Research Parks for the Knowledge Economy. By Pete Engardio Since it opened 50 years ago, North Carolina's Research Triangle Park has been the epitome of science parks: a neatly landscaped campus of low-rise building buildings in exurbia, where scientists at aspiring technology spin-offs from nearby universities toil all day in cramped, low-rent "incubators" and then disperse each evening to fight the Interstate traffic on their way home. The rest of the world is moving far beyond that model. As more nations try to gain an edge in the next generation of knowledge industries, stunning new high-tech meccas are going up from Asia to Europe to Latin America, a building spree that hardly has been slowed by the recession. They are nothing like the far-flung developments of old like Research Triangle Park, which was carved out of 11 square miles of pine forest near Raleigh-Durham. "New Century Cities" New science parks can be tightly focused.
Building Communities New science parks, meantime, have been sprouting across the U.S. Automated innovation. Towards Automated Innovation - Innovating To Win. There are many pleasures that innovation practitioners get from what they do. The satisfaction of creating and delivering a high value solution where others had failed to see the opportunity, the knowledge that what you do is changing the lives of those around you, the thrill of shaping the future are among a few of the things I have heard other innovators talk about. However on a more mundane level, it has always seemed very satisfying when another talented innovation practitioner acknowledges your efforts. So, I was delighted to see Drew Boyd’s latest blog post on Innovation in Practice: “Automated Innovation”. Drew is a very accomplished practitioner. As the Director of Marketing Mastery for Johnson & Johnson’s Ethicon Endo-Surgery division, Drew heads up J&J’s marketing university that among other things is responsible for new product innovation.
In his Automated Innovation post, Drew postulates on the role of software technology in the service of innovation. Innovation in Practice: Automated Innovation. "To avoid the fate of alchemists, it is time we asked where we stand. Now, before we invest more time and money on the information-processing level, we should ask whether the protocols of human subjects and the programs so far produced suggest that computer language is appropriate for analyzing human behavior: Is an exhaustive analysis of human reason into rule-governed operations on discrete, determinate, context-free elements possible?
Is an approximation to this goal of artificial reason even probable? The answer to both these questions appears to be, No. " Hubert L. Dreyfus"What Computers Can't Do: The Limits of Artificial Intelligence" This chilling conclusion about the fate of artificial intelligence seems to put an end to the idea that we can automate innovation. Since this book was first published in 1972, not much has changed, and the field of artificial intelligence seems to be in decline. For a machine to innovate, it would need to: Step Four is where machines struggle.
The Innovation Software Company - Invention Machine. Why will open science become the main kind of science. Ubuntu ISO Testing team.