Applied AI
Real-world applications of AI and ML across industries: computer vision, NLP, robotics, healthcare, autonomous systems.
Sub-topics
Enabling machines to interpret visual information. From edge detection to CNNs to vision transformers. Applications in autonomous driving, medical imaging, and AR.
AI for understanding and generating human language. Evolved from rule-based systems through statistical methods to transformer-based models that achieve near-human performance.
Converting spoken language to text. Evolved from HMMs to deep learning. OpenAI's Whisper (2022) provides robust multilingual transcription as an open model.
Integrating AI with physical systems. Combines computer vision, RL, and planning for manipulation, locomotion, and human-robot interaction.
Algorithms predicting user preferences. Collaborative filtering, content-based filtering, and deep learning approaches power Netflix, Spotify, YouTube, and Amazon recommendations.
Self-driving cars combining computer vision, sensor fusion, and planning. Waymo, Tesla, and Cruise represent different approaches (LiDAR+HD maps vs pure vision).
Using ML to accelerate pharmaceutical research. Molecular property prediction, generative chemistry, and virtual screening reduce time and cost of drug development.
DeepMind's AlphaFold2 (2020) solved protein structure prediction with atomic accuracy. Won CASP14 by a massive margin. Released structures for 200M+ proteins.