Democratization for the GenAI boom
Over the next few years, cloud infrastructures need to be designed to be GenAI-centric, to drive innovation and action — with clear cost structures and scalability. Through an open cloud infrastructure, businesses can be empowered by greater transparency throughout the model-training process, as well as improved interpretability of AI algorithms. How?

  • There will hopefully be more open-source AI model communities where models and related tools and services are shared among global developers.
  • While there will be a co-existence of closed-source and open-source LLMs, the ability of open-source solutions to democratize AI should accelerate its adoption.
  • Open-sourced LLMs can drive growth of AI model communities, which prioritize collaboration for improved AI interpretability. In turn, this means that there will be more democratized access for organizations of all sizes and resources, to innovate on new or enhance existing products and services with the help of GenAI.
  • One example of open source collaboration that can widen the impact of GenAI is LLMs that provide enhanced support for local languages and diverse cultures of South-east Asia. The growth of these localized open-sourced LLMs will also drive the further growth of AI model communities that prioritize collaboration for improved AI interpretability.
  • The democratization of AI, and the delivery of open, GenAI-ready cloud services also means businesses will be able to devote more resources into organizational data, to make sure it is synthesized and usable by LLMs. After all, GenAI is great at summarizing and synthesizing data, but less impressive when it comes to gaining insights from unstructured data.