The Difference Between Direct Competition and Disruption — As the ships grow, their engines have become vastly more efficient and sophisticated, the fuel mix has changed, and complex IT infrastructure has been put in place to coordinate the movement of the containers and ships. But fundamentally, the underlying cost structure of the business has not changed from 1950, when the first container ships carried a mere 500 to 800 containers across the world. (via Salim Virani)
The Impact of Copyright Policy Changes on Venture Capital Investment in Cloud Computing Companies (PDF) — Our findings suggest that decisions around the scope of copyrights can have significant impacts on investment and innovation. We find that VC investment in cloud computing firms increased significantly in the U.S. relative to the EU after the Cablevision decision. Our results suggest that the Cablevision decision led to additional incremental investment in U.S. cloud computing firms that ranged from $728 million to approximately $1.3 billion over the two-and-a-half years after the decision. When paired with the findings of the enhanced effects of VC investment relative to corporate investment, this may be the equivalent of $2 to $5 billion in traditional R&D investment.
Max Headroom Oral History — “Anybody under the age of 25 just loved it. And anybody above that age was just completely confused.”
Auto Makers Say You Don’t Own Your Car (EFF) — Most of the automakers operating in the U.S. filed opposition comments through trade associations, along with a couple of other vehicle manufacturers. They warn that owners with the freedom to inspect and modify code will be capable of violating a wide range of laws and harming themselves and others. They say you shouldn’t be allowed to repair your own car because you might not do it right. They say you shouldn’t be allowed to modify the code in your car because you might defraud a used car purchaser by changing the mileage. They say no one should be allowed to even look at the code without the manufacturer’s permission because letting the public learn how cars work could help malicious hackers, “third-party software developers” (the horror!), and competitors.
Remotely Bricking Cars (BoingBoing) — story from 2010 where an intruder illegally accessed Texas Auto Center’s Web-based remote vehicle immobilization system and one by one began turning off their customers’ cars throughout the city.
Machine Learning Classification over Encrypted Data (PDF) — It is worth mentioning that our work on privacy-preserving classification is complementary to work on differential privacy in the machine learning community. Our work aims to hide each user’s input data to the classification phase, whereas differential privacy seeks to construct classifiers/models from sensitive user training data that leak a bounded amount of information about each individual in the training data set. See also The Morning Paper’s unpacking of it.
Privacy of Phone Audio (Reddit) — unconfirmed report from Redditor I started a new job today with Walk N’Talk Technologies. I get to listen to sound bites and rate how the text matches up with what is said in an audio clip and give feed back on what should be improved. At first, I though these sound bites were completely random. Then I began to notice a pattern. Soon, I realized that I was hearing peoples commands given to their mobile devices. Guys, I’m telling you, if you’ve said it to your phone, it’s been recorded…and there’s a damn good chance a 3rd party is going to hear it.
Solar Hits Parity in 10 States, 47 by 2016 (Bloomberg) — The reason solar-power generation will increasingly dominate: it’s a technology, not a fuel. As such, efficiency increases and prices fall as time goes on. The price of Earth’s limited fossil fuels tends to go the other direction.
Facebook’s Top Open Data Problems (Facebook Research) — even if you’re not interested in Facebook’s Very First World Problems, this is full of factoids like Facebook’s social graph store TAO, for example, provides access to tens of petabytes of data, but answers most queries by checking a single page in a single machine. (via Greg Linden)
Project Naptha — automatically applies state-of-the-art computer vision algorithms on every image you see while browsing the web. The result is a seamless and intuitive experience, where you can highlight as well as copy and paste and even edit and translate the text formerly trapped within an image. Chrome extension. (via Anil Dash)
Garbage Trucks and FedEx Vans (IEEE) — Foo alum, Ian Wright, found traction for his electric car biz by selling powertrains for garbage trucks and Fedex vans. Trucks have 20-30y lifetime, but powertrains are replaced several times; the trucks for fleets are custom; and “The average garbage truck in the U.S. spends $55,000 a year on fuel, and up to $30,000 a year on maintenance, mostly brake replacements.”
Microsoft’s Quantum Mechanics (MIT TR) — the race for the “topological qubit”, involving newly-discovered fundamental particles and large technology companies racing to be the first to make something that works.
Maciej Ceglowski on Our Internet — If you haven’t already read this because someone pushed it into your hands, read it now. If these vast databases are valuable enough, it doesn’t matter who they belong to. The government will always find a way to query them. Who pays for the servers is just an implementation detail.
Design Changes Possible With Robot Cars (Brad Templeton) — While a nice windshield may be good for visibility for forward-facing passengers, there is no need to have a large unobstructed view for safety. The windshield can be reinforced with bars, for example, allowing it to be much stronger in the case of impacts, notably impacts with animals. Other than for passenger comfort, the windshield barely has to be there at all. On behalf of everyone who has ever driven in Australia at dusk … I for one welcome our new robot chauffeurs. (via The Atlantic)
Inside Google’s Self-Driving Car (Atlantic Cities) — Urmson says the value of maps is one of the key insights that emerged from the DARPA challenges. They give the car a baseline expectation of its environment; they’re the difference between the car opening its eyes in a completely new place and having some prior idea what’s going on around it. This is a long and interesting piece on the experience and the creator’s concerns around the self-driving cars. Still looking for the comprehensive piece on the subject.
How One Woman Hid Her Pregnancy From Big Data (Mashable) — “I really couldn’t have done it without Tor, because Tor was really the only way to manage totally untraceable browsing. I know it’s gotten a bad reputation for Bitcoin trading and buying drugs online, but I used it for BabyCenter.com.”
Connected for a Purpose (Jim Stogdill) — At a recent conference, an executive at a major auto manufacturer described his company’s efforts to digitize their line-up like this: “We’re basically wrapping a two-ton car around an iPad. Eloquent critique of the Internet of Shallow Things.
Why Nate Silver Can’t Explain It All — Data extrapolation is a very impressive trick when performed with skill and grace, like ice sculpting or analytical philosophy, but it doesn’t come equipped with the humility we should demand from our writers. Would be a shame for Nate Silver to become Malcolm Gladwell: nice stories but they don’t really hold up.
Gender and VR (danah boyd) — Although there was variability across the board, biological men were significantly more likely to prioritize motion parallax. Biological women relied more heavily on shape-from-shading. In other words, men are more likely to use the cues that 3D virtual reality systems relied on. Great article, especially notable for there are more sex hormones on the retina than in anywhere else in the body except for the gonads.
Even The Innocent Should Worry About Sex Offender Apps (Quartz) — And when data becomes compressed by third parties, when it gets flattened out into one single data stream, your present and your past collide with potentially huge ramifications for your future. When it comes to personal data—of any kind—we not only need to consider what it will be used for but how that data will be represented, and what such representation might mean for us and others. Data policies are like justice systems: either you suffer a few innocent people being wrongly condemned (bad uses of open data0, or your system permits some wrongdoers to escape (mould grows in the dark).
On Managers (Mike Migurski) — Managers might be difficult, hostile, or useless, but because they are parts of an explicit power structure they can be evaluated explicitly.
Big Data: Humans Required (Sherri Hammons) — the heart of the problem with data: interpretation. Data by itself is of little value. It is only when it is interpreted and understood that it begins to become information. GovTech recently wrote an article outlining why search engines will not likely replace actual people in the near future. If it were merely a question of pointing technology at the problem, we could all go home and wait for the Answer to Everything. But, data doesn’t happen that way. Data is very much like a computer: it will do just as it’s told. No more, no less. A human is required to really understand what data makes sense and what doesn’t. (via Anne Zelenka)
Morgan Stanley on the Economic Benefits of Driverless Cars — The total savings of over $5.6 trillion annually are not envisioned until a couple of decades as Morgan Stanley see four phases of adoption of self-driving vehicles. Phase 1 is already underway, Phase 2 will be semi-autonomous, Phase 3 will be within 5 to 10 years, by which time we will see fully self-driving vehicles on the roads – but not widespread usage. The authors say Phase 4, which will have the biggest impact, is when 100% of all vehicles on the roads will be fully autonomous, they say this may take a couple of decades.
Worse (Marco Arment) — I’ve been sitting on this but can’t fault it. In the last few years, Google, Apple, Amazon, Facebook, and Twitter have all made huge attempts to move into major parts of each others’ businesses, usually at the detriment of their customers or users.