ChatGPT can respond to a question presented to it in natural language and is proving to be good at producing a human-like answer. But the answer is not always correct, and this is especially the case when the question involves quantitative data. In this respect ChatGPT is similar to most humans: we find it easy to write an essay but struggle to include correct facts and figures about the subject where these require us to do complicated calculations. Give us a pocket calculator, however, and we can do very much better. Is there a pocket calculator that ChatGPT could use?
Stephen Wolfram believes there is. In Wolfram|Alpha as the Way to Bring Computational Knowledge Superpowers to ChatGPT, he explains that Wolfram|Alpha is able to accept questions in natural language which it then converts into “precise, symbolic computational language [the Wolfram Language] on which it can apply its computational knowledge power” and then produce an answer in natural language. In other words, because ChatGPT communicates using natural language it is in principle able to use Wolfram|Alpha as its pocket calculator.
A possible next step, which Stephen Wolfram says has already started, is for ChatGPT to learn how to use Wolfram Language directly in the same way that humans do. This could enable ChatGPT to produce computational essays which bring together three elements: text to describe context and motivation; computer input in Wolfram Language for a precise specification of what is being talked about; and computer output for facts and results, often in graphical form. A key point here is that the Wolfram Language enables each piece of computer input to be short, not more than a line or two, and to be understandable both by the computer and by a human reading the essay.