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Machine unlearning: Researchers make AI models ‘forget’ data

AI News

Researchers from the Tokyo University of Science (TUS) have developed a method to enable large-scale AI models to selectively “forget” specific classes of data. Progress in AI has provided tools capable of revolutionising various domains, from healthcare to autonomous driving.

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Using AI for Predictive Analytics in Aviation Safety

Aiiot Talk

Aviation professionals can apply AI-powered predictive analytics to improve safety in everything from aircraft design to airport logistics. AI can streamline and automate key safety processes such as design, monitoring, testing and more. AI monitoring reduces the risk of scenarios like this.

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Is Rapid AI Adoption Posing Serious Risks for Corporations?

ODSC - Open Data Science

This is a promising shift for AI developers, and many organizations have realized impressive benefits from the technology, but it also comes with significant risks. AI’s rapid growth could lead more companies to implement it without fully understanding how to manage it safely and ethically. What Risks Does AI Pose to Corporations?

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What is Model Risk and Why Does it Matter?

DataRobot Blog

The stakes in managing model risk are at an all-time high, but luckily automated machine learning provides an effective way to reduce these risks. Among these, Spain, the United Kingdom, and the United States passed the highest number of AI-related bills in 2021 adopting three each. appeared first on DataRobot AI Cloud.

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The future of QA is here, meet QA-GPT

LevelAI

Auto-QA Today Contact center auto-QA (Quality Assurance) refers to the use of automated tools and technologies to assess and evaluate the quality of interactions between contact center agents and customers. These solutions are often powered by legacy AI systems that are limited in scope or worse, without AI at all.

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Forecast Time Series at Scale with Google BigQuery and DataRobot

DataRobot Blog

Data scientists have used the DataRobot AI Cloud platform to build time series models for several years. With automated feature engineering, automated model development, and more explainable forecasts, data scientists can build more models with more accuracy, speed, and confidence. Forecasting the future is difficult.

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What is Responsible AI

Pickl AI

Summary: Responsible AI ensures AI systems operate ethically, transparently, and accountably, addressing bias and societal risks. Through ethical guidelines, robust governance, and interdisciplinary collaboration, organisations can harness AI’s transformative power while safeguarding fairness and inclusivity.