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How to Build a Universal Long-Term Memory Layer for AI Agents Using Mem0 and OpenAI

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Infrastructure, Applications, Artificial Intelligence, Editors Pick, Machine Learning, Software engineering, Staff, Technology, Tutorials

In this tutorial, we build a universal long-term memory layer for AI agents using Mem0, OpenAI models, and ChromaDB. We design a system that can extract structured memories from natural conversations, store them semantically, retrieve them intelligently, and integrate them directly into personalized agent responses. We move beyond simple chat history and implement persistent, user-scoped […]

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A Coding Implementation to Build Multi-Agent AI Systems with SmolAgents Using Code Execution, Tool Calling, and Dynamic Orchestration

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Infrastructure, Artificial Intelligence, Editors Pick, Staff, Technology, Tutorials

In this tutorial, we build an advanced, production-ready agentic system using SmolAgents and demonstrate how modern, lightweight AI agents can reason, execute code, dynamically manage tools, and collaborate across multiple agents. We start by installing dependencies and configuring a powerful yet efficient LLM backend, and then progressively design custom tools, including mathematical utilities, memory storage,

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A Technical Deep Dive into the Essential Stages of Modern Large Language Model Training, Alignment, and Deployment

ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Large Language Model, Technology

Table of contentsPre-TrainingSupervised FinetuningLoRAQLoRARLHFReasoning (GRPO)Deployment Training a modern large language model (LLM) is not a single step but a carefully orchestrated pipeline that transforms raw data into a reliable, aligned, and deployable intelligent system. At its core lies pretraining, the foundational phase where models learn general language patterns, reasoning structures, and world knowledge from massive

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Google AI Launches Gemini 3.1 Flash TTS: A New Benchmark in Expressive and Controllable AI Voice

agentic ai, ai, AI (Artificial Intelligence), Artificial Intelligence, Audio Language Model, Editors Pick, Language Model, New Releases, Staff, Technology, TTS, Voice AI

Google has introduced Gemini 3.1 Flash TTS, a preview text-to-speech model focused on improving speech quality, expressive control, and multilingual generation. Unlike previous iterations that prioritized simple conversion, this release emphasizes natural-language audio tags, native support for more than 70 languages, and native multi-speaker dialogue. This release signals a shift from ‘black-box’ audio generation toward

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Google DeepMind Releases Gemini Robotics-ER 1.6: Bringing Enhanced Embodied Reasoning and Instrument Reading to Physical AI

agentic ai, ai, AI (Artificial Intelligence), Artificial General Intelligence, Artificial Intelligence, Computer vision, Editors Pick, New Releases, physical ai, Robotics, Staff, Technology, Uncategorized

Google DeepMind research team introduced Gemini Robotics-ER 1.6, a significant upgrade to its embodied reasoning model designed to serve as the ‘cognitive brain’ of robots operating in real-world environments. The model specializes in reasoning capabilities critical for robotics, including visual and spatial understanding, task planning, and success detection — acting as the high-level reasoning model

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Google Launches ‘Skills’ in Chrome: Turning Reusable AI Prompts into One-Click Browser Workflows

agentic ai, ai, AI (Artificial Intelligence), AI Agents, Applications, Artificial Intelligence, Editors Pick, New Releases, Staff

Google just announced the release of Skills in Chrome, a new feature built into Gemini in Chrome that lets users save frequently used AI prompts as reusable, one-click workflows called Skills. The rollout begins April 14, 2026, targeting Mac, Windows, and ChromeOS users who have their Chrome language set to English-US. If you’ve been paying

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A Coding Implementation of Crawl4AI for Web Crawling, Markdown Generation, JavaScript Execution, and LLM-Based Structured Extraction

agentic ai, ai, AI (Artificial Intelligence), AI Infrastructure, Applications, Artificial Intelligence, Editors Pick, Language Model, Staff, Technology, Tutorials

In this tutorial, we build a complete and practical Crawl4AI workflow and explore how modern web crawling goes far beyond simply downloading page HTML. We set up the full environment, configure browser behavior, and work through essential capabilities such as basic crawling, markdown generation, structured CSS-based extraction, JavaScript execution, session handling, screenshots, link analysis, concurrent

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TinyFish AI Releases Full Web Infrastructure Platform for AI Agents: Search, Fetch, Browser, and Agent Under One API Key

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Infrastructure, AI Shorts, Applications, Artificial Intelligence, Editors Pick, New Releases, Promote, Software engineering, sponsored, Staff, Tech News, Technology, Uncategorized

AI agents struggle with tasks that require interacting with the live web — fetching a competitor’s pricing page, extracting structured data from a JavaScript-heavy dashboard, or automating a multi-step workflow on a real site. The tooling has been fragmented, requiring teams to stitch together separate providers for search, browser automation, and content retrieval. TinyFish, a

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TinyFish Launches Full Web Infrastructure Platform for AI Agents — Search, Fetch, Browser, and Agent Under One API Key

TinyFish Launches Full Web Infrastructure Platform for AI Agents — Search, Fetch, Browser, and Agent Under One API Key Read More »

NVIDIA and the University of Maryland Researchers Released Audio Flamingo Next (AF-Next): A Super Powerful and Open Large Audio-Language Model

ai, AI (Artificial Intelligence), AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Audio Language Model, Editors Pick, Language Model, Large Language Model, New Releases, Open Source, Staff, Tech News, Technology, Uncategorized, Voice AI

Understanding audio has always been the multimodal frontier that lags behind vision. While image-language models have rapidly scaled toward real-world deployment, building open models that robustly reason over speech, environmental sounds, and music — especially at length — has remained quite hard. NVIDIA and the University of Maryland researchers are now taking a direct swing

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