Formula 1® (F1) engages an audience of over 800 million fans globally across digital platforms, F1 TV, social media, ticketing, and merchandise year-round. Races happen every two weeks. Fan engagement windows are measured in minutes and commercial decisions need to move at the speed of the grid. Behind the scenes, F1’s marketing technology (MarTech) platform, Customer …
For too long, enterprises with legacy mainframe estates have been faced with a high-stakes dilemma: continue maintaining their mainframes, essentially kicking the modernization can down the road (they know they will need to deal with it eventually), or perform a dangerous “big bang” migration with many unknowns and risks. At Google Cloud, we propose an …
by Aarti Laddha, Richard Diaz-Cool, Rishika Idnani, Venkatesh Selveraj Netflix supports a vast and evolving set of features and content types, ranging from 4K streaming and immersive audio to live streaming and cloud gaming, across a diverse ecosystem of devices. However, not all devices are created equal. Hardware limitations such as available RAM, CPU cores, …
As organizations embrace AI-powered analytics, the value of a natural language (Text2SQL) answer is only as good as the business context behind it. We’re entering a phase where semantic richness (table and column descriptions, and relationships) must flow directly from where it’s authored in upstream data catalogs and semantic tools into the AI products that …
Read more “Announcing the Agentic Catalog Experience in Amazon Quick”
At Google, AI is a soup-to-nuts endeavor. Obviously, we make leading AI models like Gemini and Nano Banana. We incorporate AI into the tools you use every day (think Gmail, BigQuery, AlloyDB, Google Cloud Code and Google Cloud Assist). We make software frameworks to help you build with AI, like Gemini Enterprise Agent Platform, JAX, …
Read more “What’s new in AI infrastructure and orchestration this month”
While UMAP is widely used for exploring high-dimensional data, typical workflows focus on its lower-dimensional embedding, largely overlooking the rich k-nearest-neighbor (kNN) graph that UMAP constructs internally. This graph encodes the data manifold in its original high-dimensional space, before the distortion that UMAP’s 2D projection introduces. We demonstrate the untapped potential of this internal representation, …
Read more “Dimensionality Reduction Meets Network Science: Sensemaking on UMAP’s kNN Graph”
Authors: Ying Li, Arjun Rao, Shradha Sehgal Introduction Recommendations sit at the heart of the Netflix experience. Our current production models rely on thousands of hand‑crafted features over users, items, and interactions, along with specialized architectures for sequence modeling, feature interactions, and multi‑task objectives. This stack has evolved over many years to support diverse content types …
Read more “GenRec: Towards LLM-Native Recommendation at Netflix”
Open weight models have become powerful enough to handle complex tasks such as multi-step agentic workflows, advanced reasoning, and long-horizon coding. However, as these models grow in capability, they also grow in size and hosting multi-trillion parameter architectures requires purpose-built infrastructure, high-end GPU compute, and optimized serving frameworks. On July 27, 2026, Moonshot AI released …
In today’s agentic era, modern cloud applications are evolving from a set of passive tools to fleets of autonomous digital workers that reason, plan, and take action across a wide range of tasks. For platform engineering teams designing these environments, the simplest approach is often to deploy an agent on to an open-source framework like …
Read more “Do more with less: How GKE can reduce your cost per agent by 75%”
Siri Expressive Voices synthesize rich, configurable speech in real time and entirely on device, powered by AFM 3 Core Advanced, Apple’s most powerful on-device foundation model. This work presents the memory-efficient audio synthesis architecture behind that capability: a detokenizer that converts the semantic audio tokens emitted by the foundation model into high-fidelity audio within the …
Read more “Memory Efficient Audio Synthesis with Decoupled Temporal Depth Diffusion Transformers”