FAANG - Robotic Content

Introducing Web Search on Amazon Bedrock for foundation model grounding

by AI Generated Robotic ContentFAANG August 5, 2026Comments are Disabled

When a foundation model needs to answer a question about last week’s earnings call, yesterday’s regulatory change, or this morning’s weather forecast, it needs knowledge it was never trained on. Grounding the model in current web knowledge closes that gap – whether it’s powering chatbots, coding assistants, CLI tools, or enterprise applications, grounding helps answer …

How Deutsche Bank unlocked agility with an API-ready ecosystem

by AI Generated Robotic ContentFAANG August 5, 2026Comments are Disabled

When people think about digital transformation in banking, they often focus on the visible results: mobile apps and new digital services. But there’s an invisible infrastructure making all these services possible: APIs. At Deutsche Bank, we recognized that APIs aren’t just technical plumbing; they’re the nervous system of modern banking. A few years ago, our …

Understanding Alignment in Multimodal LLMs: A Comprehensive Study

by AI Generated Robotic ContentFAANG August 4, 2026Comments are Disabled

Preference alignment has become a crucial component in enhancing the performance of Large Language Models (LLMs), yet its impact in Multimodal Large Language Models (MLLMs) remains comparatively underexplored. Similar to language models, MLLMs for image understanding tasks encounter challenges like hallucination. In MLLMs, hallucination can occur not only by stating incorrect facts but also by …

From weeks to minutes: How Formula 1® uses agentic AI on AWS to accelerate data operations

by AI Generated Robotic ContentFAANG August 4, 2026Comments are Disabled

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 …

Real-world mainframe modernization with AI: A safe, scalable path from mainframe to cloud

by AI Generated Robotic ContentFAANG August 4, 2026Comments are Disabled

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 …

Modeling Device Capabilities for Analytics

by AI Generated Robotic ContentFAANG August 1, 2026Comments are Disabled

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, …

Announcing the Agentic Catalog Experience in Amazon Quick

by AI Generated Robotic ContentFAANG August 1, 2026Comments are Disabled

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 …

What’s new in AI infrastructure and orchestration this month

by AI Generated Robotic ContentFAANG August 1, 2026Comments are Disabled

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, …

Dimensionality Reduction Meets Network Science: Sensemaking on UMAP’s kNN Graph

by AI Generated Robotic ContentFAANG July 31, 2026Comments are Disabled

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, …

GenRec: Towards LLM-Native Recommendation at Netflix

by AI Generated Robotic ContentFAANG July 31, 2026Comments are Disabled

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 …