Approach
Kerberoasting Detections: A New Approach to a Decade-Old Challenge
Security experts have been talking about Kerberoasting for over a decade, yet this attack continues to evade typical defense methods. Why? It’s because existing detections rely on brittle heuristics and static rules, which don’t hold up for detecting potential attack patterns in highly variable Kerberos traffic. They frequently generate false positives or miss “low-and-slow” attacks…
Figma’s CEO on his new approach to AI
Tech event season is in full swing. This week, Stripe and Figma gathered thousands of people in downtown San Francisco for their respective conferences. I caught up with Figma CEO Dylan Field after his opening keynote at Config, where he announced the most significant product expansion in the company’s history. Below, you’ll find our chat…
Jim Zemlin on taking a ‘portfolio approach’ to Linux Foundation projects | TechCrunch
The Linux Foundation has become something of a misnomer through the years. It has extended far beyond its roots as the steward of the Linux kernel, emerging as a sprawling umbrella outfit for a thousand open source projects spanning cloud infrastructure, security, digital wallets, enterprise search, fintech, maps, and more. Last month, the OpenInfra Foundation…
AI lie detector: How HallOumi’s open-source approach to hallucination could unlock enterprise AI adoption
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More In the race to deploy enterprise AI, one obstacle consistently blocks the path: hallucinations. These fabricated responses from AI systems have caused everything from legal sanctions for attorneys to companies being forced to honor fictitious policies. …
New training approach could help AI agents perform better in uncertain conditions
A home robot trained to perform household tasks in a factory may fail to effectively scrub the sink or take out the trash when deployed in a user’s kitchen, since this new environment differs from its training space. To avoid this, engineers often try to match the simulated training environment as closely as possible with…
This AI Paper from UC Berkeley Introduces a Data-Efficient Approach to Long Chain-of-Thought Reasoning for Large Language Models
Large language models (LLMs) process extensive datasets to generate coherent outputs, focusing on refining chain-of-thought (CoT) reasoning. This methodology enables models to break down intricate problems into sequential steps, closely emulating human-like logical reasoning. Generating structured reasoning responses has been a major challenge, often requiring extensive computational resources and large-scale datasets to achieve optimal performance….