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# The Fundamentals of AI: Making AI practical

**[Cisco](https://daily.dev/sources/cisco)** · 18 min read · 0 upvotes · 0 comments

## Summary

A practical overview of the engineering techniques that turn large language models from research artifacts into production-ready systems. Covers foundation models and their concentration risks, fine-tuning strategies including LoRA and QLoRA, catastrophic forgetting and how modular adapters solve it, knowledge distillation for on-device deployment, retrieval-augmented generation (RAG) for grounding outputs in real documents, mixture-of-experts architecture, chain-of-thought prompting, and the real-world deployment challenges around GPU costs, latency, and enterprise privacy. The piece emphasizes that engineering ingenuity — not architectural breakthroughs — is what makes modern AI practical.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blogs.cisco.com/ai/the-fundamentals-of-ai-making-ai-practical>

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Tags: [#llm](https://daily.dev/tags/llm), [#deep-learning](https://daily.dev/tags/deep-learning), [#rag](https://daily.dev/tags/rag), [#lora](https://daily.dev/tags/lora)

[View this post on daily.dev](https://daily.dev/posts/the-fundamentals-of-ai-making-ai-practical-omgiheigt)

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