Comparison
Deep Learning vs Foundation Model
Deep Learning and Foundation Model are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Deep Learning
Deep Learning comes up when the question is fundamentally about foundations.
Image recognition models like ResNet.
When you would reach for Foundation Model
Foundation Model comes up when the question is fundamentally about foundations.
GPT-4 used by tens of thousands of applications via API.
Frequently asked
What is the difference between Deep Learning and Foundation Model?
Deep Learning: Deep learning is machine learning using neural networks with many layers ("deep" = many layers). It powers nearly every recent breakthrough in AI, including LLMs and image generators. Foundation Model: A foundation model is a single large model pretrained on broad data that can be adapted to many downstream tasks. LLMs are the most common type.
When should I use Deep Learning vs Foundation Model?
Deep Learning is the right concept when you are focused on foundations. Foundation Model applies when you are focused on foundations.
Are Deep Learning and Foundation Model the same thing?
No. Deep Learning is foundations; Foundation Model is foundations. They are related but address different parts of the AI stack.