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 networkphil.com
Beginner's Guide for Using Large Language Models in Network Operations - {networkphil}
| | www.k2view.com
What is Retrieval-Augmented Generation (RAG)? A Practical Guide
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| | Retrieval-augmented generation is an AI framework that improves LLM accuracy. Learn how to inject enterprise data into LLMs for more reliable responses.
| | www.osedea.com
From idea to impact: how we scope and start an agentic AI project
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| | Learn how Osedea scopes and builds agentic AI systems that deliver real-world impact-fast, focused, and tailored to your business goals.
| | blog.christianposta.com
A Gentle Introduction to LLMs for Platform Engineers - ceposta Technology Blog
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| | Things change quickly in the land of technology. AI is the "hot" thing. I feel for the platform engineers out there struggling with technologies like Docker, Kubernetes, Prometheus, Istio, ArgoCD, Zipkin, Backstage.io, and many many others. Those things are already confusing, complex, and require deep attention. These folks don't have time or attention to dig into AI and what's going on in that space. But little by little AI will land in their world. Platform engineers will need to understand AI.
| | xcorr.net
Denoising diffusion models for neuroscience - xcorr: AI & neuro
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| 2022 was the year of generative AI models: DALL-E 2, MidJourney, Stable Diffusion, and Imagen all showed that it's possible to generate grounded, photorealistic images. These generative AIs are instances of conditional denoising diffusion probabilistic models, or DDPMs. Despite these flashy applications, DDPMs have thus far had little impact on neuroscience. An oil painting of...