AGI is a hypothetical AI system that can understand complex problems and aims to achieve cognitive abilities like humans
Natural language generation is a type of AI which helps the computer turn data, patterns, or facts into written or spoken words
Language modeling helps computers understand and learn human language. It is used in text generation and machine translation
How to run LLM inference on edge using React Native. This hands-on guide explains how to build mobile apps with on-device language models, all without needing cloud access
Hugging Face and JFrog tackle AI security by integrating tools that scan, verify, and document models. Their partnership brings more visibility and safety to open-source AI development
How Math-Verify is reshaping the evaluation of open LLM leaderboards by focusing on step-by-step reasoning rather than surface-level answers, improving model transparency and accuracy
How Open-source DeepResearch is reshaping the way AI search agents are built and used, giving individuals and communities control over their digital research tools
Explore how π0 and π0-FAST use vision-language-action models to simplify general robot control, making robots more responsive, adaptable, and easier to work with across various tasks and environments
Understand how deconvolutional neural networks work, their roles in AI image processing, and why they matter in deep learning
A simple and clear explanation of what cognitive computing is, how it mimics human thought processes, and where it’s being used today — from healthcare to finance and customer service
What the Adam optimizer is, how it works, and why it’s the preferred adaptive learning rate optimizer in deep learning. Get a clear breakdown of its mechanics and use cases
Looking for the best podcasts about generative AI? Here are ten shows that explain the tech, explore real-world uses, and keep you informed—whether you're a beginner or deep in the field
Access to data doesn’t guarantee better decisions—culture does. Here’s why building a strong data culture matters and how organizations can start doing it the right way
How stochastic in machine learning improves model performance through randomness, optimization, and generalization for real-world applications
Looking to master SQL concepts in 2025? Explore these 10 carefully selected books designed for all levels, with clear guidance and real-world examples to sharpen your SQL skills
What data annotation is, why it matters in machine learning, and how it works across tools, types, and formats. A clear look at real-world uses and common challenges
How One Hot Encoding converts text-based categories into numerical data for machine learning. Understand its role, benefits, and how it handles categorical variables
How temporal graphs in data science reveal patterns across time. This guide explains how to model, store, and analyze time-based relationships using temporal graphs
How Voronoi diagrams help with spatial partitioning in fields like geography, data science, and telecommunications. Learn how they divide space by distance and why they're so widely used
How Monster API simplifies open source model tuning and deployment, offering a faster, more efficient path from training to production without heavy infrastructure work
AI interference lets the machine learning models make conclusions efficiently from the new data they have never seen before
How LLM evaluation is evolving through the 3C3H approach and the AraGen benchmark. Discover why cultural context and deeper reasoning now matter more than ever in assessing AI language models
