Examining mistakes gives students a chance to discuss misconceptions openly and find new approaches to solving problems.

The proof-of-concept could pave the way for a new class of AI debuggers, making language models more reliable for business-critical applications.

This same principle applies to education: If students never meet resistance from mistakes, they fail to develop the ...

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Rather than study how to use AI, students in this machine learning class work with the math that makes the AI work.