Don't think of LLMs as entities but as simulators. For example, when exploring a topic, don't ask:
"What do you think about xyz"?
There is no "you". Next time try:
"What would be a good group of people to explore xyz? What would they say?"
The LLM can channel/simulate many perspectives but it hasn't "thought about" xyz for a while and over time and formed its own opinions in the way we're used to. If you force it via the use of "you", it will give you something by adopting a personality embedding vector implied by the statistics of its finetuning data and then simulate that. It's fine to do, but there is a lot less mystique to it than I find people naively attribute to "asking an AI".
@kentcdodds Here is the core architecture -
1.Listens - LLM intent classification + routing
2.Understands - Knowledge graph traversal + RAG
3.Checks - Plan-before-execute + Human in loop
4.Acts - Function calling to API bridge to actual API calls
@aravind 3 - I am sorry, but I was also programmed before on my view about my own country, but when I started living outside, I saw the stark contrast in terms of culture, intellectual capacity, standard of living, and natural beauty. We have everything, but we are not proud of it
@aravind 2 - What I hear from them is the stereotypical view from the social media disinformation, catching the same waves i see some young influencers try to cash-on on this image further amplifying the negativity.
@aravind 1 - Right on point, sir. India is blessed with natural beauty, right from the Himalayas to the Western Ghats, from the Thar to the Darjeeling tea gardens. We have everything for all seasons, my heart wrenches when I meet non indians who don't know about this.