Now that AI has enabled us to have an unlimited amount of content, generated on demand and instantly, we find ourselves questioning the quality of the output. This episode of the Tech Field Day podcast, recorded prior to AI Field Day by delegates Barbara Roos, Guy Currier, Dave Graham, and Stephen Foskett, considers this common trade-off. Large Language Models are fundamentally personal and responsive, delivering an answer that is statistically matched to your query. This can lead users astray, as a chatbot confidently answers every question regardless of insight. These systems are best when paired with human domain expertise and fed quality data, but they are often starved of context.
Panelists
Barbara Roos is the founder of Trailhead Communications, where she helps organizations navigate the human side of AI adoption.
Dave Graham is the Director of Marketing for MLCommons, an industry non-profit focused on AI for everyone.
Chief Analyst at Visible Impact and Research Director in the Ecosystems, Channels, & Marketplaces practice at The Futurum Group, specializing in AI, DevOps–cloud-native, CPUs-GPUs-xPUs, enterprise applications, and cloud.
Stephen is the President of the Tech Field Day business unit for The Futurum Group and focuses on AI, edge, and cloud