The Intricacies Of Artificial General Intelligence And Curing Disease
Summary
Artificial general intelligence (AGI) may enable human-level reasoning and critical thinking across multiple cognitive domains. In recent months, AI model developers have claimed that soon, artificial general intelligence (AGI) will eventually be able to solve all disease. AGI generally refers to AI systems being capable of human-level reasoning and critical thinking across multiple cognitive domains, a milestone which many model developers have been working towards eagerly. One key aspect of this milestone is the thought that once AGI is achieved, there is a reasonable level of confidence that the hardest cognitive burdens could potentially be offloaded to AI systems to find solutions. Why? Because successful AGI systems will likely be able to summarize the entirety, if not centuries, of human experience and scientific discovery into rapidly usable data points, hence being able to meaningfully create an unprecedented level of productive outputs. The other key premise is the belief that the cure for all, if not many, diseases is already amongst us with regards to the raw ingredients; it’s simply about finding the right permutations, combinations and scope of scientific discovery to utilize them meaningfully.
Key points
- AGI could potentially solve all disease by offloading cognitive burdens and synthesizing centuries of human experience.
- A landmark article in the Journal of Pharmaceutical Analysis notes that AI helps accelerate drug discovery by removing uncertainty.
- A study in Drug, Design, Development and Therapy found AI lowers costs and time for drug development through better patient recruitment.
- Drug discovery is expensive because pharmaceutical companies invest billions of dollars and many years to bring a formulation to market.
- Clinical trials still require human capacity and time, and AGI systems are only as good as the data provided to them.
“"drug discovery has historically relied heavily on serendipity, with many significant breakthroughs occurring through chance observations or unintended findings. However, AI offers the potential to remove much of the uncertainty in this process, dramatically improving the chances of identifying commercially viable drug candidates while reducing both costs and time."”
Background
Traditional drug discovery is a resource-heavy process that often relies on trial and error to find a specific key to fit a protein folding pattern out of billions of potential options.
Why it matters
If AI systems can cut costs in the drug design process, pharmaceutical companies may pass savings onto consumers, making treatments more affordable.
What's next
There is a need for more cohesive policy efforts and unified guardrails as the world enters a new chapter with AGI.