Salvatore Salamone

Most use cases for AI in companies are developed by data scientists and then deployed and used essentially as a black box.

The complexity and ever-changing nature of fraud and financial crime patterns requires an ability to quickly and effectively spot and stop incidents.

In the news this week: AI and ML solutions to future-proof vehicles, an update to an open-source multi-model database, a cognitive advertising accelerator, and a major studio turns to AI to pick its next blockbuster.

Corporate AI offerings must be as robust and feature rich as the consumer AI services workers use at home. Otherwise, users will not embrace them.

Many businesses use container-based microservices architectures to develop AI. The container orchestrator Kubernetes can help with management and scaling.

Here is a quick overview of the major real-time analytics developments and innovations that got our readers’ attention over the last year.

Perhaps the underlying reason AI, CI, and other technologies will be disruptive factors in 2020 is digital transformation.

CI based on analysis of sensor and IoT data can help spot state changes in devices and make predictions about an asset’s failire probability.

In the news this week: chip vendors make acquisitions and introduce new AI products, an analytic database provider releases an enhanced solution, and more.

If businesses do not adopt their own best practices in addressing AI transparency and bias issues, they may not have a choice in the future.

In the news this week: enhancements to a mainstay DBMS, a merger between two enterprise AI companies, the next generation of a virtual beauty recommendation app, and more.

Today, there is a need to transition from simply analyzing streaming data to developing insights that understand events in real-time.