I’s strength lies in its predictive prowess. Fed enough data, the conventional thinking goes, a machine learning algorithm can predict just about anything — for example, which word will appear next in a sentence. Given that potential, it’s not surprising that enterprising investment firms have looked to leverage AI to inform their decision-making.
There’s certainly plenty of data that one might use to train an AI-powered due diligence or investment recommendation tool, including sources like LinkedIn, PitchBook, Crunchbase, Owler and other third-party data marketplaces. With it, AI-driven financial research platforms claim to be able to predict the ability of a startup to attract investments, and there might be some truth to this. One study of hedge fund performance found that AI-driven funds generated higher average monthly returns over a 15-year period than their human-guided counterparts.
Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.






