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AI Eye: Is AI content cannibalization a problem? Are Threads a loss leader for AI data?

AI Eye: Is AI content cannibalization a problem? Are Threads a loss leader for AI data?

– The popularity of ChatGPT is declining, with decreased Google searches and web traffic to OpenAI’s website.

– Users of GPT-4 have noticed that the model seems less intelligent but faster, possibly due to OpenAI breaking it up into smaller models.

– AI cannibalism is a potential factor in the decline of AI model quality. Synthetic data generated by AI is being used to train new models, leading to a negative feedback loop and decreased coherence and quality in the output.

– OpenAI’s recent paper highlights the issue of Model Autophagy Disorder (MAD), where future generative models progressively decrease in quality and diversity without enough fresh real data.

– Keeping humans in the loop and prioritizing human content for AI models could help address this issue.

– Threads, a Twitter clone by Mark Zuckerberg, may be a strategy to generate more text-based content for Meta’s AI models.

– Elon Musk has taken steps to prevent AI training on Twitter data in the future.

– Hindu chatbots trained on religious texts have been giving controversial advice, highlighting the dangers of training AI on religious texts without proper context.

– There are differing opinions on the risks and benefits of AI. Some believe that superintelligent AI could pose a threat to humanity, while others argue that the risks can be managed and that AI will bring massive benefits.

– OpenAI’s GPT-4 has a new code interpreter that allows it to generate and run code on demand, opening up various use cases.

– Other AI news includes AI’s high scores in creativity on standardized tests, copyright violation lawsuits against OpenAI and Meta, and the availability of Anthropic’s ChatGPT competitor Claude 2.

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