Based on the multitask generalisation capabilities shown so far of LLMs I’m kinda in the opposite camp - if we can figure out more data efficient and reliable architectures base language models will likely be enough to do just about anything and take general instructions. Like you can just tell the language model to directly operate on Google calendar with suitable supplied permissions and it can do it no integration needed
Exactly this. There is a reasonable chance the GUI goes the way of the dodo and some large (75% or something) percentage of tasks are done just by typing (or speaking) in natural language and the response is words and very simple visual elements.
People are building toy demos in a day that are not actual useable products. It’s cool, but it’s the difference between “I made a Twitter clone in a weekend” and real Twitter.
1 - companies are deploying real products internally for productivity, especially technical and customer support, and in data science to enable internal people to query their data warehouse in natural language. I know of 2 very large companies with the first in production and 1 with the second, and those are just ones I'm aware of.
2 - you are conflating the problems of engineering a system to do a thing for billions of users (an incredibly rare situation requiring herculean effort regardless of the underlying product) with the ability of a technology to do a thing. The above mentioned systems couldn't handle billions of users. So what? The vast majority of useful enterprise saas could not handle a billion users.
