Category Added in a WPeMatico Campaign
Today’s reality is agentic – software that can reason, plan, and act on your behalf to execute complex workflows. To meet this moment, we are excited to open the Gemini Enterprise Agent Ready (GEAR) learning program to everyone. As a new specialized pathway within the Google Developer Program, GEAR empowers developers and pros to build …
Today, we are publishing a new open source sample chatbot that shows how to use feedback from Automated Reasoning checks to iterate on the generated content, ask clarifying questions, and prove the correctness of an answer. The chatbot implementation also produces an audit log that includes mathematically verifiable explanations for the answer validity and a …
Read more “Automated Reasoning checks rewriting chatbot reference implementation”
The composition of objects and their parts, along with object-object positional relationships, provides a rich source of information for representation learning. Hence, spatial-aware pretext tasks have been actively explored in self-supervised learning. Existing works commonly start from a grid structure, where the goal of the pretext task involves predicting the absolute position index of patches …
Read more “How PARTs Assemble into Wholes: Learning the Relative Composition of Images”
Today, we’re announcing structured outputs on Amazon Bedrock—a capability that fundamentally transforms how you can obtain validated JSON responses from foundation models through constrained decoding for schema compliance. This represents a paradigm shift in AI application development. Instead of validating JSON responses and writing fallback logic for when they fail, you can move straight to …
Read more “Structured outputs on Amazon Bedrock: Schema-compliant AI responses”
As generative AI moves from experimentation to production, platform engineers face a universal challenge for inference serving: you need low latency, high throughput, and manageable costs. It is a difficult balance. Traffic patterns vary wildly, from complex coding tasks that require processing huge amounts of data, to quick, chatty conversations that demand instant replies. Standard …
Read more “How we cut Vertex AI latency by 35% with GKE Inference Gateway”
This is a guest post co-written with David Meredith and Josh Zacharias from Associa. Associa, North America’s largest community management company, oversees approximately 7.5 million homeowners with 15,000 employees across more than 300 branch offices. The company manages approximately 48 million documents across 26 TB of data, but their existing document management system lacks efficient …
At Google Cloud, we’re committed to providing customers with the leading selection of models to build and scale production-ready AI apps and agents on a platform optimized for performance, trust, and global scale. Today, we’re further expanding Vertex AI’s curated collection of models with the addition of Anthropic’s newest release: Claude Opus 4.6. Claude Opus …
Marketing teams face major challenges creating campaigns in today’s digital environment. They must navigate through complex data analytics and rapidly changing consumer preferences to produce engaging, personalized content across multiple channels while maintaining brand consistency and working within tight deadlines. Using generative AI can streamline and accelerate the creative process while maintaining alignment with business …
To advance Polar code design for 6G applications, we develop a reinforcement learning-based universal sequence design framework that is extensible and adaptable to diverse channel conditions and decoding strategies. Crucially, our method scales to code lengths up to 2048, making it suitable for use in standardization. Across all (N,K)(N, K)(N,K) configurations supported in 5G, our …
Read more “A Reinforcement Learning Based Universal Sequence Design for Polar Codes”
This post is cowritten with James Luo from BGL. Data analysis is emerging as a high-impact use case for AI agents. According to Anthropic’s 2026 State of AI Agents Report, 60% of organizations rank data analysis and report generation as their most impactful agentic AI applications. 65% of enterprises cite it as a top priority. …