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Comment by hackernoteng | Hacker News Reader

The growth and opportunities will be at the application layer. Training and fine-tuning LLMs doesn't really have that much value. Closed source (OpenAI) models and Open source models will be the foundation. As I said running some training/fine-tuning on top of these models and knowing how to do evaluations wont have that much value. Learn how to build useful applications on top of these things instead.

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The most successful use pf generative AI is a chatbot… once you can use a model with natural language you need less rich UIs. I think UIs will become simpler and value will be in the proprietary data you can manage to grab to adapt existing models to some valuable use cases.

chat is the new ui..imagine going to a bank website and you just enter in the chat - I need to view transactions and pause my debit card. It may then create an action list, and take you to the two links in order, without needing to find a button, or link. That saves a lot of time... In the future with AGI/SGI, though... well -- AI can be the entire app... you want a tax software with the look/feel of quickbooks or same exact functionality no problem... you want a 3d ai avatar that has all those things but interacts via speech, just ask for it... you want a VR version of the original 8bit legend of zelda - just ask.

Any software will just be created without any care for frameworks, platform, hosting, etc... it'll be hosted in the 'brain' of the ai.

>> Training and fine-tuning LLMs doesn't really have that much value.

I'm really not sure about that... seeing people talking about LLMops (as a role) and things like that. Well, let's see.

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