Many forwarding-looking manufacturers no longer view sustainability programs as additional costs of doing business but rather…
There are two trends converging to shape the way industrial data is handled today. First, ubiquitous…
For today’s businesses, the ability to dynamically adapt to challenging market conditions has become indispensable. With…
The value of big data is game-changing for life sciences firms equipped to leverage it. Life…
Not all location intelligence data is created equal. There are nuances and, sometimes, inherent biases. Here are three criteria for evaluating the available options: ease of use, global data, and accuracy/quality.
Using analytics and AI, OEMs of connected equipment can gain a deep understanding of the status of a machine and move to a predictive maintenance mode of operation.
Artificial intelligence (AI) and automation—such as AI cameras and automated workflows—have become vital for physical operations.
By connecting data and processes across the digital thread, companies can find improved efficiency, visibility, and innovation across the product value chain and full lifecycle.
With the proliferation of high-definition cameras, computer vision, and AI applications, retail stores can now get real-time insights while customers shop.
A new technique called monotonic selective risk could be deployed to reduce the error rate for underrepresented groups in AI models.
Working towards a lower carbon future will demand that moves be made around operational efficiency, improved production tactics, and minimized waste – all of which can be accomplished with Cognitive AI solutions.
While $1.1 trillion annually is being invested in digital factory initiatives worldwide, most companies, 64%, are still at an early stage of their digital transformation.
In this week's real-time analytics news: The NSF and Amazon awarded about a dozen organizations $9.5 million for projects that seek to root out unfairness and bias in AI and ML.
A new research collaboration will focus on Superlearners, a foundational machine learning technology that enables autonomy for all building applications.
Equipped with predictive maintenance solutions, fleet owners and OEMs will enjoy reduced maintenance prices, improved sustainability, and greater overall reliability.
Increasingly, digital businesses are using real-time behavioral analytics on pre-submitted data to look for criminal digital footprints and enhance their fraud prevention strategies.
Low-code platforms can serve as catalysts for enterprises to seamlessly leverage a variety of applications and technologies that help businesses gain a competitive edge.
MQTT’s publish/subscribe and report by exception method improves response times and dramatically reduces bandwidth usage and costs.
Managing database access can be a bane of many organizations developing modern applications. RHODA simplifies the process while offering the visibility, agility, and flexibility needed by ITOps, database administrators, and application developers.
Your identity in various metaverses will matter more than ever because a digital twin will be a virtual representation of you, the individual.
Harnessing the full power of real-time data streams delivers great value, but is difficult for many organizations. The top hurdle is integrating multiple data sources.
A new open source AI model looks to loosen the grip big tech has on AI research and innovation, offering the model to academics in all walks of life.
Multi-site critical infrastructure operations managers must secure their sites to ensure uninterrupted services for their customers that depend on them.
Banks and financial institutions, eyeing the shift to mobile banking, are reacting quickly to improve the experience of their users. That will set them up to influence customer preferences for digital channels and drive the future of banking.
OEMs can generate predictable and recurring monthly revenues by offering Features-as-a-Service in any connected equipment or product.
Most data stacks begin governance at the warehouse, but they don't know where that ELT data came from and what the context and source is. We need to fix that.