BrainBlog for Boomi by Jason Bloomberg
When ChatGPT launched in late 2022, the world changed. Forever more, the history of business technology would divide into before generative AI (genAI) and after.
Suddenly, AI was powerful enough to accept natural language prompts as input and generate plausible natural language outputs. The creators of ChatGPT and other early large language models (LLMs) trained their systems on content from the Internet itself, giving these applications an immensely broad but inherently flawed basis for generating output.
GenAI is also the driving force behind AI agents – autonomous programs that leverage AI to gather information and take action, despite ongoing issues with the underlying technology.
Today, businesses are finally coming to terms with the genAI tradeoff: its enormous power to understand human prompts and return convincing answers despite its flaws.
Given the importance of genAI for building AI agents, it’s essential for organizations to gain a clear idea of what problems genAI is well-suited to solve to extract maximum business value from the technology as their deployments of agentic AI mature.
Click here to read the entire article.
Image courtesy of Boomi.
