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LLMOps: The Next Frontier for Machine Learning Operations

Unite.AI

This is why Machine Learning Operations (MLOps) has emerged as a paradigm to offer scalable and measurable values to Artificial Intelligence (AI) driven businesses. MLOps are practices that automate and simplify ML workflows and deployments. They are huge, complex, and data-hungry.

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Elevate Your NLP Models with Automated Data Augmentation for Enhanced Performance

John Snow Labs

Proportional Augmentation is based on robustness and bias tests, while Templatic Augmentation is based on templates provided by user input data. Proportional Augmentation can be used to improve data quality by employing various testing methods that modify or generate new data based on a set of training data.

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What is Data-Centric Architecture in AI?

Pickl AI

Data Annotation In many AI applications, data annotation is necessary to label or tag the data with relevant information. Data annotation can be done manually or using automated techniques. This involves analyzing metrics, feedback from users, and validating the accuracy and reliability of the AI models.

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Data Analytics Trend Report 2023 – How to Stay Ahead of the Game

Pickl AI

Data & Analytics leaders must count on these trends to plan future strategies and implement the same to make business operations more effective. For example, how can we maximize business value on the current AI activities? Hence, introducing the concept of responsible AI has become significant. Wrapping it up !!!

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

AWS Machine Learning Blog

You can use Amazon Inspector to automate vulnerability discovery and management for Amazon Elastic Compute Cloud (Amazon EC2) instances, containers, AWS Lambda functions, and identify the network reachability of your workloads. Learn more about our commitment to Responsible AI and additional responsible AI resources to help our customers.

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Dr. Pandurang Kamat, Chief Technology Officer, Persistent Systems – Interview Series

Unite.AI

They can automate tasks, optimize processes, and empower individuals or small teams to achieve remarkable feats. These assistants adhere to Responsible AI principles, ensuring transparency, accountability, security, and privacy while continuously improving their accuracy and performance through automated evaluation of model output.

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Synthetic Data: A Model Training Solution

Viso.ai

Organizations can easily source data to promote the development, deployment, and scaling of their computer vision applications. Generation With Neural Network Techniques Neural Networks are the most advanced techniques of automated data generation. Neural networks can also synthesize unstructured data like images and video.