From the course: Build Your Own AI Lab
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Choosing the right hardware (GPUs, CPUs, memory, etc.)
From the course: Build Your Own AI Lab
Choosing the right hardware (GPUs, CPUs, memory, etc.)
- [Instructor] In this section, we'll go over one of the most crucial decisions that you will make whenever you're building your lab, and that is choosing the right hardware components for your home AI infrastructure. So let's start with the backbone of any AI lab, and that is the GPUs, right? So the GPUs or the graphical processing units, they are definitely the workhorse of any machine learning environment, right? So they're capable of performing thousands of parallel calculations simultaneously. So whenever you're selecting GPUs, you want to consider a few factors. The first thing is the compute capacity, which is measured in CUDA cores for NVIDIA cards or stream processors for AMD. And then the second is memory bandwidth and capacity, which is crucial for handling large neural networks and large LLMs. And then third of course, is your budget, because top tier GPUs can range from just a few thousands to a few tens of thousands of dollars. So in my case, as you see in the screen, I…
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Learning objectives1m 27s
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Home-based vs. cloud-based AI labs and sandboxes7m 4s
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Choosing the right hardware (GPUs, CPUs, memory, etc.)10m 9s
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Building or buying prebuilt systems3m 53s
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Choosing operating systems: Linux, Windows, or macOS4m 21s
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Surveying essential software4m 41s
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Introducing Hugging Face3m 42s
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Introducing Ollama3m 38s
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Installing Ollama6m 24s
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Ollama integrations14m 42s
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Exploring the Ollama REST API3m 3s
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Introducing retrieval augmented generation (RAG)5m 24s
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Leveraging RAGFlow13m 56s
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