For anyone interested
in learning more about AIXPRT, the Introduction to AIXPRT white paper provides detailed information
about its toolkits, workloads, system requirements, installation, test
parameters, and results. However, for AIXPRT.com visitors who want to find the answers to specific
AIXPRT-related questions quickly, a white paper can be daunting.
Because we want tech
journalists, OEM lab engineers, and everyone who is interested in AIXPRT to be
able to find the answers they need in as little time as possible, we’ve decided
to develop a new learning tool that will serve as an information hub for common
AIXPRT topics and questions.
The new learning tool
will be available online through our site. It will offer quick bites of
information about the fundamentals of AIXPRT, why the benchmark matters, the
benefits of AIXPRT testing and results, machine learning concepts, key terms,
and practical testing concerns.
We’re still working on the tool’s content and design. Because we’re designing this tool for you, we’d love to hear the topics and questions you think we should include. If you have any suggestions, please let us know!
We’re excited to see that users have successfully completed over 250,000 WebXPRT runs! From the original WebXPRT 2013 to the most recent version, WebXPRT 3, this tool has been popular with manufacturers, developers, consumers, and media outlets around the world because it’s easy to run, it runs quickly and on a wide variety of platforms, and it evaluates device performance using real-world tasks.
If you’ve run WebXPRT in any of the more than 458 cities and 64 countries from which we’ve received complete test data—including newcomers Lithuania, Luxembourg, Sweden, and Uruguay—we’re grateful for your help in reaching this milestone. Here’s to another quarter-million runs!
If you haven’t yet transitioned your browser testing to WebXPRT 3, now is a great time to give it a try! WebXPRT 3 includes updated photo workloads with new images and a deep learning task used for image classification. It also uses an optical character recognition task in the Encrypt Notes and OCR scan workload and combines part of the DNA Sequence Analysis scenario with a writing sample/spell check scenario to simulate online homework in the new Online Homework workload. Users carry out tasks like these on their browsers daily, making these workloads very effective for assessing how well a device will perform in the real world.
Happy testing to everyone, and if you have any questions about WebXPRT 3 or the XPRTs in general, feel free to ask!