Continuously Augmented Discrete Diffusion model for Categorical Generative Modeling

Standard discrete diffusion models treat all unobserved states identically by mapping them to an absorbing [MASK] token. This creates an ‘information void’ where semantic information that could be inferred from unmasked tokens is lost between denoising steps. We introduce Continuously Augmented Discrete Diffusion (CADD), a framework that augments the discrete state space with a paired …

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Implement automated smoke testing using Amazon Nova Act headless mode

Automated smoke testing using Amazon Nova Act headless mode helps development teams validate core functionality in continuous integration and continuous delivery (CI/CD) pipelines. Development teams often deploy code several times daily, so fast testing helps maintain application quality. Traditional end-to-end testing can take hours to complete, creating delays in your CI/CD pipeline. Smoke testing is …

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Announcing MCP support in Apigee: Turn existing APIs into secure and governed agentic tools

Today, we expanded Google’s support for Model Context Protocol (MCP) with the release of fully-managed, remote MCP servers, giving developers worldwide consistent and enterprise-ready access to Google and Google Cloud services. This includes support for MCP in Apigee, which makes it possible for agents to use your secure, governed APIs and custom workflows cataloged in …

Semantic Mastery: Enhancing LLMs with Advanced Natural Language Understanding

Large language models (LLMs) have greatly improved their capability in performing NLP tasks. However, deeper semantic understanding, contextual coherence, and more subtle reasoning are still difficult to obtain. The paper discusses state-of-the-art methodologies that advance LLMs with more advanced NLU techniques, such as semantic parsing, knowledge integration, and contextual reinforcement learning. We analyze the use …

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Real-world reasoning: How Amazon Nova Lite 2.0 handles complex customer support scenarios

Artificial intelligence (AI) reasoning capabilities determine whether models can handle complex, real-world tasks beyond simple pattern matching. With strong reasoning, models can identify problems from ambiguous descriptions, apply policies under competing constraints, adapt tone to sensitive situations, and provide complete solutions that address root causes. Without robust reasoning, AI systems fail when faced with nuanced …

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From adoption to impact: Putting the DORA AI Capabilities Model to work

The 2025 State of AI-assisted Software Development report revealed a critical truth: AI is an amplifier. It magnifies the strengths of high-performing organizations and the dysfunctions of struggling ones. While AI adoption is now near-universal, with 90% of developers using it in their daily workflows, success is not guaranteed. Our cluster analysis of nearly 5,000 …

The AI that scored 95% — until consultants learned it was AI

Presented by SAP When SAP ran a quiet internal experiment to gauge consultant attitudes toward AI, the results were striking. Five teams were asked to validate answers to more than 1,000 business requirements completed by SAP’s AI co-pilot, Joule for Consultants — a workload that would normally take several weeks. Four teams were told the …

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Let’s make some realistic humans: Now with Z-Image [Tutorial] – More examples and Info in Comments

This is a refresh of my tutorial on [how to make realistic](https://www.reddit.com/r/StableDiffusion/comments/10yn8y7/lets_make_some_realistic_humans_tutorial/) people, and [how to make realistic people with SDXL](https://www.reddit.com/r/StableDiffusion/comments/16opi4h/lets_make_some_realistic_humans_now_with_sdxl/), and [let’s make realistic humans with flux](https://www.reddit.com/r/StableDiffusion/comments/1enrkyz/lets_make_some_realistic_humans_now_with_flux/), but this time we will be using the Z Image model.. *Special Note = imgpile currently has something going on, so many of the old SDXL images …