Chinese lab just made AI development stupid cheap with reinforcement learning that automates human feedback. Small models eating GPT-4 for breakfast.
Breaking down LLMs into representation, model, and reasoning modules. Finally addressing hallucinations and making AI actually trustworthy instead of just impressive.
AI pair programming isn't just autocomplete anymore. It's thinking alongside you, predicting what you need before you know it. The IDE became intelligent.
Text, images, audio, video—all in one model. The boundary between different AI systems is dissolving. Everything becomes one conversation.
Chain rule applied to neural networks. The algorithm that makes learning possible. Gradients flowing backward through computation graphs.
Universal approximation theorem in practice. Neural networks can approximate any function given enough parameters and data.