{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Embracing Digital Transformation","title":"#219 Embracing Confidential Generative AI","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/b5c92f74\"></iframe>","width":"100%","height":180,"duration":1865,"description":"Confidential computing is starting to take hold in industries where data privacy and personal data protection are important. The rise of Generative AI and the lack of protection are the perfect backdrop for the conversation Darren has with returning guest Patrick Conte, VP of sales from Fortanix.As the world increasingly turns to artificial intelligence, the importance of robust data security can no longer be overlooked. With the rise of Generative AI activities, questions arise about protecting sensitive data while leveraging its potential. In this blog post, we will explore essential concepts surrounding confidential computing, the relevance of security from development to deployment, and actionable steps organizations can take to safeguard their AI models.The Landscape of Confidential ComputingConfidential computing represents a paradigm shift in how we think about data security. Traditionally, encryption protects data at rest and in transit, but what happens when that data is actively being used? Enter confidential computing, which ensures that sensitive data remains encrypted even during processing. This technology uses trusted execution environments (TEEs) to create isolated, secure spaces for processing data, effectively creating a fortress around your most sensitive information.Imagine having a data pipeline where all information is encrypted and can only be decrypted within a controlled environment. No more worries about unauthorized access or misinformed data leaks! For technologists and business leaders, this is not just a technical necessity, but a strategic advantage that empowers them to confidently pursue AI initiatives. They can do so, knowing their proprietary data and intellectual property are maintained at a high level of protection.Real-World ApplicationsUsing real-world applications can help illustrate the capabilities of confidential computing. For instance, companies involved in drug development can securely share sensitive research data...","thumbnail_url":"https://img.transistorcdn.com/IRrW2aizIeoZDn3gKLEax-JYQ8V_WzaFpHdgsslDx3k/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9jM2Ji/MDk1OTdiYzA4ZWMw/NWNlOTY0N2RhMWQ3/YmY5Mi5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}