In a recent interview with Business Today, N Ganapathy Subramaniam, COO of Tata Consultancy Services (TCS), said that the company is “currently piloting the capabilities of generative AI” and that they are “optimistic about the potential of this technology.”
Subramaniam explained that generative AI is a type of artificial intelligence that can be used to create new content, such as text, images, or code. He said that this technology has the potential to revolutionize a wide range of industries, including healthcare, manufacturing, and financial services.
However, Subramaniam also acknowledged that there are some challenges to adopting generative AI. He said that one challenge is the cost of developing and deploying these systems. Another challenge is the need to protect intellectual property.
Despite these challenges, Subramaniam said that he is confident that generative AI will eventually become a mainstream technology. He said that TCS is “committed to helping our clients adopt this technology” and that they are “already working on a number of use cases.”
Here are some of the specific use cases that Subramaniam mentioned:
- In healthcare, generative AI could be used to develop new drugs or treatments.
- In manufacturing, generative AI could be used to design new products or optimize production processes.
- In financial services, generative AI could be used to develop new investment strategies or generate personalized financial advice.
Subramaniam also said that generative AI could be used to create new forms of entertainment, such as interactive games or virtual reality experiences.
Overall, Subramaniam’s comments suggest that TCS is bullish on the future of generative AI. He believes that this technology has the potential to revolutionize a wide range of industries and that TCS is well-positioned to help its clients adopt it.
Challenges to Adopting Generative AI
As Subramaniam mentioned, there are some challenges to adopting generative AI. One challenge is the cost of developing and deploying these systems. Generative AI models can be very complex and require a lot of data to train. This can make them expensive to develop and deploy.
Another challenge is the need to protect intellectual property. Generative AI models can be used to create new content, such as text, images, or code. This content can be valuable intellectual property, so it is important to protect it from unauthorized use.
Finally, there are some ethical concerns associated with generative AI. For example, some people worry that generative AI could be used to create fake news or propaganda. It is important to address these ethical concerns before generative AI becomes more widely adopted.
Conclusion
Generative AI is a powerful new technology with the potential to revolutionize a wide range of industries. However, there are some challenges to adopting this technology, such as cost, intellectual property, and ethical concerns. TCS is committed to helping its clients adopt generative AI and is already working on a number of use cases.
It will be interesting to see how generative AI develops in the coming years. If the challenges can be overcome, this technology has the potential to have a major impact on the world.