Finance
Ray Kurzweil on how AI will transform energy, manufacturing and medicine
He’s probably wrong about medicine.
Ray Kurzweil writes:
After working in the field [of AI] For 61 years – longer than anyone alive – I’ve been happy to see AI at the center of the global conversation. Yet most commentary ignores how large language models like Chatgpt and Gemini fit into an even larger story. AI is about to make the leap from a revolution in just the digital world to a transformation of the physical world as well. This will bring countless benefits, but three areas will have particularly profound implications: energy, manufacturing and medicine.
This is from “Ray Kurzweil on How AI Will Transform the Physical World,” The economistJune 17, 2024. (closed)
Kurzweil makes his case.
Another excerpt:
In contrast, AI can quickly sift through billions of chemistries in simulation and is already driving innovations in both solar photovoltaics and batteries. This is about to accelerate dramatically. Throughout history up to November 2023, humans had discovered approximately 20,000 stable inorganic compounds for use in all technologies. Then Google’s gnome AI discovered many more, instantly increasing that number to 421,000. Yet this barely scratches the surface of materials science applications. Once a much smarter AGI [artificial general intelligence] If fully optimal materials are found, photovoltaic megaprojects will become viable and solar energy could be so abundant as to be almost free.
The abundance of energy makes a new revolution possible: in production. The costs of almost all goods – from food and clothing to electronics and cars – largely come from a number of common factors such as energy, labor (including cognitive labor such as research and development and design) and raw materials. AI is on track to dramatically reduce all these costs.
Where he falls short is medicine. It’s not that he doesn’t make a good case that in a relatively unregulated market, AI could easily have huge positive effects on the kinds of drugs we put into our bodies. It’s because he seems oblivious to the enormous power the Food and Drug Administration has over what drugs we can have.
He is writing:
Much more laboratory research is needed to accurately fill larger simulations, but the roadmap is clear. Next, AI will simulate protein complexes, then organelles, cells, tissues, organs and – ultimately – the entire body.
This will eventually replace current clinical trials, which are expensive, risky, slow and statistically underpowered. Even in a phase 3 trial, there is likely not one subject that matches you on all relevant factors of genetics, lifestyle, comorbidities, drug interactions and disease variation.
Digital examinations allow us to tailor medications to each individual patient. The potential is breathtaking: not only to cure diseases such as cancer and Alzheimer’s disease, but also the harmful effects of aging itself.
This will only happen if the FDA withdraws substantially. Let’s hope, but don’t let hope overpower painful learning from experience.
