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ExternalAI
AWS Machine Learning Blog

ScienceSoft’s HIPAA-compliant AI voice scheduler built on AWS

In this post, you will learn how ScienceSoft, an Amazon Web Services (AWS) Services Partner, integrated Amazon Nova 2 Sonic with Amazon Bedrock Guardrails to build a Health Insurance Portability and Accountability Act (HIPAA)-compliant AI voice scheduler. You will see how the solution addresses healthcare scheduling challenges while maintaining privacy, compliance, and responsible AI standards, and how you can apply the same architecture to your own workflows.

Amazon Bedrock GuardrailsAmazon NovaCustomer Solutions
AWS Machine Learning BlogRead original
ExternalSoftware Engineering
DZone

Do We Test Just to Find Bugs?

In a world where testing is mainly test execution, it is reasonable to expect that when people test, they simply expect to find bugs. "We test to find bugs" is the answer given in job interviews. An answer repeated in onboarding materials, embedded in KPI frameworks, and implicitly assumed in every conversation about when software is ready to ship. It is so thoroughly taken for granted that questioning it sounds absurd, like questioning whether hammers are for hitting things. Testing does find b

DZoneRead original
ExternalAI
NVIDIA Technical Blog

How to Run an Autoresearch Workflow with RL Agent Skills and NVIDIA NeMo

Coding AI agents are becoming practical operators for long-running machine learning (ML) workflows. They can inspect repositories, set up runtimes, resolve... Coding AI agents are becoming practical operators for long-running machine learning (ML) workflows. They can inspect repositories, set up runtimes, resolve build issues, launch experiments, monitor execution, analyze metrics, and summarize results. For reinforcement learning (RL) research, this matters because meaningful metrics often appe

NVIDIA Technical BlogRead original
ExternalAI
NVIDIA Technical Blog

Post-Train NVIDIA Cosmos 3 in One Day Using Agent Skills

What if autonomous coding AI agents could push your vision reasoning models above 90% accuracy with almost no manual effort? When adapting vision reasoning... What if autonomous coding AI agents could push your vision reasoning models above 90% accuracy with almost no manual effort? When adapting vision reasoning models to production video tasks, developers often lose days to data formatting, container setup, training scripts, baseline evaluation, and hyperparameter sweeps before they even know

NVIDIA Technical BlogRead original

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