AI Training and Focusing on the Long Game

AI has a Cold Start Problem: before AI can be effectively used on your assets it needs to understand what is important to you about your assets.

In this session, we’ll focus on the emerging art of utilizing AI in real-world scenarios and discuss the three “buckets” that many different types of AI can be sorted into: Generative, Assistive, and Analytical.

AI training is iterative and may not save a lot of time up-front, but you ARE getting more effective metadata tagging from the process through people-centered quality control.

The allure of AI as a “magic bullet” can get the best of us.

• How do we manage or remediate AI’s glut of output?
• What is the best way to avoid these time-intensive pitfalls of overzealous AI engines?

And finally, when should we be using AI for all of these processes? When is it appropriate to give AI the lead and let it create, correct, and identify within our asset libraries?

A link to the recording will be shared post-webinar with all registrants.