Tuesday, December 21, 2010
Thursday, November 25, 2010
Giving Thanks
Monday, November 1, 2010
Empty Space Does Not Exist
I am reading Steven Hawking’s new book (for the semi-ignorant masses like myself) The Grand Design. I am enjoying the book thoroughly. It is the first time I've seen Richard Feynman get the attention he deserves. About halfway through the book Hawking talks about a consequence of Heisenberg’s uncertainty principle, that there is no such thing as empty space. Empty space cannot be empty because then the both the value of the field, and the rate of change would be exactly zero and that cannot obtain. Although it seems to me that the problem Heisenberg uncertainty principle depends upon is having something to observe. So this argument seems a bit circular. But, there's a much easier way to show that space is not empty.
A little thought experiment would suggest that within the knowable universe, if Einstein was right, it’s pretty easy to decide space is not empty, in fact it is quite full, maybe completely full (whatever that means). Einstein suggested that energy and mass are forms of the same thing. The conservation of energy and the conservation of mass were both wrong, but combined are true.
Imagine you are in orbit around the earth. You look away from the sun. What do you see? Stars! You see billions of stars. In fact, if your eyes were more sensitive, perhaps more sensitive than the Hubble Space Telescope, perhaps you could see a couple hundred billion galaxies, each made up of 200 billion to 400 billion stars. That’s a lot of photons hitting your little eye all the time. Now imagine you move a few inches over to your right. What do you see? The same thing. If fact, wherever you move in space you will still be impacted by billions and billions of photons. Thus, space is not empty. Now, all I need is a photon sail and I'm off.
Tuesday, October 19, 2010
What Really Drives Financial Success?
Friday, October 8, 2010
“We already tried that and it didn’t work.”

Two scientists set out to look into the machinery for making proteins, the ribosomes, and to see if they are the same in different living creatures. They designed an experiment to take ribosomes from bacteria, insert messenger RNA from peas, and see if they would grow pea proteins or bacteria proteins. Had the experiment worked, they would have been the first to demonstrate the uniformity of life.
But it didn’t work.
You can easily imagine someone coming along later to attempt to do the same thing getting the response “We already tried that and it didn’t work!” Chris Galvin, the former CEO of Motorola, gave a talk this week at the Business Innovation Conference in which he described how he and his father would deal with this kind of question. If someone came to him with an idea that had already been tried, the Motorola CEO wouldn’t say “we already tried that.” Instead, he would encourage the innovator to pursue the idea and give some guidance where to look first. If the reason the idea didn’t work the first time was valid, the innovator would see the problem fairly soon, report the issue back to Galvin, and then go off to pursue some other idea. If you just shoot someone down with “we already tried that,” then you make it very difficult for that person to move off that idea and onto a new one. You also diminish their level of engagement.
In the case of the ribosomes RNA experiment, eventually someone did come along and show the uniformity of life. The reason the original experiment failed was due to the amateurish contribution of the lab assistant. The bacteria ribosomes he brought to the experiment were some he’d developed in a previous experiment and had stored for some time in a lab refrigerator. While there, they’d become contaminated which caused the experiment to fail. Who was this lab assistant. It was Richard Feynman, the renown physicist and Nobel Laureate.
Just because something has been tried before, doesn’t mean there’s no value in trying again. And just because it was tried by someone who’s incredibly smart, doesn’t mean an error didn’t occur.
