Dr. Alex Balbontin’s Post

Prioritize Data Security in Generative AI: It's a Prethought, Not an Afterthought In the realm of Generative AI, ensuring data security isn't merely an afterthought—it's a fundamental prethought. As we delve into the innovative potentials of AI, particularly with the advent of transformative technologies like Brane trained transformer (BTT), it's imperative to safeguard sensitive data with utmost vigilance. Here's the crux: No matter the promises made by service providers, never compromise on the sanctity of your data leaving your controlled environments—be it private cloud setups or on-premise infrastructure. Your data's security should never be negotiable. Enter BTT, the world's pioneering and exclusive private, enterprise, and locally deployable commercial Large Language Model (LLM). What sets BTT apart is its unparalleled ability to seamlessly integrate with enterprise data, whether structured or unstructured, without ever necessitating data to leave your secure environment. BTT empowers organizations to harness the transformative power of Generative AI while upholding the highest standards of data privacy and security. By deploying BTT within your environment, you retain full control over your data, mitigating the risks associated with external data transfers and ensuring compliance with stringent regulatory frameworks. Moreover, BTT isn't just about fortifying data security; it's about unlocking the true potential of AI within the confines of your enterprise. By leveraging contextual responses derived from your proprietary data sources, BTT enables organizations to craft bespoke solutions tailored to their unique operational requirements. In essence, with BTT, data security isn't an add-on—it's ingrained within the fabric of its design. It's about empowering organizations to navigate the ever-evolving landscape of AI innovation with confidence, knowing that their data remains under their jurisdiction at all times. So, as you venture into the realm of Generative AI, remember: Prioritize data security from the outset, and opt for solutions like BTT that champion privacy, security, and enterprise-grade performance without compromise. Your data deserves nothing less than the utmost protection. Brane Group

Big News! The platform seeks to address the issue of security and privacy concerns when it comes to implementing generative AI. Opaque argues that due to red tape and compliance requirements, enterprise data is often trapped, with existing techniques, like anonymization, proving to be error-prone and inadequate for many businesses. With enterprises being forced to choose between innovation with AI and security, many have no choice other than to pick security, preventing AI projects from coming to fruition. This is where Opaque’s Confidential AI Platform steps in. “Enterprises have long been forced to choose between data security and extracting value from their data. With Opaque, that dichotomy ends,” said Chief Executive Aaron Fulkerson. “Our platform ensures complete data sovereignty while allowing seamless deployment of AI workloads, unlocking business insights securely and efficiently – often enabling the use of sensitive data that couldn’t be used before.” https://lnkd.in/gJWjrrRZ

STAYING SECURE WHILE USING GENERATIVE AI: BEST PRACTICES Generative AI tools are transforming how we work and interact with technology, offering benefits from automating tasks to data analysis. However, safeguarding sensitive data is crucial when utilizing generative AI, whether you’re an individual or part of an organization. Here are strategies to ensure your data remains secure while using these tools. 1. Don’t Paste Sensitive Data🔒 Avoid copying and pasting private information, such as passwords or personal data, into AI tools. Many platforms may temporarily store user inputs to enhance their services, which could expose your data to unauthorized access. Assume that anything shared could be stored unless stated otherwise. 2. Understand the AI Tool’s Data Policy📜 Before using any AI tool, review its privacy and data usage policies. Check for features like encryption and data protection, and find out if the tool retains user inputs for training purposes. For businesses, especially in regulated industries like healthcare or finance, it’s essential to choose AI tools that comply with standards such as GDPR or HIPAA. 3. Use Redacted Data for Testing🧪 When testing AI features, avoid entering actual confidential information. Instead, use placeholders for specific details like names or addresses. This straightforward approach helps ensure privacy and is useful when trying out new AI tools for personal or professional use. 4. Consider On-Premises AI Solutions🏢 For organizations handling sensitive data, on-premises AI solutions can provide greater security than cloud-based services. This setup allows companies to run AI models within their infrastructure, ensuring that all data remains within their network. 5. Limit Data Exposure🚫 Share only the information that is absolutely necessary. AI systems don’t always require all your data to produce accurate results. By limiting what you share, you reduce the risk of disclosing sensitive information. 6. Choose Trusted AI Providers✅ Opt for AI services that prioritize data privacy and security. Look for features such as transparent data management policies, secure transfer methods, and end-to-end encryption. Reputable providers often share compliance with security standards. 7. Use Monitored AI Systems for Enhanced Security👀 In corporate environments, consider AI tools with logging and auditing capabilities. These features allow IT administrators to track data usage and detect unauthorized access. 8. Consider a Hybrid Approach for Flexibility⚖️ If you can't use a fully on-premises solution, think about implementing a hybrid AI system. This entails handling private information locally, on your own servers, while utilizing cloud services for less important work. A hybrid strategy is a workable solution for both small and large firms since it combines the privacy of on-premise data handling with the convenience of cloud AI. #GenerativeAI #DataSecurity #Cybersecurity #AIbestpractices #CloudSecurity

OneTrust platform enhancements accelerate AI adoption: OneTrust announced its newest platform features that make it easier for customers to govern their use of AI and accelerate AI innovation, ensure the responsible use of data across the entire data lifecycle, and achieve compliance program efficiency through enhanced automation and intelligence. “Today organizations are navigating the challenging complexities of being in a data-centric world amplified by AI advancements, the exponential growth of data, and the shift toward first-party data strategies,” remarked Blake Brannon, … More → The post OneTrust platform enhancements accelerate AI adoption appeared first on Help Net Security.

How do organizations tackle the data security challenges of third-party collaborations without stifling innovation? Now, throw in the complexities of building AI applications; how do you minimize the risk? Our latest blog post delves into those risks of sharing working with third parties and sharing sensitive AI training data and offers strategies for robust protection and compliance. A great read if you are interested in ensuring your collaborations are safe and successful! #DataSecurity #AI #DSPM

Create a Comprehensive Data Security Approach for Generative AI https://lnkd.in/eRvrtKuw

BigID raises $60 million to accelerate AI data security innovation: BigID announced that it closed a $60 million growth round led by Riverwood Capital with participation by Silver Lake Waterman and Advent. With the strong momentum of generative AI, enterprises have rushed to stand up new initiatives that drive productivity behind novel use cases leveraging documents, images, code, chats and other types of “unstructured” and structured data. Before BigID was launched into the market in 2018, data security products were purpose-built for specific data types. … More → The post BigID raises $60 million to accelerate AI data security innovation appeared first on Help Net Security.

Crafting a Comprehensive Data Security Approach for Generative AI https://lnkd.in/eRvrtKuw

Thrilled to share the latest from our client, Privacera! Today, #Privacera announced enhancements to their Privacera AI Governance (PAIG) solution, industry's first comprehensive generative AI governance solution. Organizations can now seamlessly integrate data from various platforms, implement advanced classification-based filtering, and enforce fine-grained authorization protocols. This innovation empowers businesses to securely leverage #GenAI technologies. #AI #DataSecurity #Governance #Innovation Learn more about how Privacera is revolutionizing AI data security governance: https://lnkd.in/g5kM3Wim

It is particularly true in our age of artificial intelligence (AI). But throughout history, wars have been fought over oil — and today, data is no less a critical resource to protect and secure. That’s because AI has changed to the way businesses approach data transformation, storage, management and governance. This is an unavoidable reality within security-critical sectors like payments and financial services, where conversations around data transformation, data sharing and generative AI are top of mind for every executive — as are the implications of AI on data collection, storage and use. “For the last 10 years, the financial sector alone has invested countless sums into data science and building out their data intelligence departments,” Taylor Lowe, CEO and co-founder of AI infrastructure platform Metal, told PYMNTS. “Not only is a lot of the infrastructure in place throughout these organizations, but the incentives are there: the years of operating with a data-first mindset have paid off, and firms see how valuable it is. Technologies like AI have just added more fuel to that fire and accelerated the insights you can get out of your data,” Lowe explained.