I spoke with Tata Consultancy Services about how new tools can help speed up AI adoption across a range of businesses

TCS teams up with Nvidia to speed up AI adoption, but how does this help businesses - and are there any risks?

News By James Capell published 5 November 2024

Back in May 2024, Tata Consultancy Services (TCS) carried out a study which revealed businesses wanted to use AI for innovation and revenue growth, but were not sure how to do it.

Now, TCS has teamed up with Nvidia to help accelerate AI adoption across a range of industries by using the latter's infrastructure to build customized AI solutions for sectors including manufacturing, automotive, finance, and retail based on large language models.

I spoke with Anupam Singhal, President of Manufacturing at TCS, about how these AI tools work, how they can benefit businesses, and how to mitigate the risks of using AI (if any) in these industries.

Anupam Singhal

When you think of language models, the topic of manufacturing or automotive industries doesn't jump straight to the front of the mind. Can you tell me more about the link between language models and how they can help manufacturing and a range of other industries?

Whilst language models might initially seem more suited for textual tasks and we do often corelate B2C use cases to them, they also possess significant potential to revolutionise industries like manufacturing and automotive in B2B and B2B2C cases.

We are already seeing this potential come to life through our Future Ready Manufacturing solutions. Here, we are transforming repair and service cycles and predictive maintenance too. We use language models to analyse historical data and identify patterns which can help indicate potential equipment failures, reducing downtime and optimising maintenance schedules. What's more, using Generative AI and SLM’s (Specialised language Models) we can transform the daily activity of a Repair and Service Technicians to improve the time taken in the repair/service cycle.

Language models are also transforming supply chain resilience. By analysing supply chain data these models can optimise inventory levels, improve logistics, and mitigate supply chain disruptions.

TCS finetunes LLMs based on industry expertise. What goes into this process and what safeguards are in place to ensure that the model does not provide sub optimal suggestions for industry challenges

Finetuning LLMs for industry-specific applications is a meticulous process. Firstly, using our industry expertise and customers’ ecosystem, we curate a high-quality dataset specific to the industry, ensuring it covers a wide range of scenarios and edge cases. We then leverage pre-trained and out-of-the-box language models as a foundation, and fine-tune these based on the industry-specific data sets.

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