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What is Lumo?

Lumo serves as a privacy-centered AI assistant that leverages generative AI's potential while prioritizing the confidentiality of your discussions. Developed by the privacy experts behind Proton Mail and VPN, Lumo ensures that conversations remain confidential, with no logs kept on its servers and all stored interactions protected by zero-access encryption, which prevents even Proton from accessing them. Boasting an open-source architecture, this service offers transparency and verification, enabling users to interact with it freely and securely. You can discuss a wide range of subjects with Lumo, from summarizing documents and rewriting emails to aiding in coding, translating text, brainstorming ideas, and more, all while maintaining peace of mind that your data won't be utilized for model training or shared externally. The platform secures conversations through end-to-end encryption, and, if you activate the AI’s web search feature, it relies on privacy-focused search engines. Lumo is easily accessible without requiring registration and is available on both web and mobile platforms, offering users a choice between free and premium plans. Its strong emphasis on safeguarding user privacy makes Lumo an appealing option for those who prioritize the security of their personal information when engaging with AI technology. Additionally, Lumo continually updates its features to enhance user experience and maintain the highest standards of privacy.

What is Google Cloud Confidential VMs?

Google Cloud's Confidential Computing provides hardware-based Trusted Execution Environments (TEEs) that ensure data is encrypted during active use, thus finalizing the encryption for data both at rest and while in transit. This comprehensive suite features Confidential VMs, which incorporate technologies such as AMD SEV, SEV-SNP, Intel TDX, and NVIDIA confidential GPUs, as well as Confidential Space to enable secure multi-party data sharing, Google Cloud Attestation, and split-trust encryption mechanisms. Confidential VMs are specifically engineered to support various workloads within Compute Engine and are compatible with numerous services, including Dataproc, Dataflow, GKE, and Vertex AI Workbench. The foundational architecture guarantees encryption of memory during runtime, effectively isolating workloads from the host operating system and hypervisor, and also includes attestation capabilities that offer clients verifiable proof of secure enclave operations. Use cases for this technology are wide-ranging, encompassing confidential analytics, federated learning in industries such as healthcare and finance, deployment of generative AI models, and collaborative data sharing within supply chains. By adopting this cutting-edge method, the trust boundary is significantly reduced to only the guest application, rather than the broader computing environment, which greatly enhances the security and privacy of sensitive workloads. Furthermore, this innovative solution empowers organizations to maintain control over their data while leveraging cloud resources efficiently.