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Concepts, frameworks, and innovations in artificial intelligence, from general AI theories to real-world applications.
In the past year, most enterprises have been focusing on generative AI pilots. However, many are stuck at this stage due to inadequate data readiness. This article explores these challenges and insights from Edward Calvesbert, Vice President of Product Management for watsonx.data at IBM. The Core Issues in AI-Ready Data According to Calvesbert, the main…
Retrieval-Augmented Generation (RAG) is an AI architecture that combines the power of Large Language Models (LLMs) with external knowledge retrieval systems to generate more accurate, relevant, and up-to-date responses. Instead of relying only on the information learned during training, a RAG system retrieves relevant information from documents, databases, websites, knowledge bases, or vector databases before…
Artificial Intelligence is evolving beyond simple chatbots and predictive models. A new paradigm known as Agentic AI is transforming how machines interact with the world by enabling them to make decisions, take actions, and pursue goals with minimal human intervention. As organizations increasingly seek automation and intelligent decision-making, Agentic AI has emerged as one of…
Introduction Artificial Intelligence development has evolved rapidly, but two names consistently define the modern developer stack: OpenAI and Hugging Face. Both platforms have shaped the AI landscape. OpenAI popularized frontier large language models through ChatGPT and managed APIs, while Hugging Face became the central ecosystem for open-source AI collaboration, model hosting, and custom deployment. For…
Introduction Over the past few years, Artificial Intelligence has moved from research laboratories into everyday software. Today, AI powers customer support systems, recommendation engines, search platforms, content creation tools, coding assistants, healthcare applications, and countless other technologies that millions of people use daily. As AI adoption continues to accelerate, one platform has emerged as a…
Introduction If Hugging Face is often called the GitHub of Artificial Intelligence, then the Transformers library is the engine that powers much of the modern AI revolution. Today, many of the world’s most advanced AI applications—including chatbots, virtual assistants, translation systems, coding copilots, content generators, and intelligent search engines—are built using transformer-based models. For beginners…
Introduction The rapid growth of Artificial Intelligence has created an unprecedented demand for powerful foundation models capable of understanding language, generating content, writing code, analyzing images, and solving complex reasoning tasks. While thousands of AI models are available today, only a small percentage have achieved widespread adoption among developers, researchers, startups, and enterprises. The Hugging…
Introduction Artificial Intelligence has evolved rapidly over the last few years, and two names consistently appear at the center of that transformation: OpenAI and Hugging Face. While both organizations play critical roles in advancing AI, they serve fundamentally different purposes within the ecosystem. OpenAI is best known for developing powerful proprietary models such as GPT,…
For decades, many organizations have relied on powerful, custom-built, on-premises systems. These Monolithic Systems have been the backbone of global commerce. Today, the demands of the market have fundamentally changed. They require speed, personalization, and intelligence at every touchpoint. This new era mandates a commitment to Digital Transformation. The challenge is clear. How can companies…
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