Kernel and Graphics Leftovers
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Ubuntu ☛ Real-time Linux: a comprehensive guide
At its core, a real-time system guarantees the execution of high-priority processes with deterministic response times. This means that enterprises can confidently run their most demanding workloads, knowing that there is an upper time bound for mission-critical latency requirements. Real-time systems are the bedrock for applications where timing is everything, ensuring that tasks are executed within specified deadlines, without compromise.
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Jeff Geerling ☛ External GPUs working on the Raspberry Pi 5
Honestly, I'm approaching 'infantile' stages of familiarity with graphics drivers, but I know enough to mess up the driver (a lot) and quite rarely get something working on my own. I hope that with the Pi 5's better PCIe bus (and Gen 3.0 speeds, even if unofficial), more people can work on squashing arm64 vs x86-related memory access bugs in various drivers.
The best thing is on the Pi 5, I've so far never encountered any bugs where the entire system crashes (to the point the kernel can't recover). On the Compute Module 4, I had to hard pull power and re-apply it to get back into a working state! Debugging is immeasurably if you can get an error message or exception, and the entire system doesn't explode every time you test it :)
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Silicon Angle ☛ Nvidia unveils generative AI microservice for accurate answers with enterprise data
Retrieval-augmented generation, or RAG, is a method for increasing the accuracy and safety of generative AI models by filling in the gaps in the “knowledge” of large language models with facts and data retrieved from external sources. An LLM receives up-front training that provides it with a lot of general task knowledge and capabilities such as understanding conversational prompts, summarization and providing question-and-answer capabilities. Training is expensive and time-consuming, so it is often only done once, or rarely, to prepare a model for deployment.