 "Nandan Nilekani")
The Generative artificial intelligence (GenAI) revolution is in its second year now and some clarity is beginning to emerge from the noise and babble of the last 18 months, Infosys Chairman Nandan Nilekani said.
“The initial hyperventilation of AI doomerism and the risk of human extinction by AI advances like artificial general intelligence (AGI) has quietened down," he said.
People have accepted that like any other general-purpose technology such as electricity, nuclear energy, internet, or the discovery of fire, GenAI has enormous potential for good when explored within the guardrails of responsibility, Nilekani wrote in a letter to shareholders in its latest annual report.
“Besides, many of the doomsday prophets pleading for extensive AI regulation have revealed themselves to be just protectionists who want to limit the fruits of GenAI to a few companies and investors," he said. The real power of AI, Nilekani said, would come from configuring all the different models and tools to get the best solutions. "It is also clear that there won’t be a scenario where we will have ‘one model to rule them all’. Every day brings new advances in large language models from a dizzying set of actors all pushing for greater innovation," he wrote.
To keep up with fast-paced technology, businesses need to "future-proof" their AI infrastructure to avoid getting stuck at a dead end with outdated technology, Nilekani said.
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Enterprise vs consumer AI
As AI evolves, it is evident that enterprise AI will be markedly different from consumer AI, he said. “The manifestations of consumer AI will be packaged in wondrous ways to make life easier and more productive for millions of people… Not unlike the smartphone that brought the magic of apps and touchscreen to billions, consumer AI will push the envelope of usability, convenience, and accessibility for everyone," Nilekani said.
Enterprise AI, on the other hand, requires a "root and branch surgery of the complex and multi-generation technology (both legacy and modern), that lie within firms".
The AI models will turn into commodities and the challenge will be to orchestrate the extensive data in a way that it is consumable by AI,” Nilekani said.
Focus on compliance
As various nations come up with different ways of regulating AI, global companies will have to build their AI applications in a way that they are compliant in every country. “While application can be trialled on very large models, deployment will be on narrow transformers, trained on relevant enterprise data, fully secure and efficient in their inferencing. Enterprises will need both an AI foundry for experimentation, and an AI factory for scaling up,” Nilekani said.
Infosys is said to be working on about 200 GenAI projects in various stages as large organisations are increasingly looking at improving cost efficiency and customer experience as the economic environment gets better.
