Water Powered car unveiled in Japan

Genepax, a Japanese company, has unveiled a car that can run on water. It apparently extracts Hydrogen from water and uses it to create energy to fuel the car. The prototype was driven around in the city of Osaka in Japan. Engadget has more details:

The key to that system, it seems, is its membrane electrode assembly (or MEA), which contains a material that's capable of breaking down water into hydrogen and oxygen through a chemical reaction. Not surprisingly, the company isn't getting much more specific than that, with it only saying that it's adopted a "well-known process to produce hydrogen from water to the MEA." Currently, that system costs on the order of ¥2,000,000 (or about $18,700 -- not including the car), but company says that if it can get it into mass production that could be cut to ¥500,000 or less (or just under $5,000)

There is a video from Reuters that I have tried to embed below, but I am not sure if it will show up on the final blog (here's the link to the Reuter's page that houses the video):



Update: Looks like there's more to it than meets the eye. See this discussion on Slashdot.

EasyEclipse - Making life easy for Developers

Link: http://www.easyeclipse.org

I went back to Java after quite sometime, and had a tough time installing some plugins (Visual Editor in particular, it is not supported as yet on the current Europa release and only on the previous Callisto) this site is really handy in case you want to get a setup with everything you need already installed. They have bundled everything together and everything just works!

They have also divvied it up into broad areas such as 'Desktop', 'Web', 'LAMP' and so on -- targeted towards programmers in that category. Apart from the fact that they have these distros, it was also a great place to find out what were the most useful plugins for development on the eclipse platform. I didn't even know they have very useful plugins even for things like database management and SVN.

A life saver for people not experts on eclipse, I must say.

The World is Round Again!

Came across an interesting article while browsing the net for Tata-JLo (!) deal yesterday. Pankaj Ghemawat, a chaired professor at Harvard Business School disagrees with Tom Friedman that globalization has reached its peak but instead believes that a lot of trade, immigration as well as "bits" travel only within national boundaries, and there is still a long way to go before we can knock down the walls we have built over centuries.

The findings fly in the face of Friedman's famous work. Take flows of people. Much as we would like to believe that this figure would be astronomically high, it is not. Says Ghemawat, "If you look at the stock of first-generation immigrants divided by the total population of the world, it is barely 2.9%."

In fact, he claims that in some metrics, we are just about reaching the 19th century level of globalization:

"On the people's side, the current ratio of immigrants to world population is slightly lower than in 1910. On the FDI side, we have probably reached new heights, but it wasn't until the 1990s that we got back to the FDI-to-GDP ratio that the world was seeing in 1901," says Ghemawat.

I can imagine this happening because of the FDI from Britain, France, and Spain into their colonies (which had been quite impoverished by then by monies being sent back as profits). A lot of flow today is in the reverse, the Tata-JLo deal being a case in point. It would be interesting to see detailed numbers, or perhaps they are present in the book.

In fact, at some point, I thought the claim that there is actually increasing localization of products which goes against globalization was being made. For instance, Coke and Wal-Mart and McDonalds have to take local tastes into account. I wonder if this would count as a case of more globalization or less globalization. I guess parts of it can be argued either way.

Link to the original article.

Should prizes make a come back as against grants?

A very interesting article by Tim Harford about how prizes were a motivation for a big chunk of research which got productised earlier, and how it could be making a comeback. The advantage is quicker solutions, involvement of a more diverse community with more diverse ideas, cutting bureaucracy, fame and fortune for the inventors, and of course, problems getting solved. He cites how a competition was used to build an accurate clock used to predict the longitude of ships, and how today, from the Gates Foundation (for pneumococcal disesases) to Netflix (for machine learning algorithms) is using a cash prize as a motivation to involve people to solve important problems. It could also be used by governments to replace patents for solving large problems. He says:

Champions of prizes see them as a component of a wider system to promote innovation, rather than as an outright replacement either for grants or patents. Instead, the hope is that prizes will help to compensate for the specific weaknesses of those alternatives.

The downside of a patent is fundamental to its design: in order to reward an innovator, the patent confers a monopoly. Economists view this as, at best, a necessary evil since monopolies distort prices. In the hope of raising profits from some customers, they will price others out of a market. The most obvious victims are consumers in poor countries.

In an ideal world, prizes could replace patents. Instead of offering a patent for an innovation, the government could offer a prize. The inventor would pocket the prize but would not be allowed to exploit any monopoly power, so the innovation would be freely available to use in products for poor consumers – cheap drugs for Africa, for instance – and, importantly, in further innovations. But to explain that idea is to see its limitations. How could the government know enough about the costs and benefits – and even the very possibility – of an innovation to put a price tag on it and write the terms of reference for a prize competition? For this reason it is hard to see prizes replacing patents in most cases. But it is not impossible.

The modern heir to 18th-century prizes for canning, water turbines and finding longitude at sea is the advanced market commitment for vaccines for the poor: the goal is clear, the costs and benefits can be guessed at, and the quasi-prize nudges the patent system to one side with a prize contract that respects the patent but, in exchange for a large subsidy, radically constricts the holder’s right to exploit it.

Prizes may be an effective way to build technologies that solve a specific problem, but I doubt if they can help in unknown sojourns into the world of science. Most of our applied technologies are build upon these basic scientific fundamentals and I don't know if a gold-rush will lead to the newest laws of physics, or fundamental rules in mathematical logic. Issues of ownership of Intellectual property are also a little ambiguous, and have to be specified clearly up front. In many cases, gauging the ramifications of a new mathematical theory, or basic physical laws might be extremely difficult (which is the reason Nobel prizes are awarded after the work has been established over a long term).

All said and done, I am sure prizes (not just the cash, the fame and respect as well) make for great motivation and we might see a lot of it.

Bitwise 2008 - Can it get any better?

I still remember Bitwise 2006 very fondly -- all the last minute action, with the teams participating, running around to arrange problems, solutions, making sure everything runs properly. And it's been 2 years since then. It's very proud to see Bitwise 2008 progressing so well, with teams from almost 43 countries and clicks from 75! It can't get any bigger than this. It all started in 2001, and has come so far since then!

If you fancy yourself as a ace programmer, and you think you can unravel the double helix in your sleep, if you live and dream algorithms, crunch numbers when nobody's looking at you, you gotta participate in Bitwise, the real test of your abilities. It's the largest algorithm intensive online programming contest in India organized completely by students from one of the best engineering institutions in the country. You compete with the best brains in the area worldwide, and there are a sweet USD 2500 on offer as prizes.

Do you have it in you? Visit the Bitwise 2008 site and register NOW.

Swarm Intelligence

In a previous post on the Honey-bee algorithm for allocating servers, which I found quite fascinating, I had pointed out I had referred to a paper on Swarm Intelligence by Eric Bonabeau and Christopher Meyer published by Harvard Business Review, and finally I got time to go back and read it and I found it quite fascinating! The paper describes case studies where people have used algorithms inspired by nature (ants, bees) which use a decentralized model of computation and optimization.

The paper points out that the main advantages of using algorithms like these are flexibility, robustness and self-organization. The algorithms work in a completely decentralized manner, and work on the principle that the wisdom of all the ants (or the small agents) can be harnessed in such a manner that the whole is far greater than the sum of its parts. Also, the algorithms are invariably robust to failure and adaptive since they don't make use of a central decision making bodies and there is a lot of experimentation with new sources of food (or results in the case of algorithms).

The paper also points out that there are several cases where these concepts have been used successfully (both in business and academia):

• Optimally routing telephones calls and Internet data packets seems to be a tough problem because if we use a centralized algorithm, it will neither be robust nor adaptive. Algorithms based on swarm intelligence come to the rescue since they are not based on a central decision making body, but rather work on the principle that the scouts recruit other agents to follow new promising paths.
• Fleet management and cargo management also suffer from similar problems. The paper points out that Southwest Airlines found out that in some cases, letting cargo go to wrong destinations and recovering is faster and more robust than always making sure that all cargo is handled correctly.
• Small simple rules that lets people take decisions for themselves usually works best. This has since been shown to work very well for companies such as Google as well.

There are more case studies in the paper, but what's fascinating is that these techniques become even more popular now-a-days because companies have realized that it is easier to tolerate failure than to eradicate it -- more so in the context of the Internet where there is a race to build systems that are self-correcting (such as Map-Reduce, Hadoop and Dryad). Also the new realities of the emerging architectures (multi-core, highly parallel, massive clusters grids) is going to mean that we have more parallel horsepower to run our applications and such self-organizing algorithms are going to become even more popular in the computing community.

However, one concern would be programming models for such computing bedrocks. We still don't understand how to manage parallel computation very well to ensure that interpreting such algorithms in code is going to remain difficult for the average programmer for quite sometime.

Parallel Programming + Type inference + Scientific notation: A Winner?

I came across this article in Linux Today which describes Project Fortress, an open-source effort from Sun to provide a language based on Fortran to easily write parallel programs. The project seems to be built on top of Java. Some salient features seem to be:

1. Implicit parallelism: If you want to execute a loop sequentially you have to explicitly write that. The big claim is of course, using this efficiently on multi-core machines.
   
2. Support for unicode: As a result, the scientific research community can make use of greek alphabets in their code, and even use things like superscripts, subscripts, and hats and bars! This means that your code is going to look a lot more like your algorithm.
3. Automated Type inference: The system has extensive type inference (the kind that functional languages and C# 3.0 have) and that means that your code is far more readable.
4. Extensive library support: In fact, even some parts of the main system are implemented as libraries. They expose the parsed AST to the programmer, and give him extensive control.

These sound quite interesting, and it seems that the scientific computing language of the future is going to look a lot like Fortress, if they are successful with this effort.