New innovations in Confidential AI and Analytics, Data Clean Rooms on Microsoft Azure confidential computing, and Privacy-Preserving LLMs are Highlighted at the inaugural Confidential Computing Summit held in San Francisco.

Opaque Systems, a pioneer of secure multi-party analytics and AI for Confidential Computing, today announced key innovations for its Confidential Computing platform. Protecting the confidentiality of organizational data during LLM use and new applications such as Data Clean Rooms will be showcased during Opaque’s keynote at the Confidential Computing Summit.

Through privacy-preserving generative AI and zero trust data clean rooms (DCRs) optimized for Microsoft Azure confidential computing, Opaque enables multiple organizations to easily and securely analyze their combined confidential data without sharing or revealing the underlying raw data. With broader support for confidential AI use cases, the Opaque platform will also provide safeguards for machine learning and AI models to execute on encrypted data inside of Trusted Executions Environments (TEEs), preventing exposure to unauthorized parties.

These innovations will be unveiled next week at the inaugural Confidential Computing Summit in San Francisco, hosted by Opaque Systems and the Confidential Computing Consortium. The Summit also features sponsors, keynotes and speakers from Microsoft, Intel, VMware, ARM, Signal Messenger, Google Cloud Platform (GCP), Fortanix, Anjuna Security, Cosmian, Meta, Google and Ernst & Young amongst others.

Opaque’s President and co-founder Professor Raluca Ada Popa will open the Confidential Computing Summit with her keynote entitled “Confidential Computing and The Solution to Privacy-Preserving Generative AI”. While ChatGPT today is trained on public data, the usefulness of LLMs can skyrocket if trained on organization’s confidential data without any risk of exposure; by protecting the data during LLM training and inference, confidential computing can unlock this potential. Raluca is also a security and privacy professor at UC Berkeley, where she co-directs the SkyLab, a lab at the forefront of LLM and privacy research that recently developed the popular Vicuna open-source LLM model (22.5K stars).

During his keynote, Rishabh Poddar, Co-founder & CEO of Opaque Systems, will unveil Opaque’s new innovations in Data Clean Rooms, secure multi-party analytics and discuss how Opaque can protect organization’s confidential data when using generative AI. At the Summit, Poddar will showcase how executing the AI and LLM models on encrypted data using the Opaque Confidential Computing Platform can safeguard against the exposure of confidential data to unauthorized parties.

“The challenge with traditional DCRs in the cloud is ensuring that other parties analyzing data do not inadvertently or purposefully gain access to raw data being processed,” said Rishabh Poddar, Co-founder & CEO, Opaque Systems. “With Opaque’s new DCR offering, organizations can securely collaborate on data within their business ecosystem while ensuring that their unencrypted, raw data is never exposed. To further protect data being used in generative AI models and LLMs, the platform will enable organizations to make use of groundbreaking Confidential AI capabilities to protect data privacy.”

“Opaque’s Data Clean Room solution on Microsoft Azure confidential computing brings secure multi-party data sharing, analytics and AI to organizations that are under increasing pressure to meet new data privacy regulations,” said Vikas Bhatia, Head of Product, Microsoft Azure Confidential Computing.  “With the Opaque solution, organizations can now tackle a range of important use cases – from detecting financial crime, identifying fraud, to enabling better marketing insights while reinforcing consent of consumers on use of their data.”

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The Opaque Platform’s DCR capabilities enable secure, multi-party analytics on fully encrypted confidential data secured in TEEs, allowing queries to be executed on encrypted data without compromising its confidentiality. This ensures the data and insights are only accessible by authorized parties. For advertisers and marketers for example, this means multiple parties can collaborate on sensitive data to measure ad campaign effectiveness, personalized consumer targeting, measurement, and more, with each party only being able to see the data they directly own.

Advantage of the Opaque Confidential Computing Platform include:

• Zero trust Data Clean Rooms: With Opaque’s data clean room capabilities, customers can create data clean rooms in minutes and perform multi-party analytics and AI on confidential data to generate unique cross-organizational insights across their ecosystem of partners while ensuring each party only sees the data that they directly own.
• Confidential AI and LLM Inference: By running LLM models within Opaque, customers will also be able ensure that their queries and data remain private and protected at all times, and are never exposed to the model / service provider or used in unauthorized ways.
• Data Security: Multiple layers of protection for sensitive data against potential cyber-attacks or data breaches, through a powerful combination of secure hardware enclaves and cryptographic fortification
• Privacy and Compliance: A powerful policy framework to govern confidential data permissions and access, while allowing confidential data to be analyzed together with non-confidential data to achieve business insights.

While these innovations will be discussed in more detail during the Confidential Computing Summit next week, the focus of the summit will remain on the growing urgency to secure and protect confidential and sensitive data, as regulations and policies around data privacy continue to rise. Between the regulations around protecting consumers data privacy in AdTech to use cases such as money laundering in financial services, and now the risk of exposing confidential data with generative AI technologies, the Summit brings to the forefront the need for confidential computing across industries.

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