The Promise and Peril of AI that Creates
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Generative AI can produce new content (text, images, video, audio) after learning patterns from large datasets. Major examples include ChatGPT, DALL-E 2, Midjourney.
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Key architectures that power generative AI models include variational autoencoders, generative adversarial networks (GANs), and transformers.
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Large language models like GPT-4 are trained on massive text datasets to predict next words and understand language. Their parameters represent word relationships.
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Generative AI can sometimes "hallucinate" convincing but false information due to flaws in training data.
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Controversies around generative AI involve data sourcing, job loss fears, and potential for misuse to create scams, misinformation, nonconsensual porn, etc.