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What is Artificial General Intelligence (AGI)? And how can it help Government Intelligence Analysts and LEAs? Online webinar: Matthew Lucas, PhD Computer Science - TeleStrategies ISS World Free for Law Enforcement, the government intelligence community, private enterprise cyber security managers and ISS vendors. Pre-registration with your government or corporate issued email address is required. |
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What is Artificial General Intelligence (AGI)? And how can it help Government Intelligence Analysts and LEAs? Today’s AI systems are excellent at image recognition, classifying unstructured data, natural language processing, document summarization, and more – all of which is fantastic for Government Intelligence Analysts and LEAs because ISS vendors can incorporate these capabilities into their products to automate tasks which otherwise take enormous time and manpower. However, today’s AI systems completely fail at even the simplest of problem solving or logic-based tasks such as correlating data across CDR and OSINT datasets, finding terrorists and criminal behavior patterns or deductive reasoning to narrow investigation efforts. Consider sending a message to an AI enhanced dancing robot to go grocery shopping, here is the store, and shopping list. The robot hypothetically answers, "I only dance and what is a grocery shopping list?" Artificial General Intelligence (AGI) is the latest evolution of AI. First, Machine Learning AI, then Generative AI and now enter AGI. This latest generation of AGI gives machines the ability to think or act (Humanoid Robot) to understand or learn any intellectual task as human beings can. The latest AGI models from Silicon Valley now incorporate “reasoning” capabilities that enable AI platforms to handle multi-step analytics and automate decision-based workflows. While at an early stage, AGI models could prove to be a game-changer for LEA/IAs. This webinar will provide background on AGI capabilities and look at how these models might be used by intelligence analysts and criminal investigators to automate laborious investigations and “find the connections” that exist within their datasets.
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