's object: to signal the feeding system to stop putting food in the tank once the fish had eaten enough to be satisfied. Photo: courtesy Sight Machine
Swarming in a tank at a fish farm. Sight Machine’s object: to signal the feeding system to stop putting food in the tank once the fish had eaten enough to be satisfied. Photo: courtesy Sight Machine.

Another client, a fish farm in Michigan, uses Sight Machine’s software to manage feeding — determining when the fish have had their fill by measuring changes in movement and switching off the farm’s auto feeders. Another proposal for an Ann Arbor-based deli and mail-order house would use Sight Machine software to watch for bunch-ups in the production line and tell managers to send help to, say, the jam-labeling station if the employee there is having trouble filling orders fast enough.

And in a live demonstration that I saw at the company’s industrial-park development space, Sight Machine software detected a misapplied badge on the back of an SUV. That’s a problem that could be corrected quickly and easily at an automaker’s quality-control checkpoint, but if a car that doesn’t have four-wheel drive makes it to a dealer’s lot with a chrome “4×4″ badge glued to the tailgate, the logistics and inventory costs of fixing the problem will be substantial.

Cameras photograph a car as it rolls through an inspection station, and signal in real-time whether trim features like badges, taillights, and rims are correct. Photo: Jon BrunerCameras photograph a car as it rolls through an inspection station, and signal in real-time whether trim features like badges, taillights, and rims are correct. Photo: Jon Bruner
Cameras photograph a car as it rolls through an inspection station, and signal in real-time whether trim features like badges, taillights, and rims are correct. Photo: Jon Bruner.

In addition to a real-time check like this one, Sight Machine's software can also aggregate results for higher-level analysis. Engineers can, for instance, call up photos of every yellow car with a bent antenna. Photo: courtesy Sight Machine.In addition to a real-time check like this one, Sight Machine's software can also aggregate results for higher-level analysis. Engineers can, for instance, call up photos of every yellow car with a bent antenna. Photo: courtesy Sight Machine.
In addition to a real-time check like this one, Sight Machine’s software can also aggregate results for higher-level analysis. Engineers can, for instance, call up photos of every yellow car with a bent antenna.
Photo: courtesy Sight Machine.

Industrial firms tend to be conservative in adopting new systems, for a reason: the costs of a plant outage are huge (consider that a large auto assembly plant might produce more than 60 vehicles per hour — an outage of just one minute is equivalent to one car’s worth of lost production). They also tend to have enormous amounts of capital tied up in big, integrated production systems, making changes costly.

Sight Machine’s founders have approached both of those obstacles carefully. The company’s developers work in an industrial park in Ann Arbor, Mich., where they built a mockup of an auto-plant inspection station to test their software under factory conditions. Several of them have worked in heavy manufacturing, including automotive and defense, and the company has its roots at the decidedly machine-oriented Maker Works, a maker space across the street that offers Michigan’s industrial prototypers access to plasma cutters and CNC mills.

Early prototypes got some upgrades to meet the expectations of plant managers used to heavy-duty equipment. Sight Machine’s system uses costly CCD cameras instead of cheaper consumer-grade cameras. Design director Kyle Lawson says, to make the company’s first camera mount he “took a Logitech webcam stand, broke it down, and filled it with pennies to make it feel industrial.” (Now he fabricates heavy-duty camera mounts himself at Maker Works.)

As for the problem of weaving a new assembly line component into an old plant, Sight Machine’s software is free-standing and can be provided as a service or licensed to run locally — minimal integration with plant controls needed. That’s an important consideration for a cautious assembly-line manager who’s experimenting with a startup’s software.

Software and industry are inching closer; the industrial Internet will make it easier for innovators to turn physical-world problems into software problems, and then solve them using rich open-source tools and pervasive networks. Along the way, I think we’ll see lots of stories like Sight Machine’s.


This is a post in our industrial Internet series, an ongoing exploration of big machines and big data. The series is produced as part of a collaboration between O’Reilly and GE.

February 07 2013

Four short links: 7 February 2013

  1. Tridium Niagara (Wired) — A critical vulnerability discovered in an industrial control system used widely by the military, hospitals and others would allow attackers to remotely control electronic door locks, lighting systems, elevators, electricity and boiler systems, video surveillance cameras, alarms and other critical building facilities, say two security researchers. cf the SANS SCADA conference.
  2. Santa Fe Institute Course: Introduction to Complexity — 11 week course on understanding complex systems: dynamics, chaos, fractals, information theory, self-organization, agent-based modeling, and networks. (via BoingBoing)
  3. Terms of Service Changes — a site that tracks changes to terms of service. (via Andy Baio)
  4. 3D Printing a Replacement Hand for a 5 Year Old Boy (Ars Technica) — the designs are on Thingiverse. For more, see their blog.

January 31 2013

Hacking robotic arms, predicting flight arrival times, manufacturing in America, tracking Disney customers (industrial Internet links)

Flight Quest (GE, powered by Kaggle) — Last November GE, Alaska Airlines, and Kaggle announced the Flight Quest competition, which invites data scientists to build models that can accurately predict when a commercial airline flight touches down and reaches its gate. Since the leaderboard for the competition was activated on December 18, 2012, entrants have already beaten the benchmark prediction accuracy by more than 40%, and there are still two weeks before final submissions are due.

Robot Army (NYC Resistor) — A pair of robotic arms, stripped from their previous application with wire cutters, makes its way across the Manhattan Bridge on a bicycle and into the capable hands of NYC Resistor, a hardware-hacker collective in Brooklyn. There, Trammell Hudson installed new microcontrollers and brought them back into working condition.

The Next Wave of Manufacturing (MIT Technology Review) — This month’s TR special feature is on manufacturing, with special mention of the industrial Internet and its application in factories, as well as a worthwhile interview with the head of the Reshoring Initiative.

At Disney Parks, a Bracelet Meant to Build Loyalty (and Sales) (The New York Times) — A little outside the immediate industrial Internet area, but relevant nevertheless to the practice of measuring every component of an enormous system to look for things that can be improved. In this case, those components are Disney theme park visitors, who will soon use RFID wristbands to pay for concessions, open hotel doors, and get into short lines for amusement rides. Disney will use the resulting data to model consumer behavior in its parks.


This is a post in our industrial Internet series, an ongoing exploration of big machines and big data. The series is produced as part of a collaboration between O’Reilly and GE.

January 23 2013

Four short links: 23 January 2013

  1. These Glasses Thwart Facial Recognition Software (Slate) — good idea, but don’t forget to put a stone in your shoe to thwart gait recognition too.
  2. opsec for Hackers (Slideshare) — how boring and unexciting most of not getting caught is.
  3. DHS Warns Password Cracker Targeting Industrial Networks (Nextgov) — Security consultants recently concluded that there are about 7,200 Internet-facing critical infrastructure devices, many of which use default passwords. Wake me when you stop boggling. Welcome to the Internet of Insecure Things (it’s basically the Internet we already have, but Borat can pwn your hydro dam and your fridge is telling Chinese milspec hackers when you midnight snack).
  4. The Evolution of Steve Mann’s Apparatus (Beta Knowledge) — wearable computing went from “makes you look like a robot who will never get laid” to “looks like sunglasses and promiscuity is an option”.

January 18 2013

Seeing peril — and safety — in a world of connected machines

I’ve spent the last two days at Digital Bond’s excellent S4 conference, listening to descriptions of dramatic industrial exploits and proposals for stopping them. A couple of years ago Stuxnet captured the imagination of people who foresee a world of interconnected infrastructure brought down by cybercriminals and hostile governments. S4 — which stands for SCADA Security Scientific Symposium — is where researchers convene to talk about exactly that sort of threat, in which malicious code makes its way into low-level industrial controls.

It is modern industry’s connectedness that presents the challenge: not only are industrial firms highly interconnected — allowing a worm to enter an engineer’s personal computer as an e-mail attachment and eventually find its way into a factory’s analytical layer, then into its industrial controls, bouncing around through print servers and USB drives — but they’re increasingly connected to the Internet as well.

Vendors counter that the perfect alignments of open doors that security researchers expose are extremely rare and require unusual skill and inside knowledge to exploit. And the most catastrophic visions — in which malicious code shuts down and severely damages a large city’s water system or an entire electrical grid — assume in many cases a level of interconnection that’s still theoretical.

In any case, industrial security appears to be advancing quickly. Security firms are able to make particularly effective use of anomaly detection and other machine-learning-based approaches to uncover malicious efforts, since industrial processes tend to be highly regular and information flows tightly prescribed. These approaches will continue to improve as the networks that feed information back to analytical layers become more sophisticated and computing power makes its way deeper into industrial systems.

The efforts of industrial security researchers seem to be paying off. In his keynote talk, Digital Bond founder Dale Peterson noted that the exposure of new vulnerabilities has slowed recently and wondered whether security might be subject to something of apredator-prey cycle, in which weak defenses in industrial controls attract hackers, which draws the attention of security researchers, who in turn drive away the hackers by closing vulnerabilities.

If that’s the case, then we’re looking at a gradual victory for the industrial Internet — as long as we don’t reach the last phase of the predator-prey cycle, in which security researchers, feeling they’ve vanquished their enemies, move on to a different challenge.


This is a post in our industrial Internet series, an ongoing exploration of big machines and big data. The series is produced as part of a collaboration between O’Reilly and GE.

December 27 2012

Four short links: 27 December 2012

  1. Improving the Security Posture of Industrial Control Systems (NSA) — common-sense that owners of ICS should already be doing, but which (because it comes from the NSA) hopefully they’ll listen to. See also Wired article on NSA targeting domestic SCADA systems.
  2. Geographic Pricing Online (Wall Street) — Staples, Discover Financial Services, Rosetta Stone, and Home Depot offer discounts if you’re close to a competitor, higher prices otherwise. [U]sing geography as a pricing tool can also reinforce patterns that e-commerce had promised to erase: prices that are higher in areas with less competition, including rural or poor areas. It diminishes the Internet’s role as an equalizer.
  3. Hacker Scouting (NPR) — teaching kids to be safe and competent in the world of technology, just as traditional scouting teaches them to be safe and competent in the world of nature.
  4. pressureNET Data Visualization — open source barometric data-gathering software which runs on Android devices. Source is on GitHub.

December 17 2012

Four short links: 17 December 2012

  1. TraceKit (GitHub) — stack traces for Javascript exceptions, in all major browsers.
  2. SCADA Manufacturer Starts Own Anti-Malware Project — perimeter protection only, so it doesn’t sound to my inexpert ears like the whole solution to SCADA vulnerability, but it at least shows that one SCADA manufacturer cares.
  3. Platform Competition in Two-Sided Markets (PDF) — The economic effects of multihoming are fascinating. (via Tim O’Reilly)
  4. Silicon Valley Straps on Pads (WSJ) — SF 49ers hiring tech people to do what Harper Reed did for Obama. Interestingly, the tech people are the ones who must see what can be done, though they’re slowly working on the rest of the org: [W]ith scouts “what we found is we have to push them to dream even more, because usually it’s like, ‘OK, we can do that for you,’ and it’s done overnight.” Now, he says, scouts are far less shy about seemingly impossible technological requests.
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