A property of functions is called location-invariant (or symmetric) if it can be characterized in terms of the frequencies in which each value occurs in the function, regardless of the locations in which each value occurs. It is known that the (query) complexity of testing location-invariant properties of functions is closely related to the (sample) …
Knowledge bases that ground agents and generative AI applications over your enterprise data are hard to build at scale. Teams typically stitch together connectors, parsers, vector stores, knowledge graphs, and retrieval logic, then operationalize all of it for production. Each piece brings its own challenges. You must decide which data sources to connect and how …
Read more “Build enterprise search for agents with Amazon Bedrock Managed Knowledge Base”
For the second consecutive year, Google has been named a Leader in the Gartner® Magic Quadrant™ for Conversational AI Platforms. Google received the furthest and highest in positioning on the “Vision” and “Execution” axes and is now ranked #1 in three out of four Critical Capabilities Use Cases. We believe this recognition reflects our continued …
Visual generative models (e.g., diffusion models) typically operate in compressed latent spaces to balance training efficiency and sample quality. In parallel, there has been growing interest in leveraging high-quality pre-trained visual representations—either by aligning them inside VAEs or directly within the generative model. However, adapting such representations remains challenging due to fundamental mismatches between understanding-oriented …
Read more “One Layer Is Enough: Adapting Pretrained Visual Encoders for Image Generation”
Document processing in real estate is complex and highly manual, impacting critical business decisions at scale, making it ripe for automation. Built Technologies, a real estate finance software provider, processes over $500B in real estate projects. The company deployed an AI-powered document processing engine on Amazon Bedrock and the AWS Intelligent Document Processing (IDP) Accelerator. …
Editor’s note: Today we hear from IDC on the results of its 2026 AI in Networking Special Report Survey exploring the enterprises’ concerns about networking infrastructure to support the rise of agentic AI in their organizations. The survey was sponsored by Google Cloud. Enterprises are moving quickly on AI pilots, but the move from pilot …
Read more “IDC: Why the right networking approach is foundational to agentic AI”
Proactive agents that anticipate user needs and autonomously execute tasks hold great promise as digital assistants, yet the lack of realistic user simulation frameworks hinders their development. Existing approaches model apps as flat tool-calling APIs, failing to capture the stateful and sequential nature of user interaction in digital environments and making realistic user simulation infeasible. …
Your prospects leave trails across multiple sources: a founder asks “What should I use for X?” in r/SaaS while their product launches on Hacker News. Stack Overflow questions spike. A GitHub repo crosses 2,400 stars. Each signal alone is noise, but correlated across sources, they reveal a prospect ready to buy. Multi-agent systems built with …
Read more “Multi-agent social intelligence with Strands Agents and Amazon Bedrock”
For years, we’ve built with a clear priority: putting the practical needs of the enterprise first. Long before generative AI dominated the headlines, we were focused on building the global infrastructure, security frameworks, and data platforms that power the world’s largest organizations. We’ve always believed that technology is only as good as its reliability, security, …
By Parth Jain, Rakesh Sukumar, Yingwu Zhao, Renzo Sanchez-Silva & Nathan FisherA deep dive into the engineering challenges of building a real-time service dependency map at Netflix scale: from streaming architectures and distributed aggregation pipelines to time-travel queries and the methodology that made it work. Introduction In our first post, we introduced the problem: engineers at …
Read more “Building Service Topology at Scale: Architecture, Challenges, and Lessons Learned”