NEWS IN BRIEF: AI/ML FRESH UPDATES

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Revolutionizing Healthcare with Machine Learning

Marzyeh Ghassemi combines her love for video games and health in her work at MIT, focusing on using machine learning to improve healthcare equity. Ghassemi's research group at LIDS explores how biases in health data can impact machine learning models, highlighting the importance of diversity and inclusion in AI applications.

Elon Musk's Twitter Investment: A Power Move

Jeff Jarvis, former TV critic and online media leader, warns of internet regulation affecting freedoms in his new book, The Web We Weave. He emphasizes the dangers of moral panic and the need to reclaim the web from tech bros to prevent stifling regulations.

Rise of AI in Online Crime

Police chief warns of criminals using AI to target victims in new ways. Urges law enforcement to adapt quickly to combat evolving threats.

Enhancing Outlier Detection with Feature Subsets

Identifying relevant subspaces in outlier detection is crucial for effective analysis of tabular data. Challenges include defining meaningful outliers and dealing with the curse of dimensionality in data with many features.

Russian AI Cyber-Attack Threat

Pat McFadden warns at Nato conference that Russia aims to target UK's electricity grid using AI. London to launch Laboratory for AI Security Research to counter emerging threats.

Everest Ascension

New technology like Generative AI faces challenges like previous tech. Progress is made with small steps, like climbing Mount Everest.

MIT breakthrough: Training more reliable AI agents

MIT researchers have developed a more efficient algorithm for training AI systems to make better decisions in complex tasks with variability, such as traffic control. The new method improves performance by strategically selecting tasks, making it 5-50 times more efficient than standard approaches, ultimately enhancing the AI agent's performance.