683: Contextual A.I. for Adapting to Adversaries, with Dr. Matar Haller
May 30, 2023
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Dr. Matar Haller discusses contextual AI in identifying malicious user-generated content online, monitoring live-streamed content, and utilizing a 'database of evil'. Topics also include leadership opportunities for women in STEM, Israel's R&D edge for AI, and the challenges of real-time content moderation on social media platforms.
Utilizing contextual AI to identify and flag malicious content online.
Implementing small moderation models for real-time monitoring of live-streamed harmful material.
Leveraging a versatile tech stack and neural science insights for effective content moderation processes.
Deep dives
Content Moderation and Threat Intelligence in Online Platforms
ActiveFence provides AI-enhanced tools for content moderation and threat intelligence on online platforms with user-generated content. Through contextual AI, they detect various forms of harmful content, such as videos, images, and text, in multiple languages and for different violations. The platform's database of violative content assists in real-time detection and adaptation to adversarial tactics, ensuring user safety and compliance with evolving regulations.
Real-Time Content Detection in Live Streaming
ActiveFence tackles the challenge of monitoring harmful content in real-time live streams by deploying small content moderation models on edge devices and sampling data on servers. Surrounding information like comments, user interactions, and behavioral patterns enhances the risk assessment of live content. The platform leverages graphical data modeling to analyze relationships and historical context, improving the accuracy of identifying harmful content in dynamic streaming scenarios.
Technological Framework and Data Science Expertise
ActiveFence employs a versatile technological stack, including Python, Node, TypeScript, and Kubernetes, for high-throughput, low-latency model deployment. Their data-driven approach, informed by neural science insights, enhances decision-making processes in content moderation. Dr. Mattar's background in neuroscience and successful transition to industrial data science through programs like Insight Data Science Fellowship underline her depth of expertise in backend engineering and data analytics.
Transition to Industry Through Insight Data Science Program
Transitioning to industry after a strong academic background in machine learning and data science was facilitated by enrolling in the Insight Data Science Program. This program helped individuals with existing skills frame their expertise in an industry context, providing insights into startup operations, job opportunities, best practices, and practical project development. Participants had a short timeframe to create impactful projects for potential employers, bridging the gap between academic knowledge and industry application.
Advancements in Brain-Computer Interfaces and Neuroscience
The discussion touched upon the evolution of brain-computer interfaces, from invasive techniques in neurological conditions like Parkinson's to non-invasive methods such as Transcranial Magnetic Stimulation for psychiatric disorders. The conversation highlighted the potential for future advancements, including Elon Musk's Neuralink project aiming for non-invasive brain-computer interfaces. The episode emphasized the complexities of neural stimulation, individualized frequency responses, and the impact on treatments, showcasing the intersection of neuroscience and technological innovation.
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 “database of evil” can help resolve the multiple challenges of blocking dangerous content across a range of media, even those that are live-streamed.
This episode is brought to you by Posit, the open-source data science company, by Anaconda, the world's most popular Python distribution, and by WithFeeling.ai, the company bringing humanity into AI. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.
In this episode you will learn: • How ActiveFence helps its customers to moderate platform content [05:36] • How ActiveFence finds extreme social media users trying to evade detection [16:32] • How to monitor live-streaming content and analyze it for dangerous material [29:13] • The technologies ActiveFence uses to run its platform [35:54] • Matar’s experience of the Insight Fellows Program (Data Science Fellowship) [40:28] • Leadership opportunities for women in STEM [1:00:41] • Israel’s R&D edge for AI [1:13:19]