cool article on retrothing about a GE engineer who used some old design sketches to recreate an old audio device that uses 35mm film as the recording material.
However, a small collection of Photophone film canisters survived in the basement of the Schenectady Museum. The only clue to their contents were handwritten notes on the cans identifying them as radio programs from the 1920s. They remained shelved and forgotten until rediscovered by the museum’s curator, Chris Hunter. He was intrigued, but there was no way to replay the material using modern equipment.
Luckily, Hunter was introduced to Russ DeMuth, a GE engineer, who rose to the challenge and built a modern version of the pallophotophone based upon Charles Hoxie’s original design sketches.
So remember back when we wrote about superhydrophobicity? Well we just ran across another interesting use of the coating that repels water: Teapots. Apparently some scientists have figured out how to stop them from dripping all over the place. Here’s the explanation from the physics arXiv blog:
Now Cyril Duez at the University of Lyon in France and a few amis, have identified the single factor at the heart of the problem and shown how to tackle it. They say that the culprit is a “hydro-capillary” effect that keeps the liquid in contact with the material as it leaves the lip. The previously identified factors all determine the strength of this hydro-cappillary effect.
So how to overcome it? There are two ways say Duez and co. The first is to make the lip as thin as possible. That’s why teapots with spouts made from thin metal are less likely to dribble.
The second is to coat the lip with the latest generation of superhydrophobic materials which strongly repel water. Duez and co show how this stops dribbling at a stroke. “Superhydrophobic surfaces fully avoid dripping, and thus beat the “teapot effect”,” they say.
Gotta love science solving everyday problems. [Link via Sciblogs]
There’s an interesting article on FastCompany.com about the different ways to track the spread of the H1N1 flu. In particular the article focuses on Google Flu Trends, which looks at the number of searches for flu-related keywords to gauge how different areas have been hit, and GE’s electronic medical records system, which have the ability to anonymously aggregate data.
Daily reports upload from GE Healthcare’s Medical Quality Improvement Consortium (MQIC), a repository designed with HIPAA-compliance parameters, of anonymous clinical data and best practices. Participating physicians automatically contribute de-identified data to MQIC each day through normal use of GE’s Centricity EMR when they document information collected during patient visits to physician offices and clinics. Operated by GE Clinical Data Services, which also provides research and analytical services, the MQIC database is growing at a rate of nearly 30 percent each year. In peer-reviewed studies the database has been validated as representative of demographic and co-morbidity averages in the U.S. population1.
Anyway, I mention this because I thought it might be cool if we could share some of this data with the public? Obviously it would need to be scrubbed, but Google’s Flu Trends offers an interesting peek into how aggregate data can be used to help give insights back to the consumers who are eventually responsible for it. It would also be quite interesting to compare the data from the two services.
Take all the power stations in the United States. Together, they produce almost 5000 gigawatts of electricity – enough to boil several billion kettles simultaneously.
Now imagine building another five power stations for every one that already exists in the United States. That is about the amount of electricity generation that the world is on track to add over the next 20 years. And three-quarters of the new stations will use fossil fuels.
Interesting. This blog post about the “Era of Open Energy Information” mentions the use of APIs, allowing developers to build their own tools that pulls in energy data. Makes perfect sense, but hadn’t really thought of it in those terms before. Still not quite sure I understand how the data is extracted from the smart grid receiver, but I’m assuming someone has figured that problem out. As we’ve seen proven on the web over and over again, once you open up the data nerds will find something fun to do with it. Of course there are some dangers of privacy, etc., but that’s the case with any new technology …
It [an NYU study] found that about half the customers noticed the calorie counts, which were prominently posted on menu boards. About 28 percent of those who noticed them said the information had influenced their ordering, and 9 out of 10 of those said they had made healthier choices as a result.
What’s interesting is that just a few weeks ago someone mentioned a similar (maybe the same) study to me and said that what was also found was that if you anchored the calories with the suggested daily intake for adults the numbers went way down. The problem is a lack of anchoring.
The “health-wealth gradient” refers to the fact that, as a general rule, the richer you are, the healthier you are. This applies across different countries and across the full range of social classes within the same country. (It’s not just that the very poorest people are sick.) No one knows exactly what causes the health-wealth gradient or why it’s so resilient. It may be that rich people have access to better health care. Or, as we’ve seen, it could be that being sick costs you money. Then there’s the possibility that poor people have a greater incentive to behave in unhealthy ways: Since they don’t have as much money to spend on happiness, they “spend” their health instead. (The pleasures of smoking and eating, for example, are easy on the wallet and hard on the body.)
Specifically it’s that last sentence: I had never thought of health as something you spend, but of course it is. I, for one, know that I go to the gym at least in part so that I can eat whatever I want. I am essentially purchasing health credits at the gym which I then spend on less healthy activities that I enjoy. Wow.
From the perspective of innovation, I learned quite a bit. I am still trying to sort through it in my head, but there are a few things that really stood out. One thing is that a lot of the folks I met are involved in something based off the internet, and their medium is information. This is pretty fascinating environment. Because the “barrier to entry” is so low, it’s relatively easy to very quickly try many different things on the web – and just see which one sticks. And that appears to be one of the keys to coming up with ideas… many cheap and quick iterations to maximize your ability to learn. I am trying to figure out how to apply this to my world, where it simply isn’t practical to build 10 different designs for a jet engine (at billions of dollars and many years of development) – and then take the best one – we’d go out of business! But it is something we can do on a smaller scale in the lab.
I say turn your health into a social game like Foursquare. Check in when you take your meds, go to the gym, walk to work, and eat like Michael Pollan. Tie this to your insurance premiums. In fact, I say turn life into one big game with various levels. Make the mundane fun. We’ve got the beginnings of the technology to do it. And I’m glad there are people like Dennis and Naveen who are there to show us how it’s done.
One of the more interesting parts of the conversation we had with David Lee was around thinking about changing the economics of going to the doctor. As David explained, a regular doctor visit has a bad risk/reward situation: There is a low liklihood anything is wrong but good chance that if something is wrong that it’s serious. On top of this, people have a tendency to overestimate small risks and devalue the future, all leading to a situation where it’s hard to get people into a regular routine of visits.
So how can this be fixed? Well, it’s counterintuitive, but first off you’d need to accurately communicate to people the low risk of the situation by letting them know just how unlikely it is that anything is wrong with them. Then, in the case that something actually was, you’d have to be prepared with a good explanation of how to approach the issue and the liklihood of success (again, people will tend to think that the risk is higher than it really is).
Hi! This is a blog about a project we are doing for GE. We are from The Barbarian Group, an online marketing company, and GE hired us to help them with their internet behavior, so this is our marketing journal where we will show you what we find and talk about what we might do next.