Data is the fuel for artificial intelligence and creates new challenges for organizations seeking to benefit from generative AI (GenAI). Bringing these two technologies together to deliver relevant and valuable results that drive business growth is not easy, reflecting the challenges that customers face.
In this episode, you will learn how easily and frankly we talk about the role of generative AI in working with organizational data - it's like being a new employee who starts working in a new position, without having all the knowledge of experienced colleagues.
Just like workers learn on the job and find their way around the environment, generative AI models can also learn from an organization's data, allowing data analysts to start making it more specific to their organization.
Instead of training models from scratch, organizations can start with pre-trained models and fine-tune them with their own data, such as content, communication channels like Slack, data from Salesforce, or workflows like ServiceNow. The individual trained model and approach is now similar to a trained employee who makes a significant contribution to the business. Manuvir also explains that trained models are used at work, embedded in applications such as chatbots, and ready for large-scale queries.
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