Maybe he was wrong about the medicine.
Ray Kurzweil wrote:
After working in the field [of AI] For 61 years, longer than anyone else, I have been delighted to see AI at the center of the global conversation. But most commentary overlooks how large-scale language models like Chatgpt and Gemini fit into a much larger story. AI is poised to leap beyond the digital revolution to the physical world. This will bring countless benefits, but three areas have particularly profound implications: energy, manufacturing, and medicine.
This is Ray Kurzweil’s article on “How AI Will Change the Physical World”. economistJune 17, 2024. (gate)
Kurzweil made his point well.
Another excerpt:
In contrast, AI can rapidly explore billions of chemicals in simulations, and is already driving innovation in both photovoltaics and batteries. This is poised to accelerate dramatically. By November 2023, humanity would have discovered some 20,000 stable inorganic compounds that could be used across all technologies. Then Google’s Gnome AI discovered even more, increasing that number to 421,000 overnight. But that barely scratches the surface of materials science applications. AGI Gets Much Smarter [artificial general intelligence] Finding the optimal materials could make large-scale solar projects feasible and solar energy so abundant that it is nearly free.
Energy abundance enables another revolution in manufacturing. The cost of almost all goods, from food and clothing to electronics and automobiles, comes primarily from a few common factors: energy, labor (including cognitive labor such as R&D and design), and raw materials. AI is on the way to significantly lowering all these costs.
Where he falls short is in medicine. That’s not to say that a relatively unregulated market doesn’t make a good case for how AI could easily have a big positive impact on the kinds of drugs we put in our bodies. He doesn’t seem to realize the enormous power the Food and Drug Administration (FDA) has over which drugs we can allow.
He wrote:
Although much more laboratory research is needed to accurately create large-scale simulations, the roadmap is clear. Next, AI simulates protein complexes, then organelles, cells, tissues, organs, and finally the entire body.
This will ultimately replace today’s clinical trials, which are expensive, risky, slow, and statistically underpowered. Even in a phase 3 trial, there will probably not be a single subject who matches you on all relevant factors, including genetics, lifestyle, comorbidities, drug interactions, and disease variants.
Digital trials allow us to provide personalized medicine to each patient. The potential is amazing. It can treat diseases such as cancer and Alzheimer’s disease, as well as the harmful effects of aging itself.
This will only happen if the FDA backs down in a substantive way. Have hope, but don’t let hope overpower the painful learnings from experience.
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