We introduce a new method to guide flow matching models. Our approach, which we call probe guidance, uses the frozen internal states of an existing diffusion model to construct a guidance signal. This works using a similar principle as autoguidance, but eliminates the need for an additional forward pass at inference time and provides a …
This post is co-written with Mauro Rallo and Patrick van der Plas from HEMA. When engineers at HEMA needed an answer, they went portal-hopping, navigating disconnected wikis, service catalogs, and IT portals to find it. To turn that friction into instant answers, the 100-year-old Dutch retailer built a knowledge layer on Amazon Bedrock AgentCore. HEMA …
Read more “From portal-hopping to instant answers: HEMA’s journey with MCP and Amazon Bedrock”
GPT-6 Sol and GPT-6 Luna are now generally available on Amazon Bedrock, giving you more options to match intelligence and efficiency to each workload. The value of AI at scale depends on two dimensions: what a model can do and how often you can put it to use. Greater intelligence expands the complexity a model …
Read more “Bring more intelligence to everyday work with GPT-6 Sol and GPT-6 Luna on Amazon Bedrock”
Today, we are announcing that xAI’s Grok 4.6 is available in Amazon Bedrock, adding a frontier model built for long-running agents, coding, and knowledge work to the Bedrock model catalog. Grok 4.6 launched on Bedrock on August 18, 2026. It offers a 500K token context window and supports configurable reasoning effort at four levels: low, …
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Activation steering has emerged as a powerful method for guiding the behavior of generative models towards desired outcomes such as toxicity mitigation. However, most existing methods apply interventions uniformly across all inputs, degrading model performance when steering is unnecessary. We introduce Dynamically Scaled Activation Steering (DSAS), a method-agnostic steering framework that decouples when to steer …
Introducing composable, module system native and agent friendly command line tools for modern Java development By Danny Thomas, JVM Ecosystem Team Recent work on the Java language to pave the on-ramp has made it easier than ever to start a Java program and evolve it using the full language and platform. At the end of …
Generative AI inference is uniquely hard: models are tens to hundreds of gigabytes, latency requirements are measured in tokens per second, cold starts can span multiple minutes as containers and weights transfer, GPU capacity is constrained, and traditional monitoring tools expose none of the token-level signals that matter in production. Amazon SageMaker AI offers customers …
Read more “Amazon SageMaker Inference: 2026 year-to-date launches in review”
AI is accelerating software development at an unprecedented pace. But as code generation scales, so do the challenges of securing the code, especially emerging AI-based vulnerability exploitations. To meet these challenges, the Google AI and Infrastructure team is transforming how we approach security. In this article, we discuss new AI-native agentic methods that we’ve developed …
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A central goal of autonomous reinforcement learning is continuous policy training without external resets. However, existing paradigms largely depend on underlying environmental reversibility, a property absent in real world manipulation, where events such as pushing objects off tables or spilling granular substances cannot be undone. We introduce REVERSAL-BENCH, a benchmark that controls reversibility via a …
Hiring at scale in industries such as retail, logistics, hospitality, and others has its fair share of challenges. Recruiting teams are expected to fill hundreds of roles within tight timelines, often with limited capacity and with tools that weren’t designed to seamlessly work together. As a result of this, applications pile up, phone screens get …
Read more “Reduce time-to-hire for quality candidates with AI-powered Amazon Connect Talent”