Topic 23: What is LLM Inference, it's challenges and solutions for it

A trained Large Language Model (LLM) holds immense potential, but inference is what truly activates it – It’s the moment when theory meets practice and the model springs to life – crafting sentences, distilling insights, bridging languages. While much of the focus used to be on training these models, attention has shifted to inference, the phase where they deliver real-world value. This step is what makes LLMs practical and impactful across industries.

In today’s episode, we will cover:

• “15 minutes with a researcher” – our new interview series – about SwiftKV, an inference optimization technique

• To the basics: What is LLM Inference?

• Challenges in LLM Inference

• Solutions to Optimize LLM Inference

  • Model Optimization

  • Hardware Acceleration

  • Inference Techniques

  • Software Optimization

  • Efficient Attention Mechanisms

• Open-Source Projects and Initiatives

• Impact on the Future of LLMs

• Conclusion

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