If the next AI winter comes, it will be because we couldn’t feed our models with enough data.
Data exists but it’s siloed and unreachable. This ruins models, particularly in banks. Anti-Money-Laundering false positive rates average 95%, fuelling $3Tn of financial crime a year.
Data scientists use Gensyn’s differentially private federated learning infrastructure to train models over networks of nodes: taking models to data, not data to models.
Gensyn’s uses transcend banks, for example in Reinsurance, Material Science and Health. We have pilots with a tier 1 bank and a global chemical firm, plus a diverse pipeline.