AI News

DECEMBER 10, 2024

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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Unite.AI

MARCH 6, 2025

In the race to advance artificial intelligence, DeepSeek has made a groundbreaking development with its powerful new model, R1. Renowned for its ability to efficiently tackle complex reasoning tasks, R1 has attracted significant attention from the AI research community, Silicon Valley , Wall Street , and the media.

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Unite.AI

JUNE 26, 2023

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. Black box AI lack transparency, leading to risks like logic bias , discrimination and inaccurate results.

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Towards AI

NOVEMBER 7, 2024

This week, we are diving into some very interesting resources on the AI ‘black box problem’, interpretability, and AI decision-making. Parallely, we also dive into Anthropic’s new framework for assessing the risk of AI models sabotaging human efforts to control and evaluate them. Enjoy the read!

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Unite.AI

DECEMBER 19, 2024

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.

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Unite.AI

APRIL 9, 2024

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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Towards AI

DECEMBER 19, 2023

The models are becoming more and more complex with deeper layers leading to greater accuracy. It is very risky to apply these black-box AI systems in real-life applications, especially in sectors like banking and healthcare. One issue with this current trend is the focus on interpretability is lost at times.

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