The talk track I've been using is that LLMs are easy to take to market, but hard to keep in the market long-term. All the hard stuff comes when you move past the demo and get exposure to real users.
And that's where you find that all the nice little things you got neatly working fall apart. And you need to prompt differently, do different retrieval, consider fine-tuning, redesign interaction, etc. People will treat this stuff differently from "normal" products, creating unique challenges.
Recent articles
- Gemini 2.0 Flash: An outstanding multi-modal LLM with a sci-fi streaming mode - 11th December 2024
- ChatGPT Canvas can make API requests now, but it's complicated - 10th December 2024
- I can now run a GPT-4 class model on my laptop - 9th December 2024