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Home » augmented deep learning

augmented deep learning

Leveraging AI and Data Technologies To Better Control Charge Costs for Electric Vehicles

By Sumit Chauhan|2023-09-15T11:39:30-04:00September 15, 2023|

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Cloud and Edge AI

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Which of the following types of AI application have you ever developed, deployed or supported?(Required)

Cloud-based AI

Data-center-based AI

Edge-based AI

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In your view, what are the primary drivers for using edge-based AI?(Required)

Bandwidth limitations

Cost reduction

Reduced latency

Enhanced privacy

Connectivity limitations

Real-time processing or analytics needs

Improved reliability

Other

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If you are using or planning to use edge-based AI, what are the biggest challenges you have faced or anticipate facing?(Required)

Other

Security concerns

Connectivity issues

Difficulties in scaling edge deployments

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When you think about AI systems generally, what's most important to you? [Please select only two responses](Required)

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Energy consumption

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Storage requirements

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In your view, how important is it to be able to control the configuration of edge-based AI solutions?(Required)

Very important – we need to be able to customize all aspects

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What is your current level of satisfaction with the tools and platforms you use for edge-based AI?(Required)

Very satisfied

Satisfied

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Very dissatisfied

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What types of tools or platforms do you most prefer for developing and/or deploying AI systems—whatever their ultimate production environment (cloud, data center, or edge)? [Please select up to two responses](Required)

Cloud-based

On-premises

Environment-specific tools/platforms (edge-specific for edge, e.g.)

Custom-built tools/platforms

Out-of-the-box tools/platforms

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