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Achieving Trusted AI in Manufacturing

Cloudera

In the dynamic landscape of modern manufacturing, AI has emerged as a transformative differentiator, reshaping the industry for those seeking the competitive advantages of gained efficiency and innovation. There are many functional areas within manufacturing where manufacturers will see AI’s massive benefits.

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Embrace the Next Industrial Revolution with the Snowflake Data Cloud for Manufacturing

Snowflake

In this second installment of our blog series on Industry 4.0, Additionally, this manufacturing data platform should facilitate IT / OT convergence with a precise asset model and plant hierarchy established in the cloud, coupled with AI/ML-based analytics capabilities.

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Covid-19 Accelerates The Need for Retail, Manufacturing Supply Chains To Adapt – Part 2

Cloudera

The 6 key takeaways from this blog are below: 6 key takeaways. The pandemic has been a call to action for both the manufacturing and retail industries and that is the bottom line with COVID. Brent Biddulph: . In better dealing with disruption across all points of the supply chain, it all comes down to data.

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How to get datasets for Machine Learning?

Knowledge Hut

Machine learning uses algorithms that comb through data sets and continuously improve the machine learning model. B ut it is a great resource for u sers /learners to get better conne cted with the data and draw insights from it by applying different types of algorithms on it. The basic datasets in this field are as follows.

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GenAI in Automotive: From R&D to On-Road Implementation

RandomTrees

AI has risen as the stepping stone of innovation, which enables manufacturers to enhance vehicle safety, efficiency, and user experience. Advanced AI algorithms combined with big data analytics have revolutionized the way researchers model complex scenarios and optimize vehicle performance.

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Better video for mobile RTC with AV1 and HD

Engineering at Meta

There are no universal definitions for low, mid, and high networks, but for the purpose of this blog post, less than 300 Kbps will be considered as low, 300-800 Kbps as mid, and above 800 Kbps as a high, HD-capable, or high-end network. This algorithm can combine these scaling distortions with the encoder distortions to produce output PSNR.

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10 Practical Generative AI Examples to be More Productive

Edureka

This data can be retrieved from anything – books, blogs, pictures or images. Recognising Patterns: The algorithm then recognises patterns and relationships between various data sets based on all the retrieved training data.