30
60
30
30
60
55
55
60
National Life Group CISO expects more vulnerabilities in six months than in thirty years
National Life Group CISO Becky Palmer says agentic AI resolves four of five SOC investigations and urges AI-speed patching practices.
In a Help Net Security interview, National Life Group CISO Becky Palmer argues frontier AI will uncover more vulnerabilities in the next six months than in the last thirty years, compressing time from disclosure to weaponized exploit from weeks to hours. She reports agentic AI in her SOC resolves 4 of 5 investigations without human escalation, saving hours daily on enrichment and summarization. She also details compensating controls such as virtual patching, least-privilege restrictions, and heightened monitoring, plus procurement questions to separate working AI products from wrappers.
16
30
57
42
60
57
30
30
60
55
30
30
55
30
30
60
30
60
30
30
The Surprising Effectiveness of Approximate Value Iteration in Self-Play
Minimal approximate value iteration self-play learns more accurate value functions than AlphaZero in Connect Four and Hex while cutting training and inference costs.
The paper trains a minimal self-play implementation of Approximate Value Iteration (AVI) without MCTS and uses ground-truth oracles for exact evaluation in Connect Four, 7x7 Hex, and synthetic games. AVI learns more accurate value functions than AlphaZero, and its one-step-lookahead greedy policies remain competitive with MCTS-based policies at substantially lower training and inference cost. Preliminary experiments on Othello and 9x9 Go show AVI trains stably on larger games, suggesting simpler approaches have become increasingly practical with modern deep-learning tools.
35
45
57
55
55
60
55
57
57
55
57
60