This is the spread of use cases of ChatGPT usage. What is not evident from the chart is that people didn’t really ask/need an LLM to do it.
Most of the users would be totally cool to have one app for images, another for summaries, another for coding assistance and just another for music.
( The chart was created by asking ChatGPT )
So long the features and cost are reasonably good, most of users won’t even care what’s powering them.
The everything-everywhere-all-at-once nature of LLMs signifies that their builders have been successful in discovering use cases around the powers that GPT gave them.
This is also the game where feature parity tends to plateau very soon. Ask anyone who has developed a successful consumer-focused mobile utility app or look at your own mobile app installation history over the last decade.
While there is always some buzz around the benchmark, the latest model from some company has beaten but 5 years into LLMs, the real question we need to ask is does the end consumer notice or even care ? Especially the average retail internet consumer? (where the market capitalization lies 🙂 )
Which is to also imply that for end internet users, the craze or utility of GenAI might have peaked as novelty and is taken for granted at par with you mobile phones.
When was the last time did you really felt the difference between version 10 and 11 of your mobile phone?
Ah LLMs ….
PS: 60% of paying chatgpt users are enterprise
