Image Analysis with Artificial Intelligence and GPTs
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In this stream, Charles G., a co-founder of GTK Cyber with over 20 years of experience in cyber, data science, and machine learning, demonstrates how to use GPT and large language models (LLMs) for image analysis. Charles discusses his career background, which includes roles in the intelligence community, major banks, and running his own startup, before showcasing practical applications of AI, particularly in analyzing images to extract data, such as identifying vehicles from security camera footage. He explains how these AI tools can be used to automate tasks by transforming image analysis results into structured data like JSON, and integrates Python scripting to ensure consistent outputs for database insertion. Charles highlights both the power and challenges of using AI in security contexts, and answers questions from viewers about practical AI implementations, while also plugging his upcoming courses and events on data science and AI security.
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Recorded:
Sep 27 2024
00:00 - Introduction: Welcoming viewers and introducing Charles G., co-founder of GTK Cyber
01:20 - Charles introduces himself: Background in cyber, data science, and his work history
02:30 - Charles on the impact of GPT: How GPT entered the scene and its explosion in popularity
04:00 - Introducing AI image analysis: Use cases in security and beyond
06:15 - Smoke and mirrors in AI: Breaking down misconceptions and practical use cases
07:30 - Setting up the demo: Using GPT to analyze images and practical examples
10:00 - Demo: Image analysis in action with GPT and extracting meaningful data
12:45 - JSON output explanation: Structured data for practical AI application
14:00 - Addressing the need for consistent AI outputs: Challenges in automation
15:30 - Transition to Python: Using scripts to ensure consistency in AI-generated results
18:00 - Technical deep dive: Base64 encoding, image formats, and Python integration
20:30 - Demo of a second car image: AI accuracy in extracting vehicle details
22:30 - Broader use cases: Security cameras, tracking vehicles, and database population
25:00 - AI’s potential: Beyond image recognition, including invoice processing use cases
27:45 - Challenges of AI hallucination: Implications for security and reliability
29:15 - Risks of AI misuse: Guardrails needed to prevent dangerous outcomes
31:00 - AI security discussion: The future of AI security and the need for better controls
34:00 - Real-world risks: Example of attacking AI models in corporate settings
36:00 - Questions from chat: AI security and future use cases in the workplace
38:00 - Charles plugs upcoming events and courses: Black Hat, virtual trainings, and more
41:00 - Closing thoughts: AI security as an emerging field and a call to action for learning
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