mc2
cerebro
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mc2 | cerebro | |
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8 | 6 | |
291 | 8,203 | |
0.7% | 0.5% | |
0.7 | 3.2 | |
almost 1 year ago | about 1 month ago | |
C++ | JavaScript | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
mc2
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Intel deprecates SGX on Core series processors
Analytics and ML on confidential data are some interesting server side use cases. See the MC2 open source project, for example: https://github.com/mc2-project/mc2
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How to Run Spark SQL on Encrypted Data
Check out more blog posts on how to securely process data with MC² Project. We would love your contributions â and support â! Please check out the Github repo to see how you can contribute. No contribution is too small.
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Announcing MC²: Securely perform analytics and machine learning on confidential data
MC2 is a platform for running secure analytics on data that stays encrypted even when in use. By doing so, the project also enables secure collaboration among multiple organizations, where individual data owners can use our platform to jointly analyze their collective data without revealing it to one another. To learn more and to see the individual projectsâ documentation, visit our landing page.
We are excited to announce the initial release of the open source MC2 Project, a collection of tools for computing and collaborating on confidential data. Developed by our team in the UC Berkeley RISELab, MC2 (Multi-Party Collaboration and Coopetition) enables rich analytics and machine learning on encrypted data, ensuring that data remains concealed even when itâs being processed. The data in use remains hidden from the server running the job, allowing confidential workloads to be offloaded to untrusted third parties or cloud providers. This not only protects confidential data from intrusions, but also enables secure collaboration -- multiple data owners can jointly run analytics or ML on their collective data, without explicitly revealing their individual data to anyone else: not even a trusted third party.
cerebro
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Should I worry about using Raycast on MacOS?
There are these open source alternatives, I havenât checked their privacy policies or their code Maybe try and report back? https://www.cerebroapp.com https://qsapp.com https://ueli.app https://github.com/ParthJadhav/Verve
- Albert â open-source keyboard launcher for Linux
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I am genuinely curious - why Microsoft thinks this is an acceptable default search behavior?
Other options that are open source are wox, cerebro and flow launcher
What are some alternatives?
Flow.Launcher - :mag: Quick file search & app launcher for Windows with community-made plugins
rofi - Rofi: A window switcher, application launcher and dmenu replacement
albert - A fast and flexible keyboard launcher
Ulauncher - Feature rich application Launcher for Linux
jumpapp - A run-or-raise application switcher for any X11 desktop
delphi - A Cryptographic Inference Service for Neural Networks
sway-launcher-desktop - TUI Application launcher with Desktop Entry support. Made for SwayWM, but runs anywhere
Thrive-Launcher - Thrive Launcher for installing and automatically updating Thrive
opaque-sql - An encrypted data analytics platform
CPLauncher - Launcher application
secure-xgboost - Secure collaborative training and inference for XGBoost.
cerebro - Cerebro: A platform for Secure Coopetitive Learning