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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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How Large Language Models Are Unveiling the Mystery of ‘Blackbox’ AI

Unite.AI

This simplicity opens the door for people from all kinds of backgrounds to interact with AI and see how it works. By making explainable AI more approachable, LLMs can help people understand the workings of AI models and build trust in using them in their work and daily lives. Take the model x-[plAIn] , for example.

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Who Is Responsible If Healthcare AI Fails?

Unite.AI

Similarly, what if a drug diagnosis algorithm recommends the wrong medication for a patient and they suffer a negative side effect? At the root of AI mistakes like these is the nature of AI models themselves. Most AI today use “black box” logic, meaning no one can see how the algorithm makes decisions.

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Enhancing AI Transparency and Trust with Composite AI

Unite.AI

The adoption of Artificial Intelligence (AI) has increased rapidly across domains such as healthcare, finance, and legal systems. However, this surge in AI usage has raised concerns about transparency and accountability. Composite AI is a cutting-edge approach to holistically tackling complex business problems.

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Is Rapid AI Adoption Posing Serious Risks for Corporations?

ODSC - Open Data Science

Bias and Inequality AI can also introduce societal issues like exaggerating bias if corporations aren’t careful. Amazon’s scrapped hiring AI model infamously penalized women’s resumes as the machine learning algorithm expanded on implicit biases within the training data.

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Copyright, AI, and Provenance

O'Reilly Media

What is contained in the model is an enormous set of parameters based on all the content that has been ingested during training, that represents the probability that one word is likely to follow another. I can also ask for a reading list about plagues in 16th century England, algorithms for testing prime numbers, or anything else.

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The future of QA is here, meet QA-GPT

LevelAI

Auto-QA solutions employ various methods such as speech analytics, natural language processing (NLP), sentiment analysis, and machine learning algorithms to automatically review and score customer interactions. In our testing, we found that QA-GPT can cover over 85% of scorecard questions out of the box without any extra configuration.