machine learning

At the recent ITWC Digital Transformation Conference, Chris Mullens, Executive Director of the Workforce Institute, UKG, shared his thoughts on how AI and analytics are enabling organizations to pivot quickly, keep people safe and connected, and provide management with instant access to trends. Technology writer Steve Prentice was on hand and shared his thought on […]

The post Leveraging technology to build trust first appeared on IT World Canada.

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As companies look to expand their use of artificial intelligence (AI) and machine learning (ML) to keep up with the demands of their customers, they are facing hurdles getting these projects to production and ultimately deliver the desired results to t…

Read More IT decision-makers doubt current data architectures will meet future model inferencing requirements

The Center for Security and Emerging Technology has a new report: “Machine Learning and Cybersecurity: Hype and Reality.” Here’s the bottom line:

The report offers four conclusions:

  • Machine learning can help defenders more accurately detect and triage potential attacks. However, in many cases these technologies are elaborations on long-standing methods — not fundamentally new approaches — that bring new attack surfaces of their own.
  • A wide range of specific tasks could be fully or partially automated with the use of machine learning, including some forms of vulnerability discovery, deception, and attack disruption. But many of the most transformative of these possibilities still require significant machine learning breakthroughs.
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In a 6-3 ruling, the Supreme Court just narrowed the scope of the Computer Fraud and Abuse Act:

In a ruling delivered today, the court sided with Van Buren and overturned his 18-month conviction.

In a 37-page opinion written and delivered by Justice Amy Coney Barrett, the court explained that the “exceeds authorized access” language was, indeed, too broad.

Justice Barrett said the clause was effectively making criminals of most US citizens who ever used a work resource to perform unauthorized actions, such as updating a dating profile, checking sports scores, or paying bills at work…

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