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Aiceberg's Approach: Using Machine Learning to Protect Generative AI from Cyber Threats

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Big Pond Podcasts and MSP Radio에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Big Pond Podcasts and MSP Radio 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Alexander Schlager, CEO of Aiceberg.ai, discusses the intersection of artificial intelligence (AI) and cybersecurity, emphasizing the importance of securing AI-powered workflows. Aiceberg employs traditional machine learning techniques to safeguard generative AI systems, providing a deterministic and explainable approach to security. This method allows organizations to understand how their AI systems operate and ensures that they can trace and audit the decisions made by these systems, which is crucial in an era where AI incidents may lead to legal challenges.

The conversation highlights the need for organizations to establish robust governance frameworks as they adopt AI technologies. Schlager points out that many businesses are still grappling with basic cybersecurity measures, which complicates their ability to implement effective AI governance. He stresses that organizations must assess their existing security postures and ensure that they are prepared for the rapid deployment of agentic AI, which allows non-technical users to create and manage AI workflows independently.

Schlager provides concrete examples of how Aiceberg's technology is integrated into real-world applications, such as in the banking sector, where AI workflows may involve third-party interactions. He explains that Aiceberg monitors these interactions to classify and respond to potential security threats, ensuring that organizations can demonstrate compliance and safety in the event of an incident. This proactive approach to security is essential for maintaining trust and accountability in AI systems.

Finally, the discussion touches on the broader implications of AI adoption, including the potential for improved customer experiences across various industries. Schlager notes that while AI can enhance service delivery, organizations must navigate the challenges of user expectations and the maturity of their AI implementations. By focusing on customer service and experience, companies can unlock significant value from their AI investments, but they must also prioritize security and governance to mitigate risks.

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1786 에피소드

Artwork
icon공유
 
Manage episode 508836532 series 2555839
Big Pond Podcasts and MSP Radio에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Big Pond Podcasts and MSP Radio 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Alexander Schlager, CEO of Aiceberg.ai, discusses the intersection of artificial intelligence (AI) and cybersecurity, emphasizing the importance of securing AI-powered workflows. Aiceberg employs traditional machine learning techniques to safeguard generative AI systems, providing a deterministic and explainable approach to security. This method allows organizations to understand how their AI systems operate and ensures that they can trace and audit the decisions made by these systems, which is crucial in an era where AI incidents may lead to legal challenges.

The conversation highlights the need for organizations to establish robust governance frameworks as they adopt AI technologies. Schlager points out that many businesses are still grappling with basic cybersecurity measures, which complicates their ability to implement effective AI governance. He stresses that organizations must assess their existing security postures and ensure that they are prepared for the rapid deployment of agentic AI, which allows non-technical users to create and manage AI workflows independently.

Schlager provides concrete examples of how Aiceberg's technology is integrated into real-world applications, such as in the banking sector, where AI workflows may involve third-party interactions. He explains that Aiceberg monitors these interactions to classify and respond to potential security threats, ensuring that organizations can demonstrate compliance and safety in the event of an incident. This proactive approach to security is essential for maintaining trust and accountability in AI systems.

Finally, the discussion touches on the broader implications of AI adoption, including the potential for improved customer experiences across various industries. Schlager notes that while AI can enhance service delivery, organizations must navigate the challenges of user expectations and the maturity of their AI implementations. By focusing on customer service and experience, companies can unlock significant value from their AI investments, but they must also prioritize security and governance to mitigate risks.

💼 All Our Sponsors

Support the vendors who support the show:

👉 https://businessof.tech/sponsors/

🚀 Join Business of Tech Plus

Get exclusive access to investigative reports, vendor analysis, leadership briefings, and more.

👉 https://businessof.tech/plus

🎧 Subscribe to the Business of Tech

Want the show on your favorite podcast app or prefer the written versions of each story?

📲 https://www.businessof.tech/subscribe

📰 Story Links & Sources

Looking for the links from today’s stories?

Every episode script — with full source links — is posted at:

🌐 https://www.businessof.tech

🎙 Want to Be a Guest?

Pitch your story or appear on Business of Tech: Daily 10-Minute IT Services Insights:

💬 https://www.podmatch.com/hostdetailpreview/businessoftech

🔗 Follow Business of Tech

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