Third Wave AI Blogs
The latest stories on Cybersecurity, AI, and everything in between from MixMode
Cybersecurity is a battlefield where innovation is paramount. Artificial intelligence (AI) has emerged as a potential game-changer, promising to revolutionize threat detection and response. Vendors have made bold claims, promising their AI-powered solutions will provide unparalleled capabilities, eliminate false positives, and autonomously defend against even the most sophisticated attacks.
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If you’ve followed this blog series, you already know that Artificial intelligence (AI) has become a ubiquitous term, holding immense promise across various industries. Cybersecurity is no exception, with AI poised to revolutionize how organizations defend their data and systems against malicious activity. However, a crucial question remains: Are cybersecurity teams effectively harnessing AI’s potential for maximum security impact?
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If you’ve been following along in this series, you already know that Artificial Intelligence (AI) has emerged as a powerful tool for organizations to strengthen their cybersecurity defenses. But how is AI being used in cybersecurity today, and what are its key benefits?
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We have now reached the Third wave of AI: Contextual Reasoning. This revolutionary approach, pioneered by MixMode in cybersecurity, utilizes self-supervised and explainable AI to independently learn and adapt without reliance on rules or training data.
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While a significant portion (53%) of respondents acknowledge their organization’s early-stage adoption of AI, only 18% report full deployment into integrated security programs. This cautious approach reflects the need for careful planning and implementation to ensure AI enhances, rather than hinders, security posture.
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The cybersecurity landscape is under siege. Organizations are bombarded by a relentless barrage of security alerts, often exceeding a staggering 22,111 per week on average. While Artificial Intelligence (AI) has emerged as a powerful tool to manage this overwhelming volume, its effectiveness isn’t without limitations, as vendors flood the market with false advertising and promises.
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This week, we’re looking into how the rise of artificial intelligence (AI) has significantly altered the threat landscape, introducing challenges and opportunities for organizations seeking to safeguard their data and infrastructure.
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The terms “machine learning” and “artificial intelligence” are frequently used in cybersecurity, often interchangeably, leading to confusion about their precise meanings and applications. Both machine learning and artificial intelligence play pivotal roles in fortifying cybersecurity defenses, yet they encompass distinct methodologies and applications. What are the disparities between them? And how do these technologies converge to bolster cyber resilience?
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Attention, fellow news anchors and concerned citizens! Rob Burgundy is here to tackle a story hotter than a disco inferno in polyester pants: Artificial Intelligence (AI) and Cybersecurity. That’s right, folks. In this digital age, hackers are running rampant like greased weasels in a chicken coop, stealing our precious data faster than you can say “glass case of emotion.” But fear not, for organizations are turning to a new weapon in this cyber war: AI, the thinking machine!
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A new report from Microsoft and Open AI shows how attackers are increasingly using artificial intelligence (AI) to improve their cyberattacks. The report found that nation-backed groups use LLMs for research, scripting, and phishing emails.
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MixMode is the first to bring a third-wave, context-aware AI approach that automatically learns and adapts to dynamically changing environments. MixMode’s monitoring platform, PacketSled, better understands network behavior as it adapts to baseline changes and enables both misuse detection and anomaly detection, as well as predictive maintenance. Used by enterprises and MSSPs for real-time network analysis, threat hunting and incident response, the platform leverages continuous stream monitoring and retrospection to provide network forensics and security analytics. Security teams can integrate PacketSled into their orchestration engine, SIEM, or use PacketSled independently to dramatically reduce false positive alerts and the resources required to respond to persistent threats, malware, insider attacks and nation state espionage efforts.
The company has been named an innovator in leading publications and by security analysts, including SC Magazine, earning a finalist award in 2018 and 2019 for "Best Computer Forensic Solution.” Based in Santa Barbara, with offices in San Diego, the company is backed by Keshif Ventures and Blu Venture Investors. For case studies, continuous product updates and industry news, please visit us at www.mixmode.ai.