Deep Learning Articles

Facundo Giuliani

Updated on February 25, 2026

Model Context Protocol connects AI models to external data, replacing brittle, custom integrations with a universal port. Our expert explains how this will usher in a new era of enterprise AI.

Avi Chai Outmezguine

Updated on February 18, 2026

Context-persistent AI systems don’t threaten human consciousness. They reveal how easily we confuse continuity with mind — and how high the cost of that confusion might be.

Ali Zonoozi

Updated on July 31, 2025

Matrix factorization is a mathematical technique that decomposes a large matrix into two lower-rank matrices whose product approximates the original, revealing latent patterns in the data. It's used in data science and unsupervised learning applications.

Juras Juršėnas

Updated on July 08, 2025

AI models are growing so complex, so quickly that we may have to recalibrate how we think about transparency.

Ellen Glover

Updated on June 30, 2025

Artificial intelligence often makes decisions we don’t understand.

Jeff Rumage

Updated on June 23, 2025

NPUs are the hot new AI chip, boasting enhanced deep learning capabilities while consuming a fraction of the energy — and all without data ever leaving the device.

Dan Schwarz

Updated on June 12, 2025

A thorough analysis of available deep research methods reveals that, for now, humans remain an essential part of any effective program.

Artem Oppermann

Updated on June 10, 2025

Artificial intelligence (AI) enables machines to perform tasks like humans. Machine learning, a subset of AI, lets machines learn from data without explicit programming. Deep learning, a subset of ML, uses multilayered neural networks to process tasks.

Artem Oppermann

Updated on June 02, 2025

Few-shot learning is a machine learning framework where an AI model is given a small amount of labeled training data to learn from. Here’s how few-shot learning works and why it’s important.

Artem Oppermann

Updated on May 23, 2025

In this four-part series, I’ll show you how the Markov decision process works and the mathematical theory you need to know to understand deep reinforcement learning.