My takeaways from these chapters are that GPT-4 is a remarkable conversationalist, it edits better than creates, provides language that suggests it has a real grasp on causality, and that it appears to exhibit logical reasoning. When asked, it can give an idea of what a patient may be thinking. To Peter’s credit, he aptly presents both sides of whether GPT-4 actually understands; the “stochastic parrot” versus a more advanced form of machine intelligence and comprehension than we have previously seen. Taking us through a poem that his son wrote, and that GPT-4 rewrites, is quite informative, as is the French phrase that the LLM interprets with remarkable cultural insight.
This issue about “understanding” is a lot like the explainability issue of AI. If it works well, it may not really matter what is the level of the machine’s capability.