This article is really only useful if LLMs are actually able to close the gap from where they are now to where they want to be in a reasonable amount of time. There are plenty of historical examples of technologies where the last few milestones are nearly impossible to achieve: hypersonic/supersonic travel, nuclear waste disposal, curing cancer, error-free language translation, etc. All of which have had periods of great immediate success, but development/research always gets stuck in the mud (sometimes for decades) because the level complexity to complete the race is exponentially higher than it was at the start.
Not saying you should disregard today's AI advancements, I think some level of preparedness is a necessity, but to go all in on the idea that deep learning will power us to true AGI is a gamble. We've dumped billions of dollars and countless hours of research into developing a cancer cure for decades but we still don't have a cure.
Not saying you should disregard today's AI advancements, I think some level of preparedness is a necessity, but to go all in on the idea that deep learning will power us to true AGI is a gamble. We've dumped billions of dollars and countless hours of research into developing a cancer cure for decades but we still don't have a cure.