IBM’s new generative AI product to boost mainframe application modernisation

Tech major IBM on Tuesday announced a new generative AI-assisted product -- Watsonx Code Assistant for Z.

New Delhi: Tech major IBM on Tuesday announced a new generative AI-assisted product — Watsonx Code Assistant for Z, that will help enable faster translation of COBOL to Java on ‘IBM Z’ and enhances
developer productivity on the platform.

This product will be generally available in the fourth quarter (Q4) of 2023 and is being designed to help accelerate COBOL application modernisation.

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“IBM is engineering Watsonx Code Assistant for Z to take a targeted and optimized approach. It’s built to rapidly and accurately convert code optimized for IBM Z, accelerate time to market and broaden the skills pool,” Kareem Yusuf, PhD, Senior Vice President, Product Management and Growth, IBM Software, said in a statement.

According to the company, Watson Code Assistant makes it easier for anyone to write code with AI-generated recommendations.

The product is also designed to assist businesses in leveraging generative AI and automated tooling to accelerate their mainframe application modernisation — all to preserve the performance, security and resiliency capabilities of IBM Z.

Moreover, IBM has designed this product to refactor, transform, and validate COBOL code to help speed time-to-value and augment skills for critical application modernisation on IBM Z.

The product will be enabled by a 20 billion parameter large language model (LLM) for code.

The COBOL data processing language supports many vital business and operational processes at organisations globally, however using Watsonx Code Assistant for Z in comparison to other approaches could make it easier for developers to selectively and incrementally transform COBOL business services into well-architected high-quality Java code, the company said.

Generative AI can help developers to more quickly assess, update, validate and test the right code, allowing them to more efficiently modernise large applications and focus on higher impact tasks.