Generative Artificial Intelligence (AI) is still a hot area in the consumer goods industry, but it has garnered a lot of attention as a technology with huge potential and various applications. We also collect some questions, concerns and doubts.
We tapped into expert voices and research from Coresight, Microsoft, and Gartner to better understand how generative AI is transforming different areas across industries.
The consensus clearly points to significant progress in this area over the next few years, but sources also agree that the way forward must be met with careful, small strategic steps. .
“Generative AI requires large amounts of data to train AI models and can damage brand reputation, resulting in biased and insensitive content based on the data trained. Solutions, Metaverse, Web 3.0, NFT, AI, OpenAI, ChatGPT, Gaming, Commerce.
Editor’s Note: Subroto Mukherjee’s contributions are his own views, based on his personal experience, research, and learning, and do not necessarily reflect those of his company.
What is generative AI?
Early iterations of artificial intelligence exist from the 1950sSo what is the difference between general AI and generative AI?
Chiefly, generative AI techniques like ChatGPT use deep learning neural networks that mimic brain cells to generate optimal text from input, according to John Harmon, senior analyst at Coresight Research.
Other AI-powered techniques, such as machine learning, ingest data sets, identify relationships between them, and make predictions.
“Many of these are quantitative projections/predictions, and the AI element allows the model to evolve and remain accurate over time,” says Harmon.
