The author expresses concerns about the concentration of power this represents and the potential decline in the quality of the web as these models starve the human engines that create knowledge. The article suggests that the future of AI may involve models that express curiosity and solicit information, potentially leading to a shift from public knowledge to private accumulation. It concludes by advocating for AI companies to behave more responsibly, attributing sources and encouraging human knowledge production.
Key takeaways:
- Large language models (LLMs) like OpenAI's ChatGPT and Google's Bard are consuming vast amounts of web data, potentially leading to a decline in the quality of the web as they siphon traffic from sites that generate the knowledge they rely on.
- These LLMs are becoming increasingly adept at synthesizing and consolidating human knowledge, potentially leading to a future where they can generate their own knowledge, either through synthetic data or by actively soliciting information from humans.
- The concentration of power in these AI models is concerning, as they aim to ingest all human knowledge and store it in their neural networks, potentially leading to a decline in public knowledge repositories like Stack Overflow or Wikipedia.
- There is a call for AI companies to behave more responsibly, by attributing the sources of their information and encouraging the continued production of human knowledge, rather than treating humans as mere stepping stones for their own development.