NEWS IN BRIEF: AI/ML FRESH UPDATES

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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.

1 Million AI Models Unleashed on Hugging Face

AI hosting platform Hugging Face hits 1 million AI model listings, offering customization for specialized tasks. CEO Delangue emphasizes the importance of tailored models for individual use-cases, highlighting the platform's versatility.

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.

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.

AI Turbocharges Data Science Workflows

NVIDIA's RAPIDS cuDF library accelerates pandas by up to 100x on RTX hardware, improving data processing speed for data scientists. Data scientists can now use their preferred code base without sacrificing efficiency, thanks to RAPIDS cuDF's GPU-accelerated Python libraries.

Save Your Money: A Guide to Dutch Exam Benchmarking

A machine learning engineer and PhD researcher conducted Dutch-specific benchmarking of LLMs, comparing models like o1-preview and GPT-4o on real Dutch exam questions. The study highlights the importance of validating AI models for Dutch-language tasks and offers valuable insights for companies targeting the Dutch market.

Mastering LLM Fine-tuning: Your FAQs Answered

LLM Fine-Tuning FAQs: Understand the nuances of fine-tuning large language models and when to use it effectively for AI projects. Fine-tuning can lower inference costs and adapt model outputs through prompt engineering, but its effectiveness depends on the use case and data volume.