Bankloch

Generative AI   has revolutionized the way we create and interact with digital content. Since the launch of Dall-E in July 2022 and ChatGPT in November 2022, the field has seen unprecedented growth. This technology, initially popularized by OpenAI’s ChatGPT, has now been embraced by major tech players like Microsoft and Google, as well as a plethora of innovative startups. These advancements offer solutions for generating a diverse range of outputs including text, images, video, audio, and other media from simple prompts. The consumer now has a vast array of options based on their specific   output needs and use cases . From generic, large-scale, multi-modal models like OpenAI’s ChatGPT and Google’s Bard to specialized solutions tailored for specific use cases and sectors like finance and legal advice, the choices are vast and varied. For instance, in the financial sector, tools like BloombergGPT ( https://www.bloomberg.com/ ), FinGPT ( https://fin-gpt.org/ ), StockGPT ( https://www.as

AI is a   hot topic   and numerous articles are published stating that financial service companies not adopting AI today risk becoming obsolete tomorrow. However, as with many hypes, the industry’s adoption of AI may not proceed as rapidly as commonly predicted. Just as an example, for the past two decades, experts have been forecasting the obsolescence of banks using old legacy mainframe systems. Yet, even after 20 years, many banks still rely on critical core banking applications built on legacy mainframe technologies, and these banks remain as strong (if not stronger) as they were two decades ago. That being said, AI is here to stay, and a gradual adoption is essential. As discussed in my blog, " The Right Fit: Assessing Business Value before Adopting AI/ML " ( https://bankloch.blogspot.com/2023/10/the-right-fit-assessing-business-value.html ), it is crucial for banks to choose their AI battles wisely, rather than implementing AI for the sake of it. Creating a comprehensiv