Microsoft’s Post

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

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

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

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

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

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

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