AppLovin, once a near‑bankrupt stock, rebounded by reshaping mobile advertising into a performance‑based, AI‑driven platform that optimizes lifetime value, leverages deep‑learning models like Axon 2, and executes bold financial moves, turning ad spend into a multi‑billion‑dollar profit engine.
This article explains how Alibaba Mama’s advertising engine adopted a Serverless, Graph‑as‑a‑Service (GaaS) model to unify budgeting across multiple ad lands, align development‑to‑delivery granularity with graph structures, and dramatically improve testing, experimentation, and production release efficiency.
This article summarizes Guo Bin's DTCC2022 talk on Google Cloud Bigtable, detailing its architecture, performance characteristics, scaling strategies, and how the fully managed NoSQL service powers low‑latency real‑time bidding and user profiling in modern advertising technology.
This article analyzes the shift from coarse, budget‑driven ad placements to Real‑Time API (RTA) driven precision advertising, detailing why RTA is needed, its technical and data requirements, integration challenges, and practical use cases such as acquisition, retargeting, dynamic product ads, frequency capping, quality scoring, and automated creative optimization.
This presentation by Huawei federated‑learning expert Liu Lu explains how federated learning can be applied to the advertising ecosystem, covering business background, multi‑perspective conversion processes, core ad‑ranking algorithms, vertical and horizontal federated learning architectures, and the associated attack‑defense techniques.
This article explains why Tubi rewrote its legacy PHP ad platform, how it adopted Scala, Akka, and Reactive Streams to model the ad request lifecycle as a reactive stream, and details the first three processing steps—parsing, enrichment, and precise filtering—along with sample Scala filter code.
