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Recently, Google announced the launch of a new open-source AI model, DataGemma, aimed at addressing the 'hallucination' problem that large language models (LLMs) often encounter when handling statistical data. This hallucination phenomenon causes the model to potentially provide inaccurate answers to questions related to numbers and statistics. The release of the DataGemma model marks a significant advancement for Google in the field of AI. Image source note: Image generated by AI, image licensed by service provider Midjourney to reduce hallucinations during statistical queries.

Michael Jordan believes that current large models still need to improve in quantifying uncertainty and providing measures of certainty in predictions. Large models also lack a healthy economic incentive structure to trace and reward those who provide answers. Michael Jordan had two epiphanies in his career, one in statistics and the other in microeconomics, which influenced his expectations for large models. He believes that solving social problems requires considering issues from a systemic and collective perspective, not just enhancing individual models. Governments and foundations should not only support large corporations.

Artificial intelligence has generated over 15 billion images, raising ethical questions about creativity and originality. AI creates an average of 34 million images daily, primarily using tools like DALL-E2 and Adobe Firefly. While AI tools play a significant role in the creative field, whether the works they generate should be considered true creations warrants further discussion.