Remove tag edge-computing
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Accelerating Industry 4.0 at warp speed: The role of GenAI at the factory edge

CIO Business Intelligence

I am fascinated and passionate about helping manufacturers leverage Gen AI-fueled edge deployments that break through legacy Industry 4.0 The detailed data must be tagged and mapped to specific processes, operational steps, and dashboards; pressure data A maps to process B, temperature data C maps to process D, etc.

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How to Launch Your AI Projects from Pilot to Production – and Ensure Success

CIO Business Intelligence

Developing models isn’t trivial, and data scientists certainly have challenges cleansing and tagging data, selecting algorithms, configuring models, setting up infrastructure, and validating results. Plan for large-scale AI applications on the edge. Establish MLOps, ModelOps, and infrastructure-monitoring capabilities.

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5 ways IT pros can accelerate webpages in a day at no cost

CIO Business Intelligence

Optimize images by serving them in the correct format and size for the target device (phone, tablet, or computer) and viewport. Utilize the srcset attribute in your image tags to allow browsers to choose the best image size and format based on the user’s device and connection. Follow the mantra “always be caching.”

IT 90
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How AI is helping the NFL improve player safety

CIO Business Intelligence

Like many other professional sports leagues, the NFL has been at the leading edge of data-driven transformation for years. Changing the game The first step in building Digital Athlete was using computer vision and ML to teach the AI to glean information from game and practice footage.

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Building a Named Entity Recognition model using a BiLSTM-CRF network

Domino Data Lab

This type of hand-crafted rule yields very high precision, but it requires a tremendous amount of work to define entity structures and capture edge cases. The tags used in the dataset follow the IOB format, which we cover in the next section. The model takes an input sequence x (words) and target sequence y (IOB tags).

Modeling 111
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Krones real-time production line monitoring with Amazon Managed Service for Apache Flink

AWS Big Data

Data source The data is gathered by a service running on an edge device reading several protocols like Siemens S7 or OPC/UA. AWS IoT Greengrass provides prebuilt components that can be deployed to the edge. This information is essential for Flink to advance event time and trigger relevant computations, such as window evaluations.

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Digital Transformation is a Data Journey From Edge to Insight

Cloudera

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.