I think this is one of the greatest features of LLMs. They are incredibly powerful tools, but have obvious limitations that require a certain amount of finesse to manage.
During the peak Uber hype cycle, insufferable self-driving people were always yabbering on about how superior the AI is, robot taxis will take over, etc. it was difficult to assess or discuss those statements then when the AI models cost millions and weren’t available outside of major companies, who tend to downplay their failures.
Now, thousands or even millions of people can set LLMs onto a variety of critical and mundane tasks that they can actually objectively evaluate. As end users, we can now build fluency in how different approaches to AI work and don’t work.
During the peak Uber hype cycle, insufferable self-driving people were always yabbering on about how superior the AI is, robot taxis will take over, etc. it was difficult to assess or discuss those statements then when the AI models cost millions and weren’t available outside of major companies, who tend to downplay their failures.
Now, thousands or even millions of people can set LLMs onto a variety of critical and mundane tasks that they can actually objectively evaluate. As end users, we can now build fluency in how different approaches to AI work and don’t work.