Many in the healthcare system rely on explicit reasoning, needing to show why and how they're informed.
Existing theories of cognition may prove useful in guiding towards a more unified system of LLM reasoning. Serena Williams stands on the baseline of the court, waiting for her opponent to send a wicked-fast ball over the net. The ball, once served, rockets over at 100 mph, tracing a parabolic arc through the air. In a reaction time of around 200 milliseconds, Williams computes the current trajectory of the ball.
To put ChatGPT's size into perspective, consider that the 2012 winner of the 'Large Scale Visual Recognition Challenge' was a neural network with 60 million parameters. In stark contrast, ChatGPT is powered by a network with 1.76 trillion parameters—30,000 times larger. When it comes to AI, size clearly does matter.While implicit reasoning can be very effective at performing complex tasks, it is not well-suited for healthcare environments where explicit reasoning is crucial.