AI

Turning a library of aerial imagery into a natural-language-searchable knowledge base is a problem that touches every industry that relies on geospatial data — insurance, real estate, government, infrastructure, and agriculture. The traditional path requires either manual tile-by-tile inspection or training a bespoke computer vision model for each new question. Multimodal embeddings, large language model […]

With ComfyUI workflows on Amazon SageMaker AI processing jobs, you can automate content generation at scale. For enterprises, every delay or misstep in creating compelling multimedia assets can mean lost sales, faded brand relevance, or missed marketing deadlines. When a product launch deadline looms or a seasonal promotion needs urgent assets, waiting for designers to

Big Tech is throwing big money into data center buildouts. As national opposition to the facilities grows, some workers are beginning to question whether it’s worth it.

Sure, anyone can use OpenAI’s chatbot. But with smart engineering, you can get way more interesting results.

The new Siri AI is conversational, omnipresent, and actually helpful.

Companies working at the frontier of aerospace, energy, and computing are constantly looking for new materials to improve performance. But in order to understand how those materials will actually behave once they’re inside rockets or on computer chips, companies first have to make the material and then test it. That’s because even the most powerful

AI agents are changing how organizations find and act on information, but they share one structural limitation: their knowledge is frozen at training time. When you ask an agent that relies only on its training data about today’s stock price, a sports score, or a release that shipped an hour ago, it can’t respond. Web

Amazon Quick and Adobe Marketing Agent help marketing teams access campaign insights within governed conversations in seconds. Marketers can ask questions about campaign performance, audiences, journeys, campaign conflicts, and content performance in natural language. Amazon Quick provides the chat experience and action orchestration. Adobe provides marketing-domain analysis to the approved data sources behind those questions.

Monitoring and troubleshooting generative AI inference endpoints operating at scale is challenging. When your large language model (LLM) endpoint’s P99 latency spikes, you must determine in minutes whether the root cause is GPU memory pressure, a saturated KV cache, unbalanced traffic across Availability Zones, or an auto scaling policy that hasn’t triggered. The shift from