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Across diverse digital mediums, generative AI will expand creative frontiers and accelerate workflows. These expansions will amplify human creativity and unlock new sources of innovation while triggering important questions about data ethics, attribution, and copyright. With each leap in foundation model prowess, the horizons for generative AI applications broaden. To manage these risks, scalable oversight

Multimodal AI uses multiple data types like text, audio and images to create a more nuanced understanding of a situation. This is similar to how humans learn by combining visual, sound and touch inputs to perceive a more holistic picture of reality. Multimodal AI models typically have input modules (for ingesting and processing) and a

AI is no longer incarcerated to large firms. Using ML tools, small ventures can better serve customers, increase productivity, and make better decisions. AI helps automate and streamline repetitive tasks, which enables employees to work on more strategic projects. It can also help with demand forecasting, allowing businesses to optimize inventory management and deliver personalized