Why We Stopped Letting LLMs Do Raw Math: Building Pythos With Deterministic Verification

Description and use

<p>Large Language Models are incredible at conceptual analogies, Socratic dialogue, and breaking down complex ideas. </p> <p>But when it comes to raw mathematics and physics derivations, <strong>they are notoriously unreliable calculators</strong>. </p> <p>They drop negative signs, fabricate intermediate arithmetic steps, and deliver confidently incorrect answers with total poise. In creative writing, a hallucination is a quirk; in mathematics and physics education, <strong>it completely derails a student's confidence and understanding.</strong></p> <p>To solve this, I built <strong><a href="h

Problem

<p>Large Language Models are incredible at conceptual analogies, Socratic dialogue, and breaking down complex ideas. </p> <p>But when it comes to raw mathematics and physics derivations, <strong>they are notoriously unreliable calculators</strong>. </p> <p>They drop negative signs, fabricate intermediate arithmetic steps, and deliver confidently incorrect answers with total poise. In creative writing, a hallucination is a quirk; in mathematics and physics education, <strong>it completely derails a student's confidence and understanding.</strong></p> <p>To solve this, I built <strong><a href="h

Outcome

<p>Large Language Models are incredible at conceptual analogies, Socratic dialogue, and breaking down complex ideas. </p> <p>But when it comes to raw mathematics and physics derivations, <strong>they are notoriously unreliable calculators</strong>. </p> <p>They drop negative signs, fabricate intermediate arithmetic steps, and deliver confidently incorrect answers with total poise. In creative writing, a hallucination is a quirk; in mathematics and physics education, <strong>it completely derails a student's confidence and understanding.</strong></p> <p>To solve this, I built <strong><a href="h

Evidence

Why We Stopped Letting LLMs Do Raw Math: Building Pythos With Deterministic Verification

Source