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Link to Best Practices for Deploying and Scaling Industrial AI

Best Practices for Deploying and Scaling Industrial AI

Artificial Intelligence (AI) is transforming industrial operations, helping organizations optimize workflows, reduce downtime, and enhance productivity. Different industry verticals leverage AI in unique ways.

Link to The Center for Adaptive Edge Intelligence

The Center for Adaptive Edge Intelligence

Adaptive edge intelligence brings real-time decision-making to the point of data creation, whether from sensors, machines, or cameras.

Link to The Value of Vehicle Electrification

The Value of Vehicle Electrification

Electric vehicles (EVs) present automakers with many design, engineering, and manufactu ring challenges.

Link to Accelerating Manufacturing Digital Transformation with Industrial Connectivity and IoT

Accelerating Manufacturing Digital Transformation with Industrial Connectivity and IoT

Digital transformation is empowering industrial organizations to deliver sustainable innovation, disruption-proof products and services, and continuous operational improvement.

Link to Smart Manufacturing for Automotive

Smart Manufacturing for Automotive

Leading a transportation revolution in autonomous, electric, shared mobility and connectivity with the next generation of design and development tools.

Link to Center for Data Pipeline Automation

Center for Data Pipeline Automation

As businesses become data-driven and rely more heavily on analytics to operate, getting high-quality, trusted data to the right data user at the right time is essential.

Link to Center for Automated Integration

Center for Automated Integration

The goal of automated integration is to enable applications and systems that were built separately to easily share data and work together, resulting in new capabilities and efficiencies that cut costs, uncover insights, and much more.

Link to Continuous Intelligence: Insights

Continuous Intelligence: Insights

Digital transformation requires continuous intelligence (CI). Today's digital businesses are leveraging this new category of software which includes real-time analytics and insights from a single, cloud-native platform across multiple use cases to speed decision-making, and drive world-class customer experiences.
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Improving Outcomes with Intelligent Edge Systems and Edge Cloud

Improving Outcomes with Intelligent Edge Systems and Edge Cloud

machine processing ideas and knowledge into data to be spread around, with production line, funnel and cloud

Edge is considered the catalyst for a lot of emerging technologies, such as LiDAR, drones, traffic management, and wind turbine control.

Written By

RTInsights Team

Jul 7, 2020

1 minute read

There are several trends that are making edge computing necessary. One of them is that there will be 28 times the amount of IoT and other connected devices than mobile devices by 2024, according to IDC.

The networking landscape will be fundamentally shifted by bringing machines, transport, industries and entire cities online. That will lead to “more than 100ZB” of data creation annually, three times more than what exists today.

Without the low-latency that edge provides, operators may be forced to perform all computation inside the device. There are some self-driving operators who are attempting to do that, although most see edge computing as complementary to their eventual commercial product.

“These new stakeholders require implementation and support to address edge-specific constraints introduced by their use cases—for example, requirements for low latency, tight data security, or autonomous operations,” according to IDC in a new InfoBrief.

View the InfoBrief, “Embedded Intelligence: Innovation Outcomes with Edge Cloud” below or download the PDF.

RTInsights Team

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The Q2 Mandate: Why AI’s Biggest Hurdle is Leadership, Not Technology

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Real-Time AI In Production: Building Reliable AI Systems at Scale

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