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How Quality Data Fuels Superior Model Performance

Unite.AI

Heres the thing no one talks about: the most sophisticated AI model in the world is useless without the right fuel. That fuel is dataand not just any data, but high-quality, purpose-built, and meticulously curated datasets. Data-centric AI flips the traditional script.

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AI Transparency and the Need for Open-Source Models

Unite.AI

In order to protect people from the potential harms of AI, some regulators in the United States and European Union are increasingly advocating for controls and checks and balances on the power of open-source AI models. When AI models become observable, they instill confidence in their reliability and accuracy.

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AI News Weekly - Issue #380: 63% of IT and security pros believe AI will improve corporate cybersecurity - Apr 11th 2024

AI Weekly

tweaktown.com Research Researchers unveil time series deep learning technique for optimal performance in AI models A team of researchers has unveiled a time series machine learning technique designed to address data drift challenges. AI’s dark side explained We live in a world where anything seems possible with AI.

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The AI Feedback Loop: Maintaining Model Production Quality In The Age Of AI-Generated Content

Unite.AI

Production-deployed AI models need a robust and continuous performance evaluation mechanism. This is where an AI feedback loop can be applied to ensure consistent model performance. But, with the meteoric rise of Generative AI , AI model training has become anomalous and error-prone.

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Concept Drift vs Data Drift: How AI Can Beat the Change

Viso.ai

Two of the most important concepts underlying this area of study are concept drift vs data drift. These phenomena manifest when certain factors alter the statistical properties of model inputs or outputs. The causes of concept drift are diverse and depend on the underlying context of the application or use case.

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Five open-source AI tools to know

IBM Journey to AI blog

The diversity and accessibility of open-source AI allow for a broad set of beneficial use cases, like real-time fraud protection, medical image analysis, personalized recommendations and customized learning. This availability makes open-source projects and AI models popular with developers, researchers and organizations.

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3 AI Trends from the Big Data & AI Toronto Conference

DataRobot Blog

Model Observability – the ability to track key health and service metrics for models in production – remains a top priority for AI-enabled organizations. The demo sparked an ideal reaction from the retailer, who emphasized that such changes will “completely change” how his team spends their time.