When ChatGPT launched, concerns were raised that the advanced chatbot, which was trained on large amounts of text scraped from the internet, could have digested swathes of copyrighted content along the way. Regular search results are cheap to deliver by comparison, and Microsoft has pumped billions of dollars of investment into OpenAI to take LLMs to the next level. Or, more accurately, users are helping to build future LLMs, which justifies the high costs that OpenAI faces in providing AI-generated output to millions of users. And it’s providing the service for free, which, as the saying goes, makes users the product. But newer implementations such as Microsoft’s updated Bing search hint at a more dynamic future.Īs the FAQ’s show, OpenAI doesn’t hide the fact that it can review conversations between users and its advanced chatbot. At busy times, users can be force to wait if servers are at capacity – the LLM itself is relatively static and, in the case of OpenAI’s ChatGPT, doesn’t query the internet directly. OpenAI teamed up with Microsoft to create the Azure-hosted supercomputer used to determine the billions of model parameters that keep ChatGPT whirring away today. Advanced chatbots built using LLMs can take months of training and require tens of thousands of GPUs.

Issues may not surface immediately – a point made by David C and Paul J in the NCSC blog post warning of the potential risks of ChatGPT and LLMs.

ChatGPT and the downside of digital democracy

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