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A 5-Step Checklist for Mastering Enterprise AI

CSM Magazine

Whenever a new iteration of the AI tool is released, remember to monitor key metrics that reflect and reinforce your original goals such as ‘What % of users engage with the assistant?’, ‘What are the most popular topics?’ How many visitors request transfer to a live agent?’ For more information, please visit www.ebi.ai.

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Digital Transformation Challenges: Creating Your Action Plan

aircall

Companies rely heavily on reporting without the advantage of data and analytics that are so critical to establishing efficient, productive workflows. In today’s marketplace, automation, digitization, and big data are your friends. Jobs in transportation and warehousing will increase due to eCommerce growth.

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Demystifying machine learning at the edge through real use cases

AWS Machine Learning

Edge is a term that refers to a location, far from the cloud or a big data center, where you have a computer device (edge device) capable of running (edge) applications. Agriculture, mining, surveillance and security, and maritime transportation are some areas where far edge devices play an important role. Edge computing.

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Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

AWS Machine Learning

Amazon Cognito for user authentication with Transport Layer Security (TLS). As we noted in the previous section, data scientists perform exploratory data analyses, run data analytics, and train ML models. We then use Kibana and the Grafana UI for searching and filtering logs and metrics. Kubeflow Logging.

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Machine learning with decentralized training data using federated learning on Amazon SageMaker

AWS Machine Learning

It serializes these configuration dictionaries (or config dict for short) to their ProtoBuf representation, transports them to the client using gRPC, and then deserializes them back to Python dictionaries. The evaluation takes place on a testing dataset existing only on the server, and the new improved accuracy metrics are produced.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

Conversely, the data in your model may be extremely sensitive and highly regulated, so deviation from AWS Key Management Service (AWS KMS) customer managed key (CMK) rotation and use of AWS Network Firewall to help enforce Transport Layer Security (TLS) for ingress and egress traffic to protect against data exfiltration may be an unacceptable risk.