Natural language interfaces for AI are challenging due to the vast degree of freedom in text input.
Prompt engineering is crucial for effectively utilizing large language models to ensure correct and meaningful responses.
For most users, interacting with AI systems through buttons and defined interfaces can lead to more efficient and seamless experiences compared to using natural language prompts.
Many people have yet to experience the impact of AI in their daily lives, indicating that the anticipated AI-driven future is not fully realized yet.
AI tools like ChatGPT and Copilot are currently used by individuals but haven't proliferated widely, with some potential hurdles being the need for broader education and the slow pace of product innovation.
The future of AI products may unfold slowly over the next 5-10 years, with challenges like technical limitations, business viability, and the need for transformative breakthroughs still to be addressed.
The strength of a platform is heavily dependent on its identity layer, which includes verifying users and maintaining trust.
Analyzing platforms in layers like a cake, starting with identity, then social proof, personalization, and finally super app-ification.
Platforms can enhance user experiences and unlock new revenue streams by leveraging a strong identity layer to provide personalized services and products.