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Paul Kassianik
Paul Kassianik
AI Safety and Security Researcher
Security Business Group
Paul Kassianik is an AI Safety and Security researcher at Cisco, working on securing large language models. He received his B.A. in Applied Mathematics with a focus in Computer Science from University of California, Berkeley. Before joining Cisco, Paul has been a research engineer at Salesforce, researching and developing Code Generation large language models and industrial time-series analysis.
Articles
Explore a new frontier in LLM quality and speed. Cisco’s Foundation-Sec model delivers high-performance AI summaries for Splunk Security Operations workflows.
The performance of DeepSeek models has made a clear impact, but are these models safe and secure? We use algorithmic AI vulnerability testing to find out.
The automated Tree of Attacks with pruning (TAP) method can jailbreak advanced language models like GPT-4 and Llama-2 in minutes, so they make harmful content.