Chris is very optimistic about the "new" approach that leverage the power of huge amount of data since, as in the Unreasonable said, for many tasks, the millions or so examples might represent the whole picture of the world.
By reading the comments, I realized that, maybe it is time to think what tasks can leverage the power of data, and let the data speaks itself. One comments try to challenge the approach by "nuclear fusion;" another thought some disciplines, like physics, still stand upon neat theories and models, while other disciplines, like biology, economics, where models come and go, could benefit more from data deluge than others.
Going back to my own questions, what are those tasks? It seems to me that the data generated by human beings themselves such as languages and behaviours might be able to speak themselves, meanwhile data generated from the nature--earth, sky, universe-- (of course, they are measured and sensored by human beings, but not of ourselves) might need to be spoken by real experiments and observations. As one comment said, the models discovered by J. Craig Venter are not discoveries until these models are confirmed with things found in real world. Therefore models from ourselves could be relatively easily validated than models from natural data, like in high energy physics, where very few data will come out until new accelerators are built.
