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This article introduces Variational Autoencoders (VAEs), compares them with GANs, explains the underlying variational inference principle, and details how VAEs are trained using the evidence lower bound, complemented by visual diagrams and key equations.
This article introduces the fundamental architecture of Graph Neural Networks, traces their evolution from early 2005 concepts through spatial and spectral models, explains why GNNs are gaining attention, and poses key questions about graph spectrum, Fourier transforms, and spectral‑domain graph convolutions.
This article explains how Long Short‑Term Memory (LSTM) networks overcome the long‑term dependency problem of traditional recurrent neural networks by using gated cells that store and retrieve information over extended periods, and highlights their widespread applications in speech recognition, machine translation, image captioning, and beyond.
This article traces the evolution of convolutional neural networks from the pioneering AlexNet through VGG, Inception, ResNet, Inception‑v4, Inception‑ResNet and ResNeXt, highlighting architectural innovations, performance gains, and the underlying biological inspirations that shaped modern deep learning models.
This article explains how Hulu tackled the trade‑off between accuracy and diversity in its massive video recommendation system by applying Determinantal Point Processes and an efficient incremental greedy algorithm, achieving 100× speed‑ups without sacrificing recommendation quality.
In this interview, Hulu’s technology director Frank Lan explains Hulu’s proprietary video codec testing process, evaluates the authority of MSU’s annual codec benchmark, offers practical advice for interpreting MSU reports, and discusses the rise of domestic Chinese codec providers and the scarcity of other neutral evaluation platforms.
This article traces the history of machine translation—from early rule‑based systems through statistical models that leveraged parallel corpora, to modern neural network approaches—while highlighting current applications, challenges, and future directions in the field.
This article explores how autonomous driving, driven by artificial intelligence, can dramatically improve safety, convenience, efficiency, and reduce congestion, outlines the five SAE levels, describes the three-layer control architecture, and explains key AI tools such as occupancy grids and cones of uncertainty that enable precise trajectory planning.
This article traces the history of game artificial intelligence—from early MiniMax chess programs and classic board‑game breakthroughs like Deep Blue, through AlphaGo’s triumph over human champions, to the self‑learning AlphaGo Zero—while explaining why games serve as a vital testbed for modern AI research.
This article explains Hulu's comprehensive approach to streaming quality optimization, covering the video system architecture, business model, the distinction between QoS and QoE, key performance metrics, adaptive bitrate algorithms, data‑driven workflows, offline validation, online A/B testing, and the measurable improvements achieved across multiple platforms.
