If you thought generative AI chatbots like OpenAI’s ChatGPT were impressive, get ready for Tata Consultancy Services’ (TCS) version of this technology.
TCS, a leading global IT services, consulting, and business solutions organization, is working on its own version of ChatGPT for enterprise code generation.
The project is currently in its initial stages and is harnessing TCS’ vast internal resources, codes, and data.
The company plans to develop the solution using its own in-house algorithms that utilize large language modeling functions.
Key Points:
- TCS is building its own version of ChatGPT for enterprise code generation.
- The company is conceptualizing a role within the organization known as “Prompt Engineer.”
- TCS is building its own ChatGPT for enterprising code generation
According to N Ganapathy Subramaniam, Chief Operating Officer of TCS, the company’s generative AI will use past code, experience, and data to comprehend, just like other similar technologies.
He also said that the company has been in the business for several years, so the knowledge gained can be used as a base. This means that if the technology develops codes that have been taught algorithms using TCS proprietary data, it will be a product that can be licensed.
Subramaniam believes that to build proprietary generative AI algorithms, TCS needs to work on various use cases to develop code, and the process has to mature later.
He also acknowledges that fine-tuning is still required for enterprise usage of AI solutions when it comes to ownership as well as the IP of the end products.
As a result, demand for enterprise solutions will continue to grow.
Subramaniam, who is set to retire next year in May, expects TCS to launch some of these solutions before the end of his tenure. The main goal behind generating these models is to create codes that can easily be deployed.
He added that if TCS wants to develop secure and contextual generative AI solutions to speed up clients’ projects, it cannot simply depend on large language tools from various providers but instead should have its own solution.
“Clients are willing to utilize a generative AI,” said Subramaniam. “However, as a supplier, I am obliged to provide them with something that is free of any infringement and contains the complete ownership of the intellectual property.”
In addition, the industry needs to wait for regulations governing these solutions to mature further to release the full capability of the technology.
The Concept of a “Prompt Engineer”
TCS is also conceptualizing a role within the organization known as “Prompt Engineer.” This person will be responsible for creating prompts that guide the AI system to generate the desired code.
The Prompt Engineer will work closely with developers and data scientists to ensure that the AI generates the correct code. This person will also be responsible for debugging and refining the prompts to ensure that the system is continuously improving.
This role is essential to ensure that the AI generates quality code that is optimized for the intended task.
The Benefits of TCS’ Generative AI for Enterprise Code Generation
TCS’ generative AI has the potential to transform the way that code is generated for enterprise applications.
The technology will enable developers to generate code faster and more accurately than ever before.
This means that enterprises will be able to speed up their project delivery, leading to increased productivity and efficiency.
Moreover, TCS’ generative AI will be secure and will provide complete ownership of the intellectual property.
This is important for enterprises as they need to ensure that their code is not infringing on anyone else’s intellectual property rights.
Introducing “Prompt Engineers”: The Future of AI Communication
Tata Consultancy Services (TCS) is not only building its own version of ChatGPT for enterprise code generation, but also conceptualizing a new role within the organization known as “Prompt Engineers.”
According to N Ganapathy Subramaniam, the Chief Operating Officer of TCS, there is a massive opportunity in developing these new roles to effectively communicate contextual questions to large language models for the requirements of enterprises.
The Importance of Asking Questions on AI Platforms
Subramaniam emphasizes the importance of asking contextual questions on AI platforms, and how it can be extremely crucial.
With the new “Prompt Engineer” role, TCS aims to provide a solution to this problem. Although the role has not yet been authorized, Subramaniam believes it will be as critical as having engineering, analytical or mathematical skills.
Collaboration with Generative AI Offerings Using MasterCraft
TCS saw an opportunity to collaborate with generative AI offerings using MasterCraft, its low-code software development platform.
The company plans to add a ChatGPT-like solution for data pattern intelligence in the future, which will help MasterCraft become an intelligent low-code platform.
Currently, more than 100 clients are utilizing the Mastercraft tool, and TCS has developed a variety of solutions that utilize generative AI while functioning with global partners.
Similarities to CoPilot
CoPilot is a solution to auto-generate code, which was released by Microsoft-owned GitHub and OpenAI to speed up the writing process of the software program.
TCS’s new “Prompt Engineer” role will be quite similar, as it will allow for effective communication with large language models for the requirements of enterprises.
Challenges in Enterprise Usage of AI Solutions
Although TCS is developing new solutions to accelerate clients’ projects, Subramaniam believes fine-tuning is still required for enterprise usage of AI solutions when it comes to ownership as well as the intellectual property of the end products. Therefore, enterprise solutions will see demand.
In addition, the industry needs to wait for regulations governing these solutions to mature further to release the full capability of the technology.
TCS is building its own version of ChatGPT for enterprise code generation using in-house algorithms which utilize large language modeling functions.
The main aim behind generating these models is to create such codes which can easily be deployed to speed up clients’ projects.
Prompt Engineers are new roles within the organization who can effectively communicate contextual questions to large language models for the requirement of enterprises.
TCS is collaborating with generative AI offerings using MasterCraft, its low-code software development platform.
More than 100 clients are utilizing the Mastercraft tool.
CoPilot is a solution to auto-generate code, which was released by Microsoft-owned GitHub and OpenAI to speed up the writing process of the software program.
Subramaniam expects the Mumbai-based software firm to launch some of these solutions before the end of his tenure, as he will retire next year in May.
TCS wants to develop its own solution for generative AI because if they want to develop secure and contextual generative AI solutions to speed up clients’ projects, then they cannot simply depend on large language tools from various providers but instead should have its own solution.
Conclusion
The development of new roles for “Prompt Engineers” is a significant step towards effective communication with large language models for the requirements of enterprises. With the collaboration of generative AI offerings using MasterCraft, TCS aims to provide an intelligent low-code platform. While challenges in enterprise usage of AI solutions still exist, TCS continues to develop new solutions to accelerate clients’ projects.
The future of AI communication looks promising, and TCS is at the forefront of this exciting development.
