Convolutional Neural Networks have revolutionized artificial intelligence by enabling machines to process visual data with remarkable accuracy. Inspired by the visual cortex, CNNs evolved from early models like LeNet-5 to powerful architectures such as AlexNet, VGG, ResNet, and DenseNet. This article explores CNN core concepts, key innovations, real-world applications, and future trends, highlighting their enduring impact on AI.

This article explores how AI is transforming science and medicine in 2025. From breakthroughs in protein engineering and brain mapping to outperforming doctors in clinical diagnosis, AI is becoming an active research partner and clinical assistant. It highlights key findings from Stanford’s AI Index Report, including the rise of virtual labs, predictive healthcare models, AI scribes, and the importance of ethical, inclusive, and regulated deployment.

This article explores TabPFN, a transformer-based foundation model designed for small tabular datasets. Trained on millions of synthetic datasets generated via structural causal models, TabPFN learns to predict labels through in-context learning. It outperforms traditional methods like CatBoost and XGBoost in both speed and accuracy, while offering robustness, interpretability, and fine-tuning capabilities. A breakthrough in tabular ML, it redefines what's possible on structu

Can AI chatbots comfort us—or make us dependent? A study explores ChatGPT's emotional impact and the ethics of affective design.

Tech giants turn to nuclear energy to power AI, tackling rising energy demands and environmental impact with bold new strategies.

Explore how Diffusion Models are revolutionizing generative AI, from their mathematical foundations to applications in image and audio.