Search results for Ai Inference Testing

At-scale testing for LLM implementations and guardrails (Reader Forum)

As AI becomes the public face of business, organizations must validate performance, security, and cost efficiency at scale. Comprehensive testing under realistic workloads is essen...

Testing AI-Infused Apps: A Dual-Layer Framework for AI Quality Assurance

AI-infused apps are different from traditional software. Apps that embed large language models, agents, retrieval-augmented generation (RAG), or tool-calling workflows bring their...

Monitoring LLM behavior: Drift, retries, and refusal patterns

The stochastic challengeTraditional software is predictable: Input A plus function B always equals output C. This determinism allows engineers to develop robust tests. On the other...

Smart Test Case Generation Using AI

Introduction In today’s fast-moving software industry, delivering high-quality applications within shorter release cycles has become a major challenge for QA teams. Traditional tes...

How we test AI at ZDNET

AI is the hottest topic in tech with new models and products launching daily. Here's how we test the latest AI developments at ZDNET.

GenAI Validation Playbook: How to Test Large Language Models Before Enterprise Rollout

This blog explains how enterprises can validate large language models before rolling out. It covers GenAI validation frameworks, LLM output accuracy testing, hallucination checks,...

Most Candidates Prepare for the Wrong NVIDIA Interview

What NVIDIA likely tests for an AI Inference Performance Engineer role — and how to prepare smarterContinue reading on Medium »

New Microsoft tool lets devs spin up AI behavior tests using text descriptions

Microsoft on Tuesday took the wraps off Adaptive Spec-driven Scoring for Evaluation and Regression Testing, an open source framework for spinning up AI evaluations.

Securing AI Systems: Red Teaming, Prompt Injection, and Adversarial Testing

Part 6 of a series on building reliable AI systems In the previous parts of this series, we explored: Testing AI systems Evaluation pipelines RAG evaluation Agent reliability...

Quality Assurance in AI-Driven Business Evolution

Why do most intelligent systems fail when they hit production? It's rarely because of a weak algorithm. Instead, it's usually a testing framework stuck in a bygone era. If you're s...

GenAI Testing Tools Shaping Modern Software QA

Stuart Gentle Publisher at Onrec 08 May 2026|News archiveGenAI Testing Tools Shaping Modern Software QAGenerative AI is beginning to transform how software testing is done. Tradit...

Train-to-Test scaling explained: How to optimize your end-to-end AI compute budget for inference

The standard guidelines for building large language models (LLMs) optimize only for training costs and ignore inference costs. This poses a challenge for real-world applications th...

AI Is Generating More Tests. But Are They Preventing the Next Cloud Outage?

There’s a moment that’s become familiar to engineering teams everywhere: you feed your codebase into an AI tool, wait a few seconds, and watch thousands of new test cases appear. I...

AI IQ is here: a new site scores frontier AI models on the human IQ scale. The results are already dividing tech.

For decades, the IQ test has been one of the most familiar — and most contested — yardsticks for human intelligence. Now, a startup project called AI IQ is applying the same metaph...

LinkedIn’s new tool lets you test the outputs of various AI models

The testing solution is designed to help LinkedIn members select the best AI tool for their use case.

Testing AI-Generated Code: How to Actually Know If It Works

I shipped a bug to production in January that embarrassed me. Not a subtle bug. A bug where a rate limiting function the AI wrote silently swallowed errors and returned true for ev...

What flavour AI?

Like all AI interactions, if its important, you should really verify the answers you get - ask where /how the answer was obtained from. LLMs, because they are developed using infor...

Real-Time AI Inference at Scale Using Cloud Run, GPUs, and Vertex AI

Real-time AI inference has become a fundamental feature of modern applications and has been used to drive applications in conversational agents, recommendation engines, fraud detec...

LLM Drift: Why Your AI Detection Pipeline is Quietly Decaying (Kimi K2 Benchmark)

A short field report on what current AI detectors actually do when you point them at frontier reasoning model output, and what I changed in my own detection workflow. I integrate...

U.S. Government will Test Advanced AI Models before Public Release

The U.S. AI Safety Institute at NIST created the Testing Risks of AI for National Security (TRAINS) Taskforce in November 2024. This…Continue reading on Medium »

The Next AI Bottleneck Isn’t the Model: It’s the Inference System

Enterprise AI systems are entering a phase where inference design matters as much as model capability itself. The post The Next AI Bottleneck Isn’t the Model: It’s the Inference Sy...

How I Speed-Tested 15 AI Models in 2026 — And What Actually Matters for Your App

Look, I'm gonna be honest with you. When I first started building AI-powered apps, I thought quality was everything. You know, the whole "my model writes better poetry than yours"...

Test-Time Compute Quietly Changed the Economics of Inference

Watch a reasoning model think.Continue reading on Medium »

A Guide to Creating an AI Toolkit