How to Train Your Podcasting AI to Sound Like You | Michael Katz
Oct 3, 2024
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Michael Katz, an AI expert specializing in helping podcasters, shares transformative insights on using AI to reflect individual voices. He emphasizes the crucial process of training AI to avoid generic outputs, ensuring authenticity in content creation. Katz discusses the true meaning of quality in AI products and the importance of maintaining a personal touch. He offers practical tips for navigating voice training, revealing that the journey involves continuous refinement, much like onboarding a new team member in your creative process.
Training AI to reflect your unique voice requires high-quality, recorded content and ongoing feedback to avoid generic outputs.
Managing expectations around the training duration of AI is essential, as it takes time and iteration to achieve authenticity and satisfaction.
Deep dives
Training AI for Authentic Representation
Training AI to function as a podcast assistant involves specific strategies that focus on authenticity and personal voice. It's essential to provide AI with high-quality, recorded content that accurately represents who you are and what you want to convey. For instance, using previous podcast episodes or other recorded materials allows the AI to learn your unique style and preferences more effectively than written formats. This approach enables podcasters to scale their content production while maintaining the authentic voice that resonates with their audience.
The Complexity of Quality in AI Outputs
Quality in AI-generated content is a nuanced concept that transcends simple definitions like grammar accuracy or fluidity. It's about ensuring that the output feels natural and human-like, avoiding common AI pitfalls that can make content feel generic. This involves being opinionated about what constitutes high-quality output and being willing to engage in a dialogue about preferences with the AI. It's important to actively provide feedback when the AI produces content, as consistent, honest input helps it learn and improve over time.
Expectation Management When Using AI Tools
Managing expectations around the time it takes to train AI tools is crucial for users, particularly those new to content creation. The time required for an AI to accurately reflect a person's voice can vary significantly based on the individual's prior experience and the specificity of their preferences. Just as with hiring and onboarding a new employee, training AI takes time, feedback, and iteration to achieve satisfactory results. Understanding that the process can be lengthy alleviates frustration and encourages users to engage deeply with the tool for better outcomes.
AI can be a game-changer for scaling your podcast, but it’s only going to work if you take the time to dial in your core message and train the AI to reflect your voice.
In this episode, AI expert Michael Katz returns to show you how to train AI to reflect your voice — not churn out the same generic content everyone else is creating. You’ll learn how to use podcasting AI to streamline your content creation without losing the unique tone and personality that makes your show stand out. So if you’re ready to harness AI to save time, reach more people, and keep your voice front and center, hit play and let’s make your business bingeworthy.
0:02 - How to Stop AI from Making You Sound Generic
1:56 - What Does Quality Really Mean in AI?
4:18 - Your Voice: The Catalyst for Meaningful Impact
7:10 - How to Train Your AI to Sound Like You
9:31 - Practical Tips for Keeping Your Voice *Your Voice* While Using AI