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TechSpective Podcast Episode 139
In the latest TechSpective Podcast, I had the pleasure of speaking with Wilson Tang, a Machine Learning Engineer on Adobe’s threat hunting team. Our conversation delved into one of the most exciting and critical areas of technology today—how artificial intelligence (AI) and machine learning (ML) are reshaping cybersecurity.
Wilson brings a unique perspective, having transitioned from traditional software engineering to focus on ML applications in security. Throughout the podcast, we explored how Adobe leverages ML to detect and mitigate threats that traditional, rules-based methods might miss. One standout example is Adobe’s use of anomaly detection in identifying suspicious logins by establishing baseline behaviors for each user—an approach far more scalable and flexible than older security techniques.
We also touch on the growing significance of large language models (LLMs), like ChatGPT, in cybersecurity. While these models have generated a lot of hype, Wilson emphasizes their best use cases, such as process improvements and AI assistance, while warning against over-relying on them for complex decision-making tasks. The conversation also highlights the environmental challenges posed by AI’s energy consumption, a hot topic in tech circles today.
For anyone curious about the future of cybersecurity, AI, and ML, this episode offers valuable insights from someone at the forefront of this evolving field. We discuss not just what’s happening now but also where technology is headed—including the potential game-changing role of quantum computing in the years to come.
Tune in to this episode of the TechSpective podcast to hear how Adobe is using cutting-edge ML technologies to stay ahead of cyber threats, and what Wilson sees on the horizon for AI in cybersecurity. Whether you’re a security professional or just interested in the intersection of AI and cybersecurity, this episode is a must-listen. The podcast itself is audio-only, but the video of our conversation is also available on YouTube if you prefer:
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