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Open Source Developments Span Robotics, Security, and Embedded Systems
Recent developments in open-source technology are making waves across various sectors, from robotics and security to embedded systems. These advancements include the creation of general-purpose robot foundation models, hardened minimal container images for improved security, and simplified embedded Linux build systems.
Physical Intelligence, co-founded by Sergey Levine, is developing general-purpose robot foundation models trained on real-world tasks. According to reports, these models aim to provide a foundation for robots to learn and adapt to various environments and tasks.
In the realm of cybersecurity, a collection of minimal container images with significantly reduced vulnerabilities are now available. These hardened images, built daily with Chainguard's tools, offer a more secure alternative to traditional base images, minimizing attack surfaces in containerized applications.
For embedded systems development, a simplified YoctoOpenEmbedded setup example has been released. Known as "simplest-yocto-setup," this project aims to provide a straightforward and practical example of how Yocto/OpenEmbedded can be used as an embedded Linux build system without unnecessary complications. The project's GitHub page states that it aims to help developers avoid problems caused by overly complex layers, promoting a more understandable, efficient, and less buggy build environment. "We have spent a lot of time in educating to writing clean layers, which often involved fixing problems by removing a lot of the code they had written or they had taken from existing third-party layers," the project description notes.
Genode, an open-source OS framework, continues to evolve as a solution for building highly secure, special-purpose operating systems. Designed to scale from embedded systems to dynamic workloads, Genode utilizes sandboxes and a recursive structure. It supports multiple CPU architectures and kernels, including L4 family members and Linux, and offers virtualization options alongside over 100 ready-to-use components. Genode Labs makes the framework commercially viable.
Other developments include optimizations in matrix multiplications on ARM's SME via the MpGEMM library and discussions surrounding compiler optimizations related to SSA-renaming and control-flow changes. These advancements reflect ongoing efforts to improve performance and efficiency across various computing platforms.
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