Deep Learning Is Applied Topology
a year ago
- #AI
- #DeepLearning
- #Topology
- Topology is the study of surfaces and their properties under deformation without tearing or puncturing.
- AI and deep learning can be understood through topological concepts, where neural networks manipulate data in high-dimensional spaces.
- Neural networks act as 'topology generators,' transforming data into semantically meaningful high-dimensional manifolds.
- Embedding vectors represent concepts mathematically, allowing operations like 'king' - 'man' + 'woman' = 'queen.'
- Instruction tuning and RLHF help shift models from next-word prediction to reasoning by refining their outputs.
- Deepseek R1 explores reinforcement learning to improve reasoning without human-curated traces, though it still has limitations.
- Diffusion models could potentially generate trained neural networks from text prompts, speeding up model initialization.
- Understanding embedding spaces and topology is key to grasping how neural networks work and reason.