The AI Convergence: Transforming Generative AI into Deterministic Models
By now, the world knows the true power of Generative AI. From their multi modal capabilities to their ability to digest information and deliver them in a conversational format has taken the world by storm. Every organization is now in a race to implement Generative AI into their workflow to create a new level of personalization in their customer engagement channel. While use cases like chatbots makes a perfect candidate for using Generative AI, organizations also have an obligation to deliver consistent response for a given input, a capability that Generative AI models today lack.
Multimodal capability refers to the ability of a Generative AI model to process and generate data across multiple forms of media, such as text, images, audio, and video, simultaneously or in an integrated manner.
I see huge investments being made across the different business domain without even thinking about standardization and consistency as a factor. This maybe because of the fact, being in the race is far more important than doing the right preparation before joining one. Only time can tell how these organizations will perform in the long run.
For those enthusiasts like me who wonder how to make Generative AI models to deliver a consistent response, I am compiling my thoughts in this blog…
