By Marc Trup – Director and Founder, Saxon Investments and Azik Capital
Think of an AI model as a boxer and its training data as the trainer holding up pads.
Over time, the boxer learns to recognise patterns: when the left pad rises, throw a left jab; when the right pad moves, throw a cross. The boxer isnβt thinking about π°π‘π²-they’ve simply learned, through repetition, that certain movements mean certain actions.
Now imagine the trainer suddenly changes things. They lift the pad higher, lower, or at a different angle. The boxer hesitates, throws the wrong punch, or misses entirely. Itβs not that the boxer has forgotten how to punch-itβs that the pattern no longer matches what theyβve seen before.
AI works the same way. When itβs trained on many examples, it learns to spot the patterns that link input (the text it reads) to output (the answers it gives). But if the wording, structure, or style of new data is very different from what itβs seen, like an unexpected pad position, it may respond less accurately or pause while it βfigures outβ whatβs happening.
With time (or retraining), the boxer learns to adapt to the new positions-and the AI learns to recognise new patterns too. Both are improving their ability to π ππ§ππ«ππ₯π’π¬π-to respond correctly even when the pattern changes a bit.
ππ©π©π₯π²π’π§π ππ‘π’π¬ ππ¨ ππ¨π¦π©π₯ππ± π₯πππ¬ππ¬
When an AI extracts information from leases, itβs using the same kind of pattern recognition. If every lease followed the same layout-the same βpad positionsβ-it could identify rent reviews, renewal clauses, and break dates with ease. But in reality, leases vary in style, age, and wording. One might say, βRent shall be reviewed every fifth anniversary,β while another buries that same idea deep inside a schedule or a definition. To the AI, thatβs like a trainer suddenly moving the pad to a new position-the pattern looks unfamiliar. The result may be a missed or delayed βpunchβ-a clause that isnβt recognised or is interpreted incorrectly. As the model encounters more of these variations, it learns to adjust, improving its accuracy in handling even the most complex and unconventional leases.
