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b"Monitoring malicious, user-generated content; contextual AI; adapting to novel evasion attempts: Matar Haller speaks to Jon Krohn about the challenges of identifying, analyzing and flagging malicious information online. In this episode, Matar explains how contextual AI and a \\u201cdatabase of evil\\u201d can help resolve the multiple challenges of blocking dangerous content across a range of media, even those that are live-streamed.\\n\\nThis episode is brought to you by Posit, the open-source data science company (posit.co), by Anaconda, the world's most popular Python distribution (superdatascience.com/anaconda), and by https://WithFeeling.ai, the company bringing humanity into AI. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.\\n\\nIn this episode you will learn:\\n\\u2022 How ActiveFence helps its customers to moderate platform content [05:36]\\n\\u2022 How ActiveFence finds extreme social media users trying to evade detection [16:32]\\n\\u2022 How to monitor live-streaming content and analyze it for dangerous material [29:13]\\n\\u2022 The technologies ActiveFence uses to run its platform [35:54]\\n\\u2022 Matar\\u2019s experience of the Insight Fellows Program (Data Science Fellowship) [40:28]\\n\\u2022 Leadership opportunities for women in STEM [1:00:41]\\n\\u2022 Israel\\u2019s R&D edge for AI [1:13:19]\\n\\nAdditional materials: www.superdatascience.com/683"