The reality is much simpler than what is often presented about science geniuses. Lorentz and Poincare had the math down to explain early experiments and the Max

The reality is much simpler than what is often presented about science geniuses. Lorentz and Poincare had the math down to explain early experiments and the Maxwell’s equations predictions of the constancy of the speed of light, and Einstein indeed provided a neat shift in the interpretation by taking a different perspective. (His photoelectric effect experiment and interpretation was a more genuine original contribution that came from experimental data and got him a Nobel prize.) The ideas behind gene editing existed since forever, but the observation that certain bacteria use a more accurate and selective gene editing system than viruses led to CRISPR. I have trouble with arguments where many examples in a row are not based on popular, often slightly mistaken beliefs, especially when it comes to discussions related to using such examples as analogies and arguments for predicting the future. I have talked to and worked with many different Nobel prize winners across different fields of science in my life, and although they were all extraordinary bright and focused individuals, the introductory part of this article misses the point. I agree that there is no linear extrapolation from being a good student, but I dont think the additional abilities are beyond the reach of machines. Focus, knowledge, perserverence, and the ability to analyze data very carefully are strict and challenging requirements. Asking the right questions is very important as well, but much easier than people assume.