AI Foundations
Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.
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Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.
Use AI productively while protecting privacy, checking outputs, and preserving human accountability.
Evaluate workplace use cases, run safe pilots, measure value, and communicate changes responsibly.
Analyze AI systems through rights, equity, governance, safety, and public-interest outcomes.
Understand language models, retrieval, agents, evaluation, cost, and deployment safeguards through practical system design.
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A Hidden Markov Model describes a system that moves through hidden states you cannot see directly, emitting observable outputs along the way.
TechnicalA Gaussian Process is a flexible, nonparametric way to model functions that comes with built-in uncertainty estimates.
IndustriesAI is moving surgical robots from teleoperated tools that simply mirror a surgeon's hands toward systems that can perceive tissue, guide instruments…
IndustriesOphthalmology is one of AI's biggest medical success stories because the eye is image-rich and easy to photograph.
IndustriesSkin is the body's largest, most visible organ, so dermatology is a natural fit for image-based AI.
CompaniesDoubao is ByteDance's family of large language models and consumer AI assistant, built by the company behind TikTok and Douyin.
CompaniesYi is a family of open and commercial large language models from 01.AI, the Chinese startup founded by AI pioneer Kai-Fu Lee.
CompaniesCommand is Cohere's family of large language models built specifically for enterprise use, with a strong focus on retrieval-augmented generation, tool use…
Audio AISoundStream is Google's end-to-end neural audio codec that compresses speech and music to extremely low bitrates while preserving quality.
Audio AIEnCodec is Meta's high-fidelity neural audio codec that compresses speech and music at very low bitrates with quality rivaling far heavier formats.
Audio AIResidual vector quantization (RVQ) is the technique that turns continuous audio embeddings into a compact stack of discrete codes by repeatedly quantizing…
Audio AIECAPA-TDNN is a neural network architecture that turns any speech clip into a compact 'voiceprint' embedding, enabling machines to tell who is speaking.
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