Embracing the potential of generative AI
The launch of ChatGPT marked a significant moment in the world of technology, captivating both businesses and enthusiasts. It has ignited a fervor within organizations to explore this transformative technology and its vast possibilities. Simultaneously, a multitude of AI providers, ranging from established players to emerging startups, are offering a rapidly expanding array of solutions.
In a world witnessing an unprecedented pace of technological advancement, generative AI holds the promise of reshaping the way businesses operate and innovate. This cutting-edge technology has the potential to simplify operations, enhance efficiency, and drive innovation. However, it's crucial to acknowledge that we are still in the early stages of its adoption, and the degree of success may vary.
At Virtusa, we've consistently positioned ourselves at the forefront of technological innovation, dedicated to exploring, researching, and engineering innovative solutions for our clients. We approach generative AI with the same commitment to exploration, focusing on creating partnerships and solutions that deliver value to businesses.
Unlocking the potential of generative AI
The capabilities offered by pretrained foundation models, such as large language models (LLMs), represent a significant leap forward in contrast to traditional AI models. These pre-trained models eliminate the substantial time and effort typically required for training and fine-tuning traditional AI models. Furthermore, they offer developer-friendly interfaces that simplify understanding and usage, accelerating experimentation and solution development like never before.
Generative AI is here to stay, with transformative potential. By aligning the possibilities it offers with the drive for innovation, we can define the boundaries of what AI can achieve, making it a wise investment for the future of any enterprise.
Generative AI expedites solution development by bypassing several traditional AI training steps. However, data privacy, security, compliance, and legal concerns must be addressed.
Clients now face a rapidly evolving landscape of choices when considering generative AI adoption, with various LLMs available, each differing in capability, licensing, hosting, and cost. The decision-making process also involves considerations for fine-tuning and customizing model responses, as well as addressing data security and compliance concerns. Choosing orchestration frameworks and de-risking model adoption through AI assurance necessitate careful consideration.
A successful approach to embracing generative AI includes critical elements: ideation focused on what can be meaningful for the business, ROI analysis, measured experimentation, early discussion of adoption concerns, and mapping the adoption journey to existing transformation lifecycles.
To guide our clients on this journey, we've structured our offerings around four key areas:
- Business advisory
- Technology advisory
- Experimentation and build
- Operate and optimize