Three Use Cases Of Gen-AI Which Can Be Useful For Organisations

In the ever-evolving landscape of technology and human interaction, the emergence of Generation AI marks a significant juncture. Born into a world where artificial intelligence (AI) is not just a tool but an integral part of daily life, this generation navigates a reality shaped by unprecedented connectivity, automation, and innovation.

Generation AI encompasses those individuals who are coming of age in a society where AI systems influence everything from education and employment to entertainment and healthcare. This generation is not only adept at utilizing AI-powered technologies but also stands poised to redefine societal norms, ethical considerations, and the very fabric of human existence in this digital era.

The Generative AI is looking at the cognitive and non-repetitive task that we thought only human beings could do; but now, Gen-AI will be able to do it, said Srikanth Nadhamuni, Founder, CTO, Aadhaar & Co-founder and Chairman, Trustt while delivering a keynote address at Entrepreneur India’s flagship event Tech & Innovation Summit 2024 on March 8 and 9 in Bangalore.

Code Generation

“There is a vast landscape of applications where Gen-AI can be used to generate text for marketing or social media platform. It can also be used for code generation which gives you 3 fold improvements in coding speed and almost eight to 10 fold improvement in documentation,” Nadhamuni added saying that code generation is going to be super important.

Quoting Jensen Huang, CEO, Nvidia, he said, “For years, everybody use to say that everybody has to learn programming whether you are a techie, a lawyer or a doctor. That was the conventional wisdom 10 years ago. Now, he is saying that you don’t have to learn to code. Say it and it will code for you.”

Retrieval Augmented Generation

Speaking on the issue of wrong responses from AI, like GPT he said that Retrieval Augmented Generation (RAG) is the technology that can be used to prevent such incidents.

“There is very powerful paradigm of Retrieval Augmented Generation (RAG) which can be used to prevent incidents like wrong and irrelevant responses from the LLM. If you use GPT which has read up all the data on the internet, there is a possibility that it might come up with the responses that are not relevant and are wrong for you. This is the biggest issue with LLM and RAG is the powerful technique which can help prevent such incidents,” he said.

Under RAG, you give your own data and when you ask questions, LLM only used to generate relevant answers to your query based on the data that you have created, he added further.

Customer Service

Srikanth Nadhamuni also shared the following use cases of Generative AI that can be beneficial, including Customer Service, Financial Decision-Making Through Analytics, Language Understanding, and Translation, Regulatory Compliance (RegTech), Personalised Banking.

“Customer service is the fantastic app when it comes to AI as no human is going to go all your CTR records understand the real needs of the customer and then answer the question whereas AI can and give answer in your own language,” he said.