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OpenAI has made a bold move into the open-source community by releasing a new family of models: GPT-OSS. This guide will introduce you to these powerful, open-weight models, their technical specifications, and how you can start running them on your own hardware for agentic workflows and advanced reasoning tasks.
GPT-5 is here and it’s redefining AI. With a huge 400k-token context, advanced reasoning, and powerful multimodal skills, it’s built for more than chat. From coding to research, GPT-5 delivers smarter, faster, safer results—making it the most capable AI agent yet.
JCacheX is a fast, production‑ready Java caching library with profile‑based tuning, rich eviction strategies, Spring Boot integration, Kotlin extensions, and optional Kubernetes‑native distributed caching.
Step-by-step guide to building a neural network from scratch using Python and NumPy, with forward propagation, backpropagation, and training examples.
Multimodal models integrate text, images, audio, and video into unified AI systems. Learn how they work, their development process, and how they handle data storage for optimal performance.
Explore how Large Language Models (LLMs) reason step-by-step using CoT, RAG, tools, and more to solve problems accurately and think like humans.
A detailed comparison of CPUs, GPUs, and TPUs, covering their architecture, performance, and real-world applications, with example calculations to demonstrate their capabilities.
Learn TensorFlow from scratch with this beginner-friendly guide. Build, train, and evaluate a neural network using the MNIST dataset with step-by-step examples.
Transformers power AI models like GPT-4 and BERT, enabling machines to understand and generate human-like text, transforming how we interact with technology.
Discover how to create, fine-tune, and deploy powerful LLMs with customized Retrieval-Augmented Generation (RAG) using Ollama. Learn best practices, optimize performance, and integrate RAG for accurate, domain-specific responses.