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Prompt caching in Amazon Bedrock can reduce your input token costs by up to 90 percent when you repeatedly send the same context to foundation models, based on Amazon Bedrock prompt caching pricing. Without caching, a 10,000-token contract sent alongside 50 user questions means 500,000 input tokens billed at full price for content the model …
Read more “Optimizing cost and latency with Amazon Bedrock prompt caching”
AI agents now run in production at a scale of billions of operations a day, and a recurring architectural pattern has surfaced: agents need a compute scratch pad. Not only for coding tasks, but for data aggregation, analysis, verification, and any workflow where semantic reasoning alone isn’t enough. Abnormal AI, a behavioral security service that …
Read more “Abnormal AI: Amazon Bedrock AgentCore for agentic email security at scale”
Sign language processing systems have traditionally operated at the sentence level, ignoring critical discourse phenomena fundamental to sign language comprehension. We introduce DiscoSign, a computational approach for discourse-aware text to sign language gloss translation grounded in linguistic research. We address three key phenomena within our modular Large Language Model (LLM)-based translation framework: (i) spatial coreference …
Read more “DiscoSign: Discourse-Aware Text to Sign Language Gloss Translation”
Multi-agent systems in production experience issues in ways that traditional monitoring misses. For example, the agent can’t invoke its foundation model (FM) and returns an empty response. This could be because of a missing AWS Identity and Access Management (IAM) permission on an agent’s execution role that doesn’t throw a 500 error. A supervisor agent …
Read more “Monitoring production agent lifecycle with AWS DevOps Agent and AgentCore Evaluations”
Quick note — The Loop’s first session is today, 4:30 PM PDT, live on Zoom. Free, monthly, and genuinely hands-on: what building an AI agent actually looks like, why the internet is shifting from static information to something built for agents and people, and what that shift means for anyone still thinking in old-SEO terms. This is for you …
Read more “Reminder: Live Today — Building AI Agents, The Loop”
When you build an application on top of a large language model (LLM), the prompt you send to the model typically has two parts. There’s a fixed part that sets up context (instructions, reference documents, conversation history) and a variable part that contains the actual user input. Take a customer service bot as an example. …
Read more “Reduce LLM latency with prefix-aware routing on Amazon SageMaker Inference”
On August 12, 2026, Alibaba’s Qwen team released Qwen3.8-2.4T-A95B. This is the first time a Qwen-Max-class model has been made available as open weights. With 2.4 trillion total parameters (95 billion activated per token), a hybrid linear-plus-full-attention architecture, and native context up to 262K tokens (extensible to 1M), Qwen3.8 targets the most demanding agentic and …
Read more “Deploying Qwen3.8-2.4T-A95B on Amazon SageMaker HyperPod with vLLM”
We are excited to share that Gartner has named Google a Leader in its inaugural 2026 Magic Quadrant for Enterprise AI Assistants. In this comprehensive evaluation of top enterprise AI assistant vendors, Gartner placed Google in the Leaders quadrant for its evaluation across both Completeness of Vision and Ability to Execute. Gemini Enterprise helps organizations …
Read more “Google is a Leader in the 2026 Gartner® Magic Quadrant™ for Enterprise AI Assistants”
GPT-6 Astra from OpenAI brings greater depth and judgment to your most demanding tasks and runs on the Amazon Bedrock inference engine built for high performance, security, and scale. Organizations are already running AI agents that write code, analyze data, and automate complex workflows at production scale on Amazon Bedrock. GPT-6 Astra raises the potential …
Read more “Take on your most ambitious work with GPT-6 Astra on Amazon Bedrock”
When building consumer-facing generative AI applications, balancing high generation quality with fast response times across diverse media types, can be challenging. KDDI, a major telecommunications carrier in Japan, tackled this challenge head-on when they developed Buffmee, their consumer Retrieval-Augmented Generation (RAG) app. Buffmee is an interactive AI service built on the concept of ‘AI that …
Read more “How KDDI built Buffmee, a faster, reliable consumer RAG app”