gensai.aiAn algorithm is a precise sequence of instructions a machine executes to solve a problem: sorting data, computing a route, recommending content. In AI, learning algorithms adjust a model from examples rather than applying hand-written rules.
In practice at Gensai
Gensai picks the approach to fit the need: simple rules when they suffice, machine learning when complexity demands it.
Rules or learning: how to choose?
Hand-written rules are enough when the logic is stable and easy to explain: calculating a discount, routing requests by keyword, checking a format. Machine learning becomes useful when cases are too numerous or too varied to be described one by one: recognising an image, understanding a freely worded request, detecting an anomaly.
Common mistake
Believing an algorithm is neutral by nature. A trained model reproduces the biases of its training data: its results must be checked on real cases, especially when it influences a decision about people.
Same theme
Definition written with AI assistance, checked by Sébastien Lecocq, co-founder of Gensai.
Going beyond the definition?
From concept to project: Gensai builds custom, sovereign, GDPR-compliant AI solutions.
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