Scaling AI to Generate Better and Different Outcomes

Om kurset

Barb Wixom reads MIT CISR's December 2021 research briefing, which she co-authored with Ida Someh and Robert Gregory. See the text version and related content at https://cisr.mit.edu/publication/2021_1201_ScalingAI_WixomSomehGregory. Abstract: Since 2019, MIT CISR has investigated fifty-two AI solutions to learn about AI scaling: growing the value created by both a core trained model and recontextualized adaptations of the model. This research has identified that scaling up happens when an AI solution moves from core model development to pilot to production, with increasing value creation. Further, scaling out happens when an AI model is trained using new data and new expertise, which are required for a new related application. This briefing describes both AI scaling dimensions within the context of an AI project journey at Pegasystems.