Introduction
Artificial intelligence (AI) adoption has more than doubled over the past five years, and investment in AI is gathering pace. That said, machine learning, an AI technique, was largely limited to observe and classify patterns in content with the help of predictive models. Now text-based machine learning models rely on self-supervised learning, which involves feeding a model a humungous amounts of text to enable it to generate predictions. Known as Generative AI, it describes algorithms and chatbot models such as ChatGPT that are multimodal, implying that they can be used not only to create or generate new content but also audio, code, images, text, simulations, and videos.
Individuals and smaller companies across the world appear to be heartily embracing these new AI-powered tools to write blogs, reviews, resumes, product descriptions, make short films, create images, make videos, generate software code, provide templates for marketing campaigns, and even analyze broad economic trends. However, the models will also need a fair bit of customisation and fine-tuning besides addressing security and privacy challenges to stay up-to-date when used by companies. Regardless, Generative AI is being discussed in global boardrooms--17% of CEOs in the January-March quarter of this calendar year, spurred by the release of ChatGPT and the discussions around its potential use cases. Experts at this event will discuss how to make the best use of AI and Generative AI models even as they discuss how to address the challenges and disruption that the exponential growth of these new technologies is posing.