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OThink-R1: A Dual-Mode Reasoning Framework to Cut Redundant Computation in LLMs

The Inefficiency of Static Chain-of-Thought Reasoning in LRMs Recent LRMs achieve top performance by using detailed CoT reasoning to solve complex tasks. However, many simple tasks they handle could be solved by smaller models with fewer tokens, making such elaborate reasoning unnecessary. This echoes human thinking, where we use fast, intuitive responses for easy…

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Building AI-Powered Applications Using the Plan → Files → Code Workflow in TinyDev

In this tutorial, we introduce TinyDev class implementation, a minimal yet powerful AI code generation tool that utilizes the Gemini API to transform simple app ideas into comprehensive, structured applications. Designed to run effortlessly in Notebook, TinyDev follows a clean three-phase workflow—Plan → Files → Code—to ensure consistency, functionality, and modular design. Whether building…

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Microsoft AI Introduces Code Researcher: A Deep Research Agent for Large Systems Code and Commit History

Rise of Autonomous Coding Agents in System Software Debugging The use of AI in software development has gained traction with the emergence of large language models (LLMs). These models are capable of performing coding-related tasks. This shift has led to the design of autonomous coding agents that assist or even automate tasks traditionally carried…

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Internal Coherence Maximization (ICM): A Label-Free, Unsupervised Training Framework for LLMs

Post-training methods for pre-trained language models (LMs) depend on human supervision through demonstrations or preference feedback to specify desired behaviors. However, this approach faces critical limitations as tasks and model behaviors become very complex. Human supervision is unreliable in these scenarios as LMs learn to mimic mistakes in demonstrations or exploit inherent flaws in…

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MemOS: A Memory-Centric Operating System for Evolving and Adaptive Large Language Models

LLMs are increasingly seen as key to achieving Artificial General Intelligence (AGI), but they face major limitations in how they handle memory. Most LLMs rely on fixed knowledge stored in their weights and short-lived context during use, making it hard to retain or update information over time. Techniques like RAG attempt to incorporate external…

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How AI and Virtual Assistant help.

986 Photos   |   24 Courses   |   18 Nominations


Ready to kickstart your career as a Virtual Assistant? This free YouTube course is designed to guide you — even if you’re starting from scratch. Learn essential VA skills, tools, and strategies to land clients, build your profile, and work from anywhere.

✅ What You’ll Learn:

  • What a Virtual Assistant is and what they do
  • Top skills every successful VA should master
  • How to create a winning profile and proposal
  • Tools (including AI!) to boost your productivity
  • Real client examples and platforms to apply on

No experience? No problem! Start learning today and become a confident, skilled Virtual Assistant — for free!

AI tools are transforming the way we work, create, and communicate. From writing emails and generating images to automating tasks and analyzing data, these smart tools help individuals and businesses save time, boost productivity, and stay competitive in the digital age.

Whether you’re a freelancer, virtual assistant, marketer, content creator, or entrepreneur — AI tools can simplify your workflow and unlock powerful results..

🔍 With AI Tools, You Can:

🎥 Create content, captions, and videos with ease

✍️ Write faster with tools like ChatGPT

🎨 Design stunning graphics using Canva AI

🧠 Brainstorm ideas and strategies in seconds

📅 Automate repetitive tasks and save hours daily

📈 Make smarter decisions with AI-powered analytics


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