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The article discusses the importance of data readiness for AI-driven innovation, highlighting three key indicators for assessing data readiness. Despite the high adoption of AI by organizations, many face challenges during implementation, with a significant gap between perceived data readiness and actual data quality. The need for a more rigorous data readiness assessment before embarking on AI projects is emphasized.
One of the indicators for data readiness is centralized data, crucial for successful AI implementation. The article mentions Microsoft Copilot as an example, recommending the consolidation of data into Microsoft 365 for improved accessibility and data management. For projects where centralizing data is not feasible, the process of harvesting data from multiple sources and preparing it for AI is essential.
Isomorphic Labs, the AI drug discovery platform that was spun out of Google's DeepMind in 2021, has raised external capital for the first time. The $600
How to level up your teaching with AI. Discover how to use clones and GPTs in your classroom—personalized AI teaching is the future.
Trump's Third Term? AI already knows how this can be done. A study shows how OpenAI, Grok, DeepSeek & Google outline ways to dismantle U.S. democracy.
Sam Altman today revealed that OpenAI will release an open weight artificial intelligence model in the coming months. "We are excited to release a powerful new open-weight language model with reasoning in the coming months," Altman wrote on X.
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