Artificial Intelligence

Sandbox AQ is Alphabet’s new bet on the future of quantum cryptography

Googleu2019s parent has spun out a team working on novel encryption and navigation systems using quantum techniques.

Nvidia speeds AI, climate modeling

At its annual customer conference, Nvidia is showing off new ways to model and predict the behavior of clouds and more, in the cloud and elsewhere.

What is synthetic data? Generated data to help your AI strategy

Artificially generated data can be used in place of real historic data to train AI models when actual data sets are lacking in quality, volume, or variety.

Shell sees AI as fuel for its sustainability goals

The energy giantu2019s dual-cloud transformation includes a data lake architecture that AI chief Dan Jeavons says is catalyzing business efficiencies and will prove key in cutting carbon emissions over time.

Priceline takes flight with real-time analytics in the cloud

Priceline takes flight with real-time analytics in the cloud

The online deal maker is midway through a multicloud migration that makes the most of real-time analytics and cloud-native technologies, but not without pockets of turbulence along the way.

How Walmart’s Indian IT team used AI to predict customer preferences

Walmart Global Tech India developed applications to improve customer satisfaction and employee efficiency during the pandemic.

Your AI strategy’s secret ingredient

Taking a people-centered approach to rolling out artificial intelligence initiatives is the key to success, experts say. Hereu2019s how to ensure your AI efforts are u2018augmentingu2019 the value employees bring to their work.

4 ways to mature your digital automation strategy

When it comes to realizing the benefits of digital automation, maturity matters. Here's what CIOs need to know to assess and advance their automation efforts.

IT leaders should measure and balance fairness in AI models, Forrester says

Eliminating bias in artificial intelligence is increasingly an issue as more enterprises use it in their services.

3 areas where AIops excels — and 2 where it still falls short

AIops speeds IT discovery and troubleshooting, but it isnu2019t magic. And operations staff must still prepare the data for machine learning and manually solve some issues.