Optimizing Generative AI with Prompt Engineering and Fine-Tuning

While innovations in the space of AI/ML have been going on for over a decade now, there has been a steep surge in its adoption and large-scale implementation across industries in the last few years. And, among the various applications of AI, generative AI has emerged as an essential enabler of forward-looking, digital-first enterprises. Likewise, Generative AI’s journey over the years has also been nothing short of remarkable. From purpose-specific translation of natural language and mastering new perspectives to the implementation of large language models (LLMs) for fast and meaningful conversations, generative AI has come a long way.

As we navigate the digital+ landscape and embark on an AI-driven journey to the future of the workplace, the application of generative AI will not be limited to customer-focused marketing activities. Over the next few years, generative AI will disrupt, impact and reshape operations across various fields, including IT and DevOps. It will also increasingly be applied across industries, such as healthcare, retail and CPG, education, BFSI, business and digital process outsourcing, and media and entertainment, among others.

Intelligent Coding: Generative AI-Driven Software Development

Generative AI is assuming more critical roles in the backend by aiding coders, testers, and software developers. LLMs are a crucial element here and while they were initially developed to aid in language generation exercises, their versatility is now assisting developers in tasks such as code completion. By inputting the right prompts, software developers can generate purpose-specific codes quickly and efficiently.

Some of the ways in which generative AI is assisting developers are:

• Understanding and maintaining codes that were written by someone else
• Identifying suitable classes or code libraries for specific tasks
• Automating code consistency improvements through refactoring and style changes
• Suggesting simpler code alternatives and exploring alternative solutions to coding challenges
• Generating unit tests to reduce human errors and handle corner cases
• Translating code between languages for legacy migration
• Creating user stories and success criteria
• Accelerating debugging by quickly identifying coding mistakes
• Writing codes that go beyond templates to kickstart new tasks

As developers embrace generative AI models for various purposes, the potential of the technology is expanding the horizon for enterprises. However, popular and widely used LLMs and generative AI tools may soon prove inadequate for all functionalities of software development. As a result, enterprises will need tailor-made approaches and purpose-built layers on top of LLMs that offer able and holistic assistance to developers in their coding journeys. Technology vendors, like HCLSoftware, are finely poised to bring that cutting edge to the generative AI-driven coding revolution.

Taking Generative AI to the Next Level with Diverse Use Cases

HCLSoftware’s Intelligent Operations unit is constantly devising new products, and platforms to aid future-facing enterprises in their digitally enabled business and IT pursuits. Intelligent enterprise operations is the centerpiece of our initiatives, and our philosophy of combining dependable AI-fueled products with the innovations in generative AI is helping our customers get ahead of the curve. As leaders in the generative AI space, we are driving value across functions, for enterprises and their employees.

HCL BigFix AEX, a conversational AI platform leverages prompt engineering and finetuning methodologies to optimize generative AI and unlock its value at scale. Here are some of the generative AI-powered practical coding use cases of BigFix:

• Pre-programed with a layer over ChatGPT and aimed at optimizing desired results for OpenWhisk serverless functions, BigFix AEX enables users to generate codes with minimal natural language words. Compared to other products, this allows users to get outputs within minutes and with minimum intervention and iterations.
• This approach negates verbose, generic responses, reduces turnaround time and improves context and accuracy, resulting in increased developer/user efficiency and reduced costs.
• BigFix AEX allows users to refactor and add new functionalities to the codes at any time. Users can also add languages of their choice to generate the codes. This is aimed at improving ease of use and reach.
• BigFix AEX puts users at the center and makes the code generation process more conversational and outcome driven. By enabling multilingual counter questioning, It avoids standard and false responses, thereby preventing user confusion and hallucination. Ambiguity around perceptions can lead to wrong and delayed outcomes.
• BigFix AEX is a fully integrated platform that comes with out-of-the-box capabilities built on GPT knowledge. This resolves user problems faster and more efficiently. It is empowered with answers to a variety of user queries, thereby improving the conversation experience and expediting code generation.
• It also enables multilingual translation of SOPs and helps summarize texts easily. This improves end user experience and generates outcomes with a few clicks.

As LLMs revolutionize software development, there is a vast potential that is yet to be explored. And, at HCLSoftware, we are focused on unleashing that unexplored potential of generative AI with our future-thinking solutions. HCL BigFix AEX aims to intelligently automate tasks, foster creativity and shape a more sophisticated future for software development. As generative AI unlocks new frontiers, we will add our expertise to build new capabilities for enterprise.

To register for a 30-day free trial of BigFix AEX, click here.