John's Covid-19, politics and futurism blog

This is the second of two posts on Generative AI. Late last year (November), OpenAI released ChatGPT to the public. However, it took a few months for the internet at large to catch on and realise the potential of this new tool. The trend started to take off in December, and by February everyone was talking about it. ChatGPT is an example of a "Generative AI". To recapitulate, let's see what this means. For convenience, let's call AIs that are not generative, "regular" AIs. Regular or "Narrow" AI (Artificial Intelligence): Regular AI, often referred to as "narrow" or "specific" AI, focuses on building systems that can perform specific tasks or solve specific problems. These AI systems are designed to operate within predefined boundaries and excel at specialised tasks. For example, a regular AI could be created to classify images, play chess, or process natural language. Another example is the AI that chooses your words in predict

This is the first of two posts on Generative AI. Late last year (November), OpenAI released ChatGPT to the public. However, it took a few months for the internet at large to catch on and realise the potential of this new tool. The trend started to take off in December, and by February everyone was talking about it. Well, what is ChatGPT? ChatGPT is an LLM, or Large Language Model, released by the company OpenAI, founded in 2015. A language model is a program that has been trained on a huge amount of text data, like books, articles, and websites. It learns patterns and relationships between words, so it can predict what words or phrases are likely to come next in a sentence. We see an example of this in predictive text in cellular telephone chat applications. The "large" part means that the model has been trained on a massive amount of data, which helps it become even better at understanding and generating human-like text. It's like having read millions of books and articl