You are probably wrong about the medication.
Ray Kurzweil says:
After working in the field [of AI] 61 years—longer than anyone else alive—I’m glad to see AI at the heart of the global conversation. But most of the comments miss how big language models like Chatgpt and Gemini fit into an even bigger story. AI is about to take a rapid step from changing the digital world to changing the virtual world. This will bring countless benefits, but three areas have the most profound impacts: energy, productivity and medicine.
This is from, “Ray Kurzweil on how AI will change the physical world,” The EconomistJune 17, 2024. (digested)
Kurzweil makes his case well.
Another quote:
In contrast, AI can quickly sort out billions of chemistries through simulation, and is already driving innovations in both photovoltaics and batteries. This is good for speeding up a lot. Throughout history until November 2023, humans have discovered about 20,000 stable inorganic compounds for use in all technologies. Then, Google’s gnome AI found more, increasing that number overnight to 421,000. But this does not scratch the surface of the application of materials science. AGI is very intelligent [artificial general intelligence] gets things fully right, photovoltaic megaprojects will work and solar energy will be so abundant that it will be almost free.
Abundance of energy makes another revolution: in production. The cost of almost all goods—from food and clothing to electronics and cars—comes largely from a few common items such as energy, labor (including cognitive work such as r&d and design) and raw materials. AI is on the way to significantly reduce all these costs.
Where he fails is medicine. Not that he doesn’t make a good case that in a relatively unregulated market, AI could have far-reaching effects on the types of drugs we put into our bodies. It is because he seems to be unaware of the enormous power the Food and Drug Administration has over the drugs we will be allowed to possess.
You write:
More laboratory research is needed to accurately complete large-scale simulations, but the road map is clear. Next, AI will model protein complexes, then organelles, cells, tissues, organs and—eventually—the whole body.
This will eventually replace today’s clinical trials, which are expensive, dangerous, slow and statistically weak. Even in a phase 3 trial, there is almost no single subject that matches you in all aspects of genetics, lifestyle, comorbidities, drug interactions and disease diversity.
Digital testing will allow us to tailor medicine to each patient. The potential is amazing: to treat not only diseases like cancer and Alzheimer’s, but the harmful effects of aging itself.
This will only happen if the FDA backs down in a big way. Let’s hope, but don’t let hope overcome the painful learning of experience.
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