Researchers at TUS and collaborating institutes have created a deep learning binary classifier that identifies an unknown quasicrystalline phase in materials with over 92% accuracy, revolutionizing material analysis with wide-ranging technological implications.

Lincoln Laboratory is working to reduce the energy requirements of AI models by promoting energy usage transparency and improving training efficiency.

This guide provides over 50 customizable AI-generated prompts for creating line art coloring book pages using Midjourney, Stable Diffusion, and DALL-E. The prompts span various themes suitable for both children and adults and are designed to output clean, thick-outlined images ideal for coloring. Tips for prompt adjustments and negative prompts are included for optimal results.

Artificial Intelligence, with advancements like GPT-4, has evolved into multimodal AI, integrating text, images, audio, and video for a holistic understanding akin to human perception. This allows for more accurate predictions and nuanced interactions across applications such as customer service, social media analysis, and training, significantly enriching AI’s interface with everyday life.

A study involving 32 papers reviewed the application of explainable AI in poverty estimation using satellite imagery and deep learning. It found that transparency, interpretability, and domain knowledge—key elements of explainable machine learning—vary and often fall below the necessary scientific standards for accurate insights into poverty and welfare.

The blog post introduces PyTorch, a key deep learning library used for creating and operating on tensors, the core components for neural network modeling. It provides a beginner-friendly guide on tensor properties and operations, like addition and multiplication, and connects tensor manipulation to deep learning application. It mentions resources for further learning, including a free…

Deep Learning advancements in AI, specifically in SLAM technology, have been made by University College London researchers with DSP-SLAM. This system accurately maps environments and tracks camera movement, utilizing object shape and pose estimation to improve scene representation significantly. It performs well across multiple input types and has excelled in reconstructing objects in tests.

Duck AI’s DuckTrack is an advanced tool for tracking user interactions, vital for training intelligent systems. It records various inputs including mouse and keyboard actions and integrates with major operating systems. While it faces challenges with double clicks and trackpad gestures, the tool excels in precision and is constantly improved through community participation. DuckTrack demonstrates…

Explore regularization methods to enhance Neural Network performance and avoid overfitting. Read more at Towards Data Science.