11. Stop guessing auto scaling targets for TTS on Amazon SageMaker AI A traffic spike hits your self-hosted text-to-speech (TTS) endpoint, and requests start queueing. Latency climbs past your service level objective (SLO) right when the most callers 10/23 00:30 ♡
12. How Rescale built an AI triage agent with Strands Agents and AI-DLC Every engineering team knows the ritual, and Rescale was no exception. A nightly test suite fails. An on-call engineer pulls the logs, classifies the root cause, and routes it 10/23 00:25 ♡
13. Securing Quick access from corporate networks with AWS PrivateLink When enterprise data sits behind a corporate firewall or in a private on-premises data center, there’s no direct network path from AWS, even though the AI agents and dashboards in 10/22 07:38 ♡
14. 5 production challenges in multi-agent systems and how Deep Insight solved them Building a multi-agent system is now pretty straightforward. Taking it to production is where the real challenges begin. Thanks to open source frameworks and cloud services, you ca 10/22 07:36 ♡
15. Adaptive agentic intelligence framework using Strands Agents Organizations building AI agents face a common challenge: Every request, whether a routine status check or complex analysis, typically gets routed to a single large, expensive mode 10/22 05:23 ♡
16. Train Qwen3 on AWS Trainium with torchtitan Using torchtitan on AWS Trainium means using it the way you always have. TorchNeuron registers Trainium as a native PyTorch device, which lets torchtitan use it through standard Py 10/22 04:00 ♡
17. How U.S. Hunger connects leaders and data using Amazon Quick For U.S. Hunger, feeding families takes more than delivering food to them. It takes understanding the people behind each request, the pressures they face, and the business that mak 10/22 03:19 ♡
18. Beyond the KV cache: Training and serving i14’s Laplace 3B linear attention model on AWS Trainium2 with native PyTorch Most large language models (LLMs) use transformer architectures with softmax attention. During inference, their key-value (KV) cache grows with the conversation or document context 10/21 05:14 ♡
19. Workflow context for AI agents with Smartsheet MCP on AWS AI agents are most useful when they can act on the real work happening across your organization. Running projects and operations involves complex, cross-functional tasks such as up 10/21 01:59 ♡
20. From data to decisions: Conversational supply chain intelligence with Amazon Quick and Amazon Bedrock AgentCore Giving supply chain teams direct access to the systems behind their decisions. Every supply chain generates constant signals: orders in approval, shifting lead times, slowing ports 10/21 01:52 ♡
