I believe that there is a large difference between the magnitude of error in my natural bias for estimating exponential rates of growth and the naive applicatio

I believe that there is a large difference between the magnitude of error in my natural bias for estimating exponential rates of growth and the naive application of a mathematical model to the fields of biotechnology and cognitive science by someone untrained in either. Computing hardware and software may be developing rapidly due to the commercial sector, but my guess is that the developments in academia (algorithms, etc.) are hardly exponential. What about the fields where happenstance discoveries drive improvement? Innovation occurs readily in fields that have money--mobile computing is huge right now, isn't it? The question is whether this distribution of reward correlates with the reverse salients of technological advancement. In my original post I offered several predictions for the growth of biotechnology. I think I'm placing important and valid markers to be able to identify the trend. When I see them happen I'll be happy to conclude that we're on the path to exponential growth in our field. (Note: I follow this area well enough to see where the reverse salients lie and what discoveries may inform us to better techniques.) I'm tired of the Kurzweil meme because I feel that it gives people a comfort that we'll reach some kind of Utopia without much effort. It's wrong, and quite frankly damaging. If the people who believe in him so strongly really want to see his vision happen, perhaps they would lend their hands in developing automation tools for us biologists.