
Interactive topics discussed will be led by Rob Barton, CTO for Cisco Canada.
Join us as we discuss the transformative potential of AI, empowering cybersecurity professionals to stay ahead of cyber threats in the security landscape.
As cyber threats evolve, we are under ever-increasing pressure to protect critical data and maintain resilient networks. AI is now delivering unprecedented levels of threat and anomaly detection, enabling proactive defense against malware, phishing, and insider threats.
This session will explore the transformative effects of AI, particularly the implementation of domain-specific Language Models (LLMs), in enhancing security operations. We will explore the choice between various AI models—from open-source options like LLama2 to third-party offerings like GPT-4—and how custom solutions may be used for specific use cases. Lastly, we will emphasize the critical need for extensive, up-to-date domain-specific training data to ensure LLMs remain current and effective against the latest security trends and threats.
Agenda:
• 9:30 – 10:30 – Presentation
• 10:30 – 11:00 – Guided Discussion
Location: Cisco Office – Toronto
88 Queens Quay West, Suite 2900 – Toronto, Ontario M5J 0B8
When: Wednesday, April 10th, 2024 | 9:00am – 11:00am
Rob Barton Bio:
Rob Barton, P. Eng, is the CTO of Cisco Canada and is a Cisco Distinguished Engineer. Rob has worked in the IT industry for over 25 years, the last 23 of which have been with Cisco. Rob Graduated from the University of British Columbia with a degree in Engineering Physics. Rob is a successful author, with books published on Network Quality of Service (QoS), Wireless Communications, and IoT. Additionally, he has also co-authored many academic research papers and leads Cisco’s academic research partnership program. Rob also holds numerous patents in the areas of wireless communications, network security, cloud networking, IoT, and Machine Learning. His current areas of work include wireless communications of all types, IT/OT convergence, network automation, and AI/ML in networking systems.
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