Honestly it very much looks like that. With current technology, we just need feasible integrations to disseminate and we can remove huge swathes of knowledge workers.

This will enable many new business models, but the amount of paying customers may rapidly decline too, complicating matters. Blue collar workers (especially around the world), can to a large extent already be automated away (ordering screens at restaurants, arms deep frying chicken and putting it on a conveyor belt... e.g. workerless KFCs in Russia: https://www.youtube.com/watch?v=7cighS7cNvk or a Chinese restaurant in a rustbelt city my mom visited with a robotic waiter bringing food from the kitchen). Costs just have to decrease to make this feasible.

And at the current rate of improvement - friends in the field say many techniques from 2018 papers still aren't in production - I honestly doubt if even the top 5-10% of capable workers can truly keep up. It's horrifying and challenging...

But yes, this is all in the backdrop of a new revolution in industry!

LLMs will be quickly replaced with Large Multi-Modal Models.

I do agree that there is something here, but it will likely take longer than we think. There are still issues with tasks requiring large context or specific domain expertise. Then there are tasks that are better suited to an existing algorithm than a LLM, like renaming a function across a large code base. How do we integrate and balance the two ends of the spectrum?

t's fascinating to observe the rapid progress of large language models like GPT-4 and their increasing capabilities. While it's difficult to predict the exact trajectory of these models, it's evident that they have the potential to revolutionize many aspects of our lives, much like the industrial revolution did. The ability to automate complex tasks, generate human-like responses, and aid in problem-solving across various domains indicates that these AI models could significantly impact productivity, communication, and even the job market. However, it's essential to approach this transformation with caution, addressing potential ethical concerns, biases, and the implications on human society as a whole. Just as the industrial revolution came with both benefits and challenges, it's crucial that we prepare for and manage the consequences of large-scale AI adoption in our daily lives