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AI Degree offers busy learners a self-paced, 100% online path to mastering artificial intelligence—combining affordability, a comprehensive 42-course curriculum, and hands-on projects with real-world impact. With scholarships, free starter courses, global recognition, and guaranteed internships, it’s designed to fit into your life while equipping you with the skills to thrive in the AI-powered future.

This article explores how AI technology is transforming the cashew nut grading process. It is based on a research paper published by a team of researchers who developed an innovative, low-cost AI-powered grading system.

AI Degree offers busy learners a self-paced, 100% online path to mastering artificial intelligence—combining affordability, a comprehensive 42-course curriculum, and hands-on projects with real-world impact. With scholarships, free starter courses, global recognition, and guaranteed internships, it’s designed to fit into your life while equipping you with the skills to thrive in the AI-powered future.

AI distillation—a process of training smaller, faster models by extracting knowledge from larger ones—has moved from niche research to industry disruptor, thanks to Chinese startup DeepSeek. By leveraging this low-cost, high-impact technique, DeepSeek and others have challenged AI giants like OpenAI and Google, delivering competitive models in weeks for a fraction of the cost. This shift is fueling an open-source wave, slashing AI deployment expenses, and accelerating innovation across industries. While big tech still chases AGI with billion-dollar investments, distilled models are reshaping the market and empowering a new generation of AI builders.

Google’s experimental AI co-scientist, powered by Gemini 2.0, is designed to act as a virtual research collaborator—synthesising vast scientific literature, generating novel hypotheses, and aiding in biomedical breakthroughs from drug repurposing to antimicrobial resistance studies. By orchestrating multiple specialised AI agents, it mirrors the scientific method, rapidly refining ideas and integrating insights across diverse domains. While debate continues over its capacity for true novelty, early results suggest it could transform how science is conducted, making research faster, broader, and more connected than ever.

Evaluating Large Language Models (LLMs) is fast becoming one of the most critical skills in AI. This post breaks down why LLM evals matter, how they differ from model evaluations, and the key metrics, tools, and strategies you need to ensure AI agents work reliably in the real world. Drawing on insights from Arize CEO Aparna Dhinakaran, we explore practical frameworks for testing everything from routers to multimodal agents—so you can measure, debug, and optimize AI systems with confidence."

DeepSeek AI is disrupting the AI industry with its open-source approach, advanced reasoning, and cost efficiency. Learn how it challenges big names like OpenAI and Google while making AI more accessible.

DeepSeek AI is disrupting the AI industry with its open-source approach, advanced reasoning, and cost efficiency. Learn how it challenges big names like OpenAI and Google while making AI more accessible.

Part 4 of a multi-part series where we demystify the terminology behind AI and Machine Learning, breaking down complex concepts into simple, relatable explanations.

This blog talks about the importance of AI guardrails and the role they play in AI systems

This blog talks about the importance of AI guardrails and the role they play in AI systems

Retrieval-Augmented Generation (RAG) is a smart way for AI to find and use real-world information to give better responses. In this blog post, we go over the basics of RAG

An exploration of 2024's groundbreaking AI research papers, simplified to highlight their real-world applications and benefits, making cutting-edge innovations accessible and actionable for everyone.

This blog breaks down some highly demanded AI skills this 2025

Part 3 of a multi-part series where we demystify the terminology behind AI and Machine Learning, breaking down complex concepts into simple, relatable explanations.