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Master the fundamental libraries and frameworks that form the building blocks of modern applications.
Stay updated with the latest AI news this week — from Google’s Nano Banana (Gemini 2.5 Flash Image) to Anthropic’s Claude for Chrome, OpenAI’s Codex IDE integration, Nvidia’s Jetson Thor robot brain, Microsoft’s VibeVoice TTS, and Kling AI 2.1.
Boost your LLM with Gemini URL Context. Ground responses in real-time web data using Google’s GenAI SDK for precise, fresh, and reliable outputs.
A complete 2025 guide to OpenAI’s GPT-OSS model — learn its features, setup process, and practical use cases for developers and AI enthusiasts.
Explore how NeonDB, a serverless PostgreSQL solution, simplifies AI applications with pgvector for vector searches, autoscaling, and branching. Learn to set up NeonDB, run similarity searches, build a to-do app, and integrate an AI chatbot—all with efficient PostgreSQL queries! 🚀
Discover FAISS, the ultimate library for fast similarity search and clustering of dense vectors! This in-depth guide covers setup, vector stores, document management, similarity search, and real-world applications. Master FAISS to build scalable, AI-powered search systems efficiently! 🚀
Discover how to use Giskard to evaluate AI models for performance, bias, and security. Learn to build a climate-focused QA system with LangChain, integrate OpenAI models, and automate testing. Ensure AI reliability with scanning, reporting, and custom test suites.
In this blog post, we delve into smolagents, a powerful library designed to build intelligent agents with code. Whether you're a machine learning enthusiast or a seasoned developer, this guide will help you explore the capabilities of smolagents, showcasing practical applications and use cases.
Llama Parse is a powerful tool designed to transform unstructured data into structured formats, handling sources like PDFs, HTML, and text files. It simplifies large-scale data parsing, enabling seamless integration with workflows and making complex tasks more efficient.
MLflow simplifies the ML lifecycle with tools for tracking experiments, managing models, and ensuring reproducibility. With integrations for generative AI, LangChain, and Transformers, it empowers data scientists to streamline workflows, enhance scalability, and focus on innovation.
Fireworks AI, an open-source platform, empowers you to create advanced generative AI applications. This blog covers setup, key features, and practical examples, equipping you with the knowledge to build cutting-edge solutions and fully leverage Fireworks AI's powerful capabilities.
SentenceTransformers, a Python library, generates sentence embeddings for tasks like semantic similarity, clustering, and summarization. Built on models like BERT, it captures sentence meaning efficiently, enabling use cases such as search engines, topic clustering, and text summarization.
This blog explores the most popular large language models and their integration capabilities for building chatbots, natural language search, and other LLM-based products. We’ll also explain how to choose the right LLM for your business goals and examine real-world use cases.
Create systems where multiple agents work together, building, orchestrating, and managing intelligent agents.
7 articles →Extract, process, and transform raw data into intelligent applications that solve real problems.
9 articles →Tools for testing, evaluating, monitoring, and managing the entire lifecycle of your LLM systems.
2 articles →