Most laptops will last about what the manufacturer advertises, while using it in the manner disclosed by the manufacturer. For example Apple quotes their battery time while watching video on medium brightness. If you do that, you'll be close to the times Apple says you will be able to reach. If you're running Java applications or gaming on high quality settings, don't complain that your battery life is less than quoted by the manufacturer!

After a move like that, is it any wonder that Microsoft gets so many contracts with the government of Canada? It's another sad day for open source in Canada when it is so obvious that the GoC is in Microsoft's pocket.

That's funny. I had not read the linked story and up to this point I had assumed that it was Microsoft that was paying $400M. What kind of a deal is that? Microsoft is getting a lot of publicity, telecast rights and video game content with a lot more money that a few thousand tablets should cost. Not to mention that their "market share" will seem to go up with this deal, which I'm sure they're desperate for at the moment.

Who doesn't revere engineering?

Washing with water would be open "source" (french word for a water spring). Many cultures do it this way already. Once you get passed the cringe phase because you're not used to it, you realize that it makes much more sense to wash off the stuff than smear it across your ass with a pieace of paper...

I can imagine the new porn that will come out... literally!

Old news... Cobwebs at my place have been repelling all kinds of females for a long time, not just my aunts.

The popularity of these GPUs baffles me. They are hard to program and very limited in what they can do, not to mention the horrible transfers to main memory, yet because there is no other foreseeable technology coming in the next 5 years or so they are becoming the standard for massively parallel programming on a budget. Any university and its dog has GPU projects, with wild performance claims, usually measuring a code they spend years optimizing for the GPU against the original code running un-optimized on one CPU thread. Yet in the real world there are very few applications of the GPU. The memory transfer bottleneck amplifies Amdahl's law. I work in an mission-critical supercomputing center and it will be years before we adopt the GPUs because of the manpower required to convert existing code, the uncertainty of the future of the technology, the quasi vendor lock-in situation that we have now with NVidia, and the fact that vendor support is not yet where it should be. Yet I am watching this technology being slowly adopted by everyone for lack of a better alternative. Thinking about it, it is pretty sad times that we live in term of supercomuting. Don't believe me? Ask the vendors what exciting new technology they have coming. They don't have any.