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Our products are used to:

_reduce the uncertainty of Machine Learning models,

_prioritize enterprise data efforts,

_support experts in the ML loop,

_improve the quality of ML models, especially in multi-class settings with complex ontologies,

_reduce data footprint and compactify ML models so as to be used by the Internet of Things applications,

_improve gaming experience via more challenging and realistic AI in games,

_create intelligent advisory systems from pre-compiled building blocks.

Sebastian Stawicki Head of ML Operations

A programmer and data wrangler, whose passion for computers originated from playing games on Atari 65XE, Amiga 600 and PC. An enthusiast of the Python programming language, and modern data collection and processing technologies. His academic interests include Data Mining, Knowledge Discovery and Machine Learning, with particular emphasis on Rough Sets. In professional life he took part in several projects, either commercial or R&D, related to such areas as web applications, databases, methane concentration threats in coal mines, recruitment industry or video games. His other past or current activities involve juggling, kickboxing, judo, chess, motorcycles, gliders, handcrafting, and dancing.

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