Sat.Jun 04, 2016 - Fri.Jun 10, 2016

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How google helps 600,000 webmasters re-secure their hacked sites every year

Elie

Every year, close to 600,000 sites are hacked. Given the scale of the problem, notifying users to prevent harm and webmasters so they can clean up their sites is critical to combat hacking. This post looks at the effectiveness of the current warning strategies used by Google and their long-term impact.

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Lisa Sotto Interviewed: Are Law Firms Soft Targets for Hackers?

Hunton Privacy

In a recent video published by Mimesis Law, Lisa Sotto , chair of the firm’s Global Privacy and Cybersecurity practice , was interviewed during Mimesis Law’s Cy-Pher Executive Roundtable in New York. Sotto, along with several other privacy professionals, discussed the risks that law firms face in protecting their clients’ confidential information, as well as their own data.

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Technical debt: public sector at the forefront

CGI

Technical debt: public sector at the forefront. narmada.devarajan. Wed, 06/08/2016 - 02:48. Representing up to 40% of information systems volume, unused lines of source code, also known as “technical debt,” create higher operating costs for IT departments. The public sector in particular is struggling with this problem. Technical debt is an increasing burden on the IT systems of all organizations, regardless of size.

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Webinar on How to Discuss Cybersecurity with Your C-Suite and Board of Directors

Hunton Privacy

On May 19, 2016, Hunton & Williams LLP and The Advisory Board Company hosted a webinar on How to Discuss Cybersecurity with Your C-Suite and Board of Directors. Hunton partner Matthew Jenkins moderated the session, and speakers included partner Paul Tiao , member of the firm’s Global Technology and Privacy practice , and The Advisory Board Company’s Chief Information Security Officer and Senior Research Director.

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.