Mistaking Quantity for Quality in Tech and Life

About this episode

This episode discusses the trade-off between quantity and quality in AI-generated content.

Learn More about AI Field Day 8 here . 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: Guy Currier , Research Director and Analyst at The Futurum Group Barbara Roos , Founder and Principal Consultant at Trailhead Communications Dave Graham , Head of Marketing at MLCommons Hosts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠Tom Hollingsworth⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , Event Lead for Tech Field Day ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Alastair Cooke⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , Event Lead at Tech Field Day ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Stephen Foskett⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , President and Organizer of ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow the Tech…

People in this episode

Hosts: Stephen Foskett, Tom Hollingsworth, Alastair Cooke

Guests: Guy Currier, Barbara Roos, Dave Graham

Topics covered

• AI
• content quality
• Large Language Models
• human expertise
• technology

Keywords

• AI
• Large Language Models
• content generation
• quality vs quantity
• technology

Mentioned in this episode

Organizations: Tech Field Day, The Futurum Group, Trailhead Communications, MLCommons

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