NEWS IN BRIEF: AI/ML FRESH UPDATES

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Secure Amazon S3 Access for SageMaker Studio

Amazon SageMaker Studio offers a unified interface for data scientists, ML engineers, and developers to build, train, and monitor ML models using Amazon S3 data. S3 Access Grants streamline data access management without the need for frequent IAM role updates, providing granular permissions at bucket, prefix, or object levels.

Mastering Logistic Regression in C#

Article: "Logistic Regression with Batch SGD Training and Weight Decay Using C#". It explains how logistic regression is easy to implement, works well with small and large datasets, and provides highly interpretable results. The demo program uses stochastic gradient descent with batch training and weight decay for accurate predictions.

Uncovering Nazca's Hidden Geoglyphs with AI

Archaeologists using AI discovered 303 new geoglyphs near Peru's Nazca Lines, doubling known figures at the 2,000-year-old site. The figures depict parrots, cats, monkeys, killer whales, and decapitated heads, revealing more about the ancient civilization.

Decoding Text: The Power of Tokenization for AI

Tokenization is crucial in NLP to bridge human language and machine understanding, enabling computers to process text effectively. Large language models like ChatGPT and Claude use tokenization to convert text into numerical representations for meaningful outputs.

Deepfake Scam Targets US Senator

FBI probes AI deepfake impersonating Dmytro Kuleba questioning Ben Cardin in suspected election interference attempt. Senator Cardin raises suspicions during Zoom call with imposter posing as Ukraine's former foreign minister.

AI vs. Art Critic: The Unreplaceable Eye

The AI version of Brian Sewell's review lacks his authentic voice, disappointing readers. Sewell's posh voice and unique style are sorely missed in the London Standard's attempt to recreate his writing.

Secure Cloud Computation: Defending Data from Attackers

MIT researchers have developed a quantum-based security protocol for cloud-based deep-learning models, ensuring data privacy without compromising accuracy. The protocol utilizes the no-cloning principle of quantum mechanics to prevent attackers from intercepting information, maintaining 96 percent accuracy in tests.