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OnTrack: The PCB Design Podcast
Edge Devices and LLMs: What's Ahead for AI
Jun 12, 2024
Jan Jongboom, co-founder of Edge Impulse, discusses the evolution of GPT models, importance of edge computing, reducing LLM sizes for deployment on edge devices, practical AI applications, and challenges of running large language models on GPUs in this informative podcast.
41:53
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Quick takeaways
- Reducing LLM size enhances edge device deployment efficiency.
- Synthetic data aids in training AI models more cost-effectively and accurately.
Deep dives
Neural Networks Evolution from GPT-2 to GPT-4
The podcast discusses the evolution of neural networks from GPT-2 to GPT-4, highlighting the significant advancements in language processing over five years. Despite the efficiency improvement, GPT-4 retains the fundamental architecture of its predecessor, raising concerns about scaling down for edge devices. The increase in parameter count poses challenges for deploying advanced models on smaller devices, prompting the need for new architectures or parameter reduction methods.
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Discover
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