Author: Maulik Shah

According to a McKinsey survey, more than 77 percent of CIOs are considering a mobile-first approach for digital transformation. The next generation of customers and employees will be digital-native and have greater familiarity with touch screen devices. Moreover, the business case for mobile apps continues to expand as 82 percent of American adults own a smartphone as of 2023, up from just 35 percent in 2011. Mobile apps are now a necessity for businesses to attract new customers and retain employees.

Regardless of the size and scope of your project, following this mobile development process will help you launch your mobile apps successfully.

While Generative AI is not a new technology, the launch of Generative AI solutions like ChatGPT, Bard, and Midjourney has spiked interest in leveraging Generative AI applications for enterprise and industry-specific use cases. However, the AI models leveraged by these Generative AI applications are trained for general-purpose utility and lack business- and industry-specific knowledge. Companies trying to capitalize on the current trends and transform their business through their emerging AI capabilities are required to take a hybrid approach with their AI strategy to partly leverage existing solutions for general-purpose activities and create their own custom AI solutions specific to their business needs.

For companies to create custom Generative AI solutions, they will need to prepare their own language models, trained with proprietary business data. The custom Large Language Models (LLMs) will help companies unleash Generative AI capabilities for their business and provide them a competitive edge.