3 resultados para revolution in Quebec
em National Center for Biotechnology Information - NCBI
Resumo:
In the beginning of modern plant biology, plant biologists followed a simple model for their science. This model included important branches of plant biology known then. Of course, plants had to be identified and classified first. Thus, there was much work on taxonomy, genetics, and physiology. Ecology and evolution were approached implicitly, rather than explicitly, through paleobotany, taxonomy, morphology, and historical geography. However, the burgeoning explosion of knowledge and great advances in molecular biology, e.g., to the extent that genes for specific traits can be added (or deleted) at will, have created a revolution in the study of plants. Genomics in agriculture has made it possible to address many important issues in crop production by the identification and manipulation of genes in crop plants. The current model of plant study differs from the previous one in that it places greater emphasis on developmental controls and on evolution by differential fitness. In a rapidly changing environment, the current model also explicitly considers the phenotypic variation among individuals on which selection operates. These are calls for the unity of science. In fact, the proponents of “Complexity Theory” think there are common algorithms describing all levels of organization, from atoms all the way to the structure of the universe, and that when these are discovered, the issue of scaling will be greatly simplified! Plant biology must seriously contribute to, among other things, meeting the nutritional needs of the human population. This challenge constitutes a key part of the backdrop against which future evolution will occur. Genetic engineering technologies are and will continue to be an important component of agriculture; however, we must consider the evolutionary implications of these new technologies. Meeting these demands requires drastic changes in the undergraduate curriculum. Students of biology should be trained in molecular, cellular, organismal, and ecosystem biology, including all living organisms.
Resumo:
This paper introduces the session on advanced speech recognition technology. The two papers comprising this session argue that current technology yields a performance that is only an order of magnitude in error rate away from human performance and that incremental improvements will bring us to that desired level. I argue that, to the contrary, present performance is far removed from human performance and a revolution in our thinking is required to achieve the goal. It is further asserted that to bring about the revolution more effort should be expended on basic research and less on trying to prematurely commercialize a deficient technology.