Hi everyone,
Much discussion surrounds AI’s role in assisting testing. I’m interested in understanding more about effective methods for rigorously testing AI models and systems.
For further context, I’m especially focused on AI vision systems, but please don’t feel limited by this. I’m eager to learn from all experiences and knowledge you can share.
Here are a few questions to get the conversation started:
What experiences do you have with testing AI?
Have you encountered any unique challenges or successes?
What tools, techniques, and approaches have you used?
Are there any specific frameworks or methodologies that you recommend?
Have you come across any interesting articles, blogs, vlogs, etc., on this subject?
Please share links and resources that you found helpful!
Additional Questions:
How do you ensure the reliability and accuracy of AI models during testing?
What strategies do you use to handle biases in AI systems?
Can you share any case studies or examples of successful AI testing projects?
What are the best practices for maintaining and updating AI models post-deployment?
Looking forward to hearing your insights and experiences!