Devo, the security analytics company, recently launched data orchestration, a data analytics cloud, and security operations center (SOC) workflow enhancements. https://bit.ly/3M3lg5x #CyberSecurity
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Principal Cybersecurity Engineer, Vulnerability Management - Cyber Vulnerability, Conformance & Risk Team at T-Mobile
https://lnkd.in/e6SrvY3i For my Seattle area connections: Build your AI Knowledge Track 1: AI Security Fundamentals AI Threats and Vulnerabilities Covering the potential threats and vulnerabilities associated with AI systems and exploring the various attack vectors, security risks, and potential misuse of AI technologies. Topics may include adversarial attacks, data poisoning, model corruption, and other security concerns related to AI models and systems. AI Security Testing and Validation Exploring the methods and techniques for testing, evaluating and validating the security of AI systems. Topics may include adversarial testing, model vulnerability assessment, and best practices for securing AI systems throughout the development lifecycle. Track 2: AI Security Governance and Controls AI Control Framework Focusing on the development and implementation of control frameworks for AI systems. Topics may include risk assessment, control design, monitoring, and auditing of AI systems to ensure their safe and responsible deployment. AI Organizational Responsibilities & AI Governance Examining the responsibilities and obligations of organizations in the context of AI systems. Topics may include ethical AI practices, accountability, transparency, and governance, risk management, and compliance (GRC) aspects of AI systems and regulatory landscape, legal and ethical considerations, and best practices for ensuring AI systems are developed and deployed in a responsible and compliant manner. Track 3: AI Security Operations and Emerging Trends MLSecOps Focusing on the intersection of machine learning (ML), security, and operations (SecOps). Topics may include secure ML pipelines, model governance, continuous monitoring, and the integration of security practices into the ML lifecycle. AI and Cybersecurity Integration Examining the integration of AI technologies with cybersecurity practices and tools. Topics may include AI-powered threat detection, automated incident response, and the use of AI in enhancing cybersecurity operations. AI Security in Specific Domains Exploring the unique security challenges and considerations of AI systems in specific domains or industries, such as healthcare, finance, transportation, or critical infrastructure. AI Trends & Future Considerations Exploring the latest trends and future considerations in the field of AI. Topics may include emerging AI technologies, research advancements, potential use cases, and the impact of AI on various industries and society as a whole.
Join me at SECtember.ai 2024
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Struggling with security overload, clunky tools, and a talent shortage? Google Cloud has your back! 💯 Recent breakthroughs in AI, especially large language models (LLMs), are supercharging security solutions. Watch this video to see how Google Cloud Security AI Workbench, a one-of-a-kind platform powered by a specialized security LLM, tackles these top three security headaches: <> Threat overload <> Toilsome tools <> The talent gap See how Google Cloud Security AI Workbench can revolutionize your security posture. https://lnkd.in/gWw3EaQj -
Supercharge security with generative AI
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Google Cloud Data Loss Prevention allows businesses to securely encrypt, decrypt, and anonymise data, such as Personally Identifiable Information (PII), to pursue innovative generative AI use cases whilst minimising security risks. 🔐 Read about our work with a leading energy supplier to find out more: 🔋 https://lnkd.in/e37R_BDp #GenerativeAI #DataLossPrevention #Security #Energy #Electricity #CustomerExperience
Innovating Securely with Generative AI | Datatonic
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As we approach 175 zettabytes of information by 2025, AI is taking the lead in securing data through innovations like Zero Trust Security, Predictive Threat Intelligence, and Cloud Security. See how AI is set to reshape IT and other top industries in 2024 👇 #AI2024 #TechInnovation #TechTrends ✍️ Dr. Pooja Choudhary - AiThority.Com https://bit.ly/3O3tJ9Y
State Of AI In 2024 In The Top 5 Industries
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As the use of Cloud SaaS platforms of generative AI solutions increases, the likelihood of more “GPT” attacks used to gather credentials, payment info, and corporate data also increases. https://bit.ly/4b89QIO
Use of Generative AI Apps Jumps 400% in 2023, Signaling the Potential for More AI-Themed Attacks
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The future of the cloud is being formed by data-driven systems and AI, and with these shifts, there is an impact on applications. CIOs in Toronto came together for a Town Hall last month to explore how AI will impact the application lifecycle, the range of AI solutions available, and how to turn AI predictions into reality – these are their takeaways. #EvantaCIO #CIO #Cloud #AI #EvantaCISO #TorontoCISO #MontrealCISO #EvantaCIO #TorontoCIO #Leadership #cybersecurity
Predictions for the Future of Cloud
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Generative AI is all about accuracy, and that's where Groundedness Detection comes in. This first-of-its-kind feature on Azure AI cloud platform identifies and blocks "hallucinations" in outputs, increasing accuracy and usefulness. The Verge covers this and three other tools that help organizations deploy AI responsibly. Check it out! #msftadvocate #ai
Microsoft’s new safety system can catch hallucinations in its customers’ AI apps
theverge.com
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SaaS / Tech Executive and Leader / Helping companies simplify technology for Business Growth / Entrepreneur / Agile Enthusiast / Father 6K+ connections
The value of AI-generated platforms and products, particularly when combined with Quantum Computing, is a rapidly evolving area with several key trends and opportunities: Generative AI: This trend involves AI that can create content, design products, or simulate scenarios. It's particularly useful for industries like gaming, film, and design, where the ability to generate new, unique content can be a game-changer. Explainable AI (XAI): As AI systems become more complex, the need for transparency and understanding of how these systems make decisions is crucial. XAI aims to make AI decisions more interpretable to humans, which is essential for gaining trust and meeting regulatory requirements. Quantum Machine Learning: Quantum Computing promises to significantly speed up the processing capabilities of machine learning algorithms. This could lead to breakthroughs in drug discovery, material science, and complex optimization problems. The integration of AI and Quantum Computing is poised to transform industries by enabling more efficient algorithms, improving cybersecurity, and facilitating advancements in various fields such as healthcare, finance, and material science. However, challenges such as the "black box" problem of AI, where the decision-making process is not transparent, and the need for rapid development in Quantum AI, present hurdles that need to be overcome. For businesses and industries, leveraging these trends means investing in platforms and products that can harness the power of both AI and Quantum Computing to stay ahead of the curve. This could involve adopting AI solutions that prioritize explainability and ethical practices, as well as exploring Quantum Computing's potential to enhance their operations and innovation capabilities. Elastic CEO talking about AI and Cloud Computing at Davos 2024: https://lnkd.in/ess_FBMW #ai #quantumcomputing #cloudcomputing
Elastic CEO on cloud demand, cybersecurity trends, and artificial intelligence
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In this article, CIO Online dives into the top trends shaping the ever-changing enterprise IT landscape. It explores the rise of generative AI, the evolving role of cloud computing, the importance of zero-trust security, and the potential of quantum computing. #technology #trends #techtrends #genai #cloudcomputing #cybersecurity #quantumcomputing #datamanagement
6 trends defining the enterprise IT market today
cio.com
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