I researched creative AI and how AI can help people be creative, people thought it was a ridiculous and pointless topic. I’m biased.
Firstly, I think it’s important to see the non-chat applications. Goblin Tools is a great example of code we just couldn’t have written before. Purely from an NLP perspective, these tools are outstanding, if imperfect.
I’m excited to see new paradigms of applications come up when talented new developers are able to locally run LLMs and integrate them into their everyday programming, and too see what they can cook up in a world where that’s normal.
I’m interested in LLMs not to generate data on the fly, but to pre-generate and validate massive amounts of content or data than we’d otherwise be able to for things like games.
From a chat perspective, I like that it can support fleshing out ideas, parsing lots of data in a usable way.
And finally I’m excited for how lightweight LLMs could affect user interface design. I could imagine a future where OSs have swappable LLMs like they have shells that can allow for natural language interfacing with programs.
I don’t know, it’s just really accessible NLP, and that’s great.
What I find interesting is how useful these tools are (even with the imperfections that you mention). Imagine a world where this level of intelligence has a consistent low error rate.
Semantic computation and agentic function calling with this level of accuracy will revolutionize the world. It’s only a matter of time, adoption, and availability.
I researched creative AI and how AI can help people be creative, people thought it was a ridiculous and pointless topic. I’m biased.
Firstly, I think it’s important to see the non-chat applications. Goblin Tools is a great example of code we just couldn’t have written before. Purely from an NLP perspective, these tools are outstanding, if imperfect.
I’m excited to see new paradigms of applications come up when talented new developers are able to locally run LLMs and integrate them into their everyday programming, and too see what they can cook up in a world where that’s normal.
I’m interested in LLMs not to generate data on the fly, but to pre-generate and validate massive amounts of content or data than we’d otherwise be able to for things like games.
From a chat perspective, I like that it can support fleshing out ideas, parsing lots of data in a usable way.
And finally I’m excited for how lightweight LLMs could affect user interface design. I could imagine a future where OSs have swappable LLMs like they have shells that can allow for natural language interfacing with programs.
I don’t know, it’s just really accessible NLP, and that’s great.
What I find interesting is how useful these tools are (even with the imperfections that you mention). Imagine a world where this level of intelligence has a consistent low error rate.
Semantic computation and agentic function calling with this level of accuracy will revolutionize the world. It’s only a matter of time, adoption, and availability.