NEWS IN BRIEF: AI/ML FRESH UPDATES

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Unlocking the Power of LoRA: Navigating the Path to Parameter Efficiency

Discover how to achieve parameter efficiency in finetuning with LoRA, including strategies for adapting linear modules and optimizing learning rates. This article explores the deliberate design decisions that can enhance model performance, GPU memory utilization, and training speed, offering a nuanced understanding and greater control.

Accelerating Toward a Brighter Future: Blendeered's NVIDIA-Themed New Year's City

Pedro Soares, aka Blendeered, showcases his stunning NVIDIA-themed New Year's celebration animation, highlighting the power of technological innovation and NVIDIA Studio's impact on content creation. Using Blender and the NVIDIA GeForce RTX 4090 GPU, Blendeered creates a futuristic city scene with real-time rendering, OptiX ray tracing, and AI-powered tools like NVIDIA Canvas.

Closing the Gap: A Surgeon's Perspective on AI in Healthcare

The article discusses the growing disconnect between clinical practice and AI research in healthcare, emphasizing the lack of clinician participation and collaboration. It highlights the need for a practical approach in identifying actual problems and evaluating if AI can develop better solutions in healthcare.

AI Breathes New Life into Early Mickey Mouse: Exploring the Public Domain

AI experimenters have quickly taken advantage of three early Mickey Mouse cartoons entering the public domain in the US, using an AI model trained on those cartoons to create new still images of Mickey Mouse, Minnie Mouse, and Peg Leg Pete. While the results are sometimes garbled, this early experimentation showcases the potential of integrating public domain characters into the AI space.

Unveiling a Hidden Bias: Enhancing Decision Trees and Random Forests

Recent research explores how decision trees and random forests, commonly used in machine learning, suffer from bias due to the assumption of continuity in features. The study proposes simple techniques to mitigate this bias, with findings showing a 0.2 percentage point deterioration in performance when attributes are mirrored.

Accelerating Deep Learning: Unleashing the Power of Momentum, AdaGrad, RMSProp & Adam

This article explores acceleration techniques in neural networks, emphasizing the need for faster training due to the complexity of deep learning models. It introduces the concept of gradient descent and highlights the limitations of its slow convergence rate. The article then introduces Momentum as an optimization algorithm that uses an exponentially moving average to achieve faster convergence.

Revolutionizing Music AI: 3 Breakthroughs to Expect in 2024

2024 could be the tipping point for Music AI, with breakthroughs in text-to-music generation, music search, and chatbots. However, the field still lags behind Speech AI, and advancements in flexible and natural source separation are needed to revolutionize music interaction through AI.