- Manufacturers and Consumers (Matt Webb) — manufacturers never spoke to consumers before. They spoke with distributors and retailers. But now products are connected to the Internet, manufacturers suddenly have a relationship with the consumer. And they literally don’t know what to do.
- Calendar Hacks (Etsy) — inspiration for your New Year’s resolution to waste less time.
- Making an Ethical Decision — there actually is an [web] app for that.
- Masks That Look Human to Computers — an artist creates masks that look like faces to face-recognition algorithms, but not necessarily to us. cf Deep Neural Networks are Easily Fooled.
"computer vision" entries
AI Lecture, Programming Provocation, Packet Laws, and Infrared Photography
- Analogy as the Core of Cognition (YouTube) — a Douglas Hofstadter lecture at Stanford.
- Why Isn’t Programming Futuristic? (Ian Bicking) — delicious provocations for the future of programming languages.
- Border Check — visualisation of where your packet go, and the laws they pass through to get there.
- Pi Noir — infrared Raspberry Pi camera board. (via DIY Drones)
Visual Arduino Coding, Hardware Iteration, Segmenting Images, and Client-Side Adjustable Data View
- Visually Programming Arduino — good for little minds.
- Rapid Hardware Iteration at Scale (Forbes) — It’s part of the unique way that Xiaomi operates, closely analyzing the user feedback it gets on its smartphones and following the suggestions it likes for the next batch of 100,000 phones. It releases them every Tuesday at noon Beijing time.
- Machine Learning of Hierarchical Clustering to Segment 2D and 3D Images (PLoS One) — We propose an active learning approach for performing hierarchical agglomerative segmentation from superpixels. Our method combines multiple features at all scales of the agglomerative process, works for data with an arbitrary number of dimensions, and scales to very large datasets.
- Kratu — an Open Source client-side analysis framework to create simple yet powerful renditions of data. It allows you to dynamically adjust your view of the data to highlight issues, opportunities and correlations in the data.
Filmic Photogrammetry, Car APIs, Takedowns, and OpenCV for Processing
- Sifted — 7 minute animation set in a point cloud world, using photogrammetry in film-making. My brilliant cousin Ben wrote the software behind it. See this newspaper article and tv report for more.
- Vehicle Tech Out of Sync with Drivers’ Devices — Ford Motor Co. has its own system. Apple Inc. is working with one set of automakers to design an interface that works better with its iPhone line. Some of the same car companies and others have joined the Car Connectivity Consortium, which is working with the major Android phone brands to develop a different interface. FFS. “… you are changing your phone every other year, and the top-of-mind apps are continuously changing.” That’s why Chevrolet, Mini and some other automakers are starting to offer screens that mirror apps from a smartphone.
- Incentives in Notice and Takedown (PDF) — findings summarised in Blocking and Removing Illegal Child Sexual Content: Analysis from a Technical and Legal Perspective: financial institutions seemed to be relatively successful at removing phishing websites while it took on average 150 times longer to remove child pornography.
- OpenCV for Processing (Github) — OpenCV for Processing is based on the official OpenCV Java bindings. Therefore, in addition to a suite of friendly functions for all the basics, you can also do anything that OpenCV can do. And a book from O’Reilly, and it’ll be CC-licensed. All is win. (via Greg Borenstein)
Backbone Stack, Automating Card Games, Ozzie on PRISM, and Stuff that Matters
- Our Backbone Stack (Pamela Fox) — fascinating glimpse into the tech used and why.
- Automating Card Games Using OpenCV and Python — My vision for an automated version of the game was simple. Players sit across a table on which the cards are laid out. My program would take a picture of the cards and recognize them. It would then generate valid expression that yielded 24, and then project the answer on to the table.
- Ray Ozzie on PRISM — posted on Hacker News (!). In particular, in this world where “SaaS” and “software eats everything” and “cloud computing” and “big data” are inevitable and already pervasive, it pains me to see how 3rd Party Doctrine may now already be being leveraged to effectively gut the intent of U.S. citizens’ Fourth Amendment rights. Don’t we need a common-sense refresh to the wording of our laws and potentially our constitution as it pertains to how we now rely upon 3rd parties? It makes zero sense in a “services age” where granting third parties limited rights to our private information is so basic and fundamental to how we think, work, conduct and enjoy life. (via Alex Dong)
- Larry Brilliant’s Commencement Speech (HufPo) — speaking to med grads, he’s full of purpose and vision and meaning for their lives. His story is amazing. I wish more CS grads were inspired to work on stuff that matters, and cautioned about adding their great minds to the legion trying to solve the problem of connecting you with brands you love.
A software startup builds itself to work with Michigan's manufacturers.
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. Read more…
Informed Citizenry, TCP Chaos Monkey, Photographic Forensics, Medical Trial Data
- Aaron’s Army — powerful words from Carl Malamud. Aaron was part of an army of citizens that believes democracy only works when the citizenry are informed, when we know about our rights—and our obligations. An army that believes we must make justice and knowledge available to all—not just the well born or those that have grabbed the reigns of power—so that we may govern ourselves more wisely.
- Vaurien the Chaos TCP Monkey — a project at Netflix to enhance the infrastructure tolerance. The Chaos Monkey will randomly shut down some servers or block some network connections, and the system is supposed to survive to these events. It’s a way to verify the high availability and tolerance of the system. (via Pete Warden)
- Foto Forensics — tool which uses image processing algorithms to help you identify doctoring in images. The creator’s deconstruction of Victoria’s Secret catalogue model photos is impressive. (via Nelson Minar)
- All Trials Registered — Ben Goldacre steps up his campaign to ensure trial data is reported and used accurately. I’m astonished that there are people who would withhold data, obfuscate results, or opt out of the system entirely, let alone that those people would vigorously assert that they are, in fact, professional scientists.
Who will pay damages when a driverless car gets into an accident?
Megan McArdle has taken on the question of how liability might work in the bold new world of driverless cars. Here’s her framing scenario:
Imagine a not-implausible situation: you are driving down a brisk road at 30 mph with a car heading towards you in the other lane at approximately the same speed. A large ball rolls out into the street, too close for you to brake. You, the human, knows that the ball is likely to be followed, in seconds, by a small child; you slam on the brakes (perhaps giving yourself whiplash) or swerve, at considerable risk of hitting the other car.
What should a self-driving car do? More to the point, if you hit the kid, or the other car, who gets sued?
The lawyer could go after you, with your piddling $250,000 liability policy and approximately 83 cents worth of equity in your home. Or he could go after the automaker, which has billions in cash, and the ultimate responsibility for whatever decision the car made. What do you think is going to happen?
The implication is that the problem of concentrated liability might make automakers reluctant to take the risk of introducing driverless cars.
I think McArdle is taking a bit too much of a leap here. Automakers are accustomed to having the deepest pockets within view of any accident scene. Liability questions raised by this new kind of intelligence will have to be worked out — maybe by forcing drivers to take on the liability for their cars’ performance via their insurance companies, and insurance companies in turn certifying types of technology that they’ll insure. By the time driverless cars become a reality they’ll probably be substantially safer than human drivers, so the insurance companies might be willing to accept the tradeoff and everyone will benefit. Read more…