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Infrastructure emerges as biggest challenge for enterprises to scale GenAI

Bengaluru: Even as artificial intelligence (AI) gains traction in different industries, companies are grappling with infrastructure challenges as they look to increasingly incorporate AI and its newest form, generative AI (GenAI), into their operations.

Industry experts hashed out the “infrastructure” challenge that their companies were looking to overcome, in a fireside chat at the Mint AI for Business Summit 2024, held in association with IBM.

Ramesh Lakshminarayanan, chief investment officer (CIO) at HDFC Bank Ltd, said creating the AI infrastructure was the first impediment his company was looking to overcome. “We are kind of working in a dual mode, what we call as the on-prem mode of looking at GenAI and we’re also trying to see how to look at public AI in some spaces,” he said.

On-prem or on-premise refers to an organisation managing its own hardware, software and data within its own physical location.

Lakshminarayanan added that figuring out the right infrastructure for AI, whether it is on-prem, cloud, or a kind of hybrid infrastructure would pose the biggest challenge for enterprises looking to scale artificial intelligence in their operations.

In an organisation’s bid to convert pilot AI projects into real-time projects, Lakshminarayanan also stressed that companies would not get the correct AI output if they did not have the right information architecture in place.

Viswanath Ramaswamy, vice-president of technology sales, India/South Asia, IBM, broadened the definition of “infrastructure” to include security principles pertaining to frauds, and also biases and ethics to that AI model.

On the hardware side of things, Ramaswamy said organisations have to decide whether they would retrain the AI models or continue with the trained models they already have. “If you (the company) already have a trained model which you do not require a retraining for, a central processing unit (CPU) can do the job….but if you’re retraining the AI model, which is when you require a whole lot of graphic processing units (GPUs), and that’s one challenge, either you do it on-premises or on the cloud,” said Ramaswamy.

Adding that security design around that AI model’s infrastructure gains importance due to exposure, Ramaswamy said that explaining the outcome of the AI model without any bias also formed a part of having a responsible AI infrastructure.

On Gen AI’s uses for marketing purposes, Arvind Iyer, head of marketing for Piramal Capital and Housing Finance Ltd, said his company is looking to employ Gen AI in interactions or transactions with customers. Iyer said his company, a large part of whose marketing is hinterland-based, is also looking to develop linguistic capabilities to talk to customers with various “cultural nuances.”

“We’re now really looking forward to what Bharat GPT does so a lot of Natural Language Processing (NLP) – related work is something that we are fronting,” said Iyer.

Natural Language Processing (NLP) is a component of AI that is used to understand human language in both, written and verbal forms.

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Published: 27 Mar 2024, 06:01 AM IST

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