When an AI model "hallucinates," it deviates from the data given to it by changing or adding additional information not contained in it. While there are times this can be beneficial, Microsoft researchers have been putting large language models to the test to reduce instances where information is fabricated. Find out how we're creating solutions to measure, detect and mitigate the phenomenon as part of its efforts to develop AI in a safe, trustworthy and ethical way. https://msft.it/6049Y0m41
Very informative
That’s fantastic to hear, Microsoft! Reducing instances of AI hallucination is crucial for maintaining the integrity and reliability of AI systems. By creating solutions to measure, detect, and mitigate fabricated information, you are setting a high standard for AI development. This approach not only enhances the accuracy and trustworthiness of large language models but also ensures their safe and ethical use in various applications. Kudos to your researchers for their dedication to advancing AI technology in a responsible manner. Looking forward to seeing the positive impact of these innovations!
Another good breadcrumb along the discussion path on memory is this one: https://en.wikipedia.org/wiki/Fuzzy-trace_theory
It's a feature and not a bug, let it hallucinate, we all do it from time to time.
In some ways, this AI model mimics how our own brains piece together what we think is our memory of events: https://www.scientificamerican.com/article/perception-and-memory/
Our professor once explained AI hallucinations. I love it when academia presents industry topics.
Any preference: Florence or OpenCV?
I'll keep this in mind
Amazing and so proactive!
A excellent way to see the evolution very fast