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A collection of 269 posts

How Prompt Caching Helps to Reduce AI Cost

How Prompt Caching Helps to Reduce AI Cost

Prompt caching has emerged as a powerful strategy for reducing the operational costs and improving the efficiency of AI systems, especially those powered by large language models (LLMs) like OpenAI’s GPT, Anthropic’s Claude, and others. As AI adoption accelerates across industries, understanding how prompt caching works and how

Running DeepSeek Prover V2 7B on Linux: A Complete Guide

Running DeepSeek Prover V2 7B on Linux: A Complete Guide

DeepSeek Prover V2 7B is an open-source large language model designed specifically for formal theorem proving, particularly in the Lean 4 proof assistant language. It excels at formal mathematical reasoning by generating precise proofs, making it a powerful tool for researchers, educators, and enthusiasts in mathematics and computer science. This

Running DeepSeek Prover V2 7B on Ubuntu: Complete Installation Guide

Running DeepSeek Prover V2 7B on Ubuntu: Complete Installation Guide

Running DeepSeek Prover V2 7B on Ubuntu involves a detailed process that includes setting up your environment, preparing GPU infrastructure, installing dependencies, and configuring the model for local or cloud-based use. This guide walks you through all essential steps to get DeepSeek Prover V2 7B up and running on an

Running DeepSeek Prover V2 7B on Windows: A Complete Setup Guide

DeepSeek Prover V2

Running DeepSeek Prover V2 7B on Windows: A Complete Setup Guide

Running DeepSeek Prover V2 7B on Windows involves several key steps—ranging from environment preparation to downloading and executing the model. This guide walks you through everything you need to install and run DeepSeek Prover V2 7B on a Windows system effectively. What Is DeepSeek Prover V2 7B? DeepSeek Prover

Running DeepSeek Prover V2 7B on macOS: A Comprehensive Guide

Running DeepSeek Prover V2 7B on macOS: A Comprehensive Guide

DeepSeek Prover V2 7B is an advanced open-source large language model designed specifically for formal theorem proving in Lean 4. Running this powerful AI model locally on macOS brings benefits such as enhanced privacy, reduced latency, and cost savings compared to cloud-based alternatives. This guide walks you through everything needed

How to Use Generative AI for Mobile Computing

mobile computing

How to Use Generative AI for Mobile Computing

Generative AI is rapidly transforming the landscape of mobile computing, enabling a new era of intelligent, adaptive, and creative mobile applications. From personalized user experiences to automated content creation and advanced network management, generative AI is reshaping what is possible on smartphones and other mobile devices. This article provides a

How to add MCP to any React App

How to add MCP to any React App

Adding Managed Copilot Protocol (MCP) to a React application enables seamless integration with AI-powered tools and services. This guide walks you through implementing MCP in any React or Next.js app using CopilotKit. Initial Setup and Project Configuration If you're starting fresh, create a new Next.js application:

Install Qwen 2.5- Omni 3B on Ubuntu

Install Qwen 2.5- Omni 3B on Ubuntu

Qwen2.5-Omni 3B is an advanced multimodal AI model capable of processing text, image, audio, and video in a single, 3-billion-parameter architecture. This guide provides step-by-step instructions for installing Qwen2.5-Omni 3B on Ubuntu, including three different installation methods optimized for GPU usage. System Requirements Hardware Specifications * Minimum * 16GB RAM

Install Qwen2.5-Omni 3B on Windows

Install Qwen2.5-Omni 3B on Windows

Qwen2.5-Omni 3B is Alibaba Cloud’s compact, multimodal AI model optimized for local deployment on consumer-grade hardware. Unlike the 7B variant, the 3B model significantly reduces VRAM usage—by more than 50%—while maintaining robust performance across text, image, audio, and video tasks. With real-time output and simultaneous multimodal

Install Qwen2.5-Omni 3B on macOS

Install Qwen2.5-Omni 3B on macOS

Qwen2.5-Omni 3B is a cutting-edge multimodal AI model developed to handle text, image, audio, and video processing tasks. While macOS doesn't offer the same native GPU acceleration as Linux or Windows systems, it's still possible to run Qwen2.5-Omni 3B locally with some optimization. This

Gemma 3 vs Qwen 3: In-Depth Comparison of Two Leading Open-Source LLMs

Gemma 3 vs Qwen 3: In-Depth Comparison of Two Leading Open-Source LLMs

The rapid evolution of large language models (LLMs) has brought forth a new generation of open-source AI models that are more powerful, efficient, and versatile than ever. Two of the most prominent contenders in 2024–2025 are Gemma 3 by Google and Qwen 3 by Alibaba. Both models have attracted

Nari Dia 1.6B vs ElevenLabs: Which Is the Best TTS Solution?

Nari Dia 1.6B vs ElevenLabs: Which Is the Best TTS Solution?

The text-to-speech (TTS) landscape has evolved rapidly, with new entrants challenging established leaders. Two of the most talked-about TTS models in 2025 are Nari Labs’ open-source Dia 1.6B and the commercial powerhouse ElevenLabs. Both promise lifelike, expressive speech synthesis, but their approaches, capabilities, and accessibility differ significantly. This in-depth

Nari Dia 1.6B vs Sesame CSM 1B: Which Is the Best TTS?

Nari Dia 1.6B vs Sesame CSM 1B: Which Is the Best TTS?

Text-to-speech (TTS) technology has seen rapid advancements, evolving from robotic voices to lifelike AI-generated speech. In 2025, two of the leading open-source models are Nari Dia 1.6B and Sesame CSM 1B. Both offer impressive capabilities in realistic speech synthesis, but they cater to different use cases and offer distinct

Run Microsoft Phi 4 on Windows: An Installation Guide

Run Microsoft Phi 4 on Windows: An Installation Guide

Microsoft's Phi-4 represents a breakthrough in efficient language models, offering state-of-the-art reasoning capabilities with its 14-billion parameter architecture. While originally designed for Linux environments, this guide provides detailed methodologies for Windows users to harness its multimodal capabilities. System Requirements Hardware Specifications 1. CPU: * Minimum: 8-core Intel i7/Ryzen

Run Microsoft Phi-4 on Ubuntu: A Comprehensive Guide

Run Microsoft Phi-4 on Ubuntu: A Comprehensive Guide

Microsoft’s Phi-4 is a state-of-the-art multimodal AI model, capable of advanced language, vision, and audio understanding. Running Phi-4 locally on Ubuntu allows developers, researchers, and enthusiasts to leverage its capabilities. What is Microsoft Phi-4? Microsoft Phi-4 is a cutting-edge multimodal AI model, designed to process and generate text, understand

Run Microsoft Phi 4 on Mac: Installation Guide

Run Microsoft Phi 4 on Mac: Installation Guide

Microsoft's Phi-4 models represent a breakthrough in efficient language model design, offering advanced natural language capabilities while maintaining hardware accessibility. This guide covers all technical aspects of running Phi-4 Mini and Phi-4 Noesis variants on macOS, including architectural considerations, installation procedures, optimization strategies, and practical applications. Model Architecture

MCP vs API: Differences, Similarities, and Benefits

MCP vs API: Differences, Similarities, and Benefits

The landscape of software integration and automation is evolving rapidly, especially with the rise of AI-driven systems. Two key technologies at the center of this transformation are MCP (Model Context Protocol) and API (Application Programming Interface). While both act as communication bridges between software systems, their design, use cases, and

Run Qwen3-8B on Ubuntu: A Comprehensive Guide

Run Qwen3-8B on Ubuntu: A Comprehensive Guide

Qwen3-8B is one of the latest large language models (LLMs) from Alibaba's Qwen series, designed for high performance and versatility in a wide range of natural language processing tasks. Running Qwen3-8B locally on Ubuntu allows developers and researchers to leverage its capabilities without relying on cloud APIs, ensuring

Running Qwen3 8B on Windows: A Comprehensive Guide

Running Qwen3 8B on Windows: A Comprehensive Guide

Qwen3 8B is a powerful, open-source large language model (LLM) developed as part of the Qwen3 series, designed for advanced reasoning, coding, and multilingual tasks5. Running such a model locally on Windows unlocks privacy, flexibility, and the ability to experiment with AI without relying on cloud services. This guide provides

Run Qwen 3 8B on Mac: An Installation Guide

Run Qwen 3 8B on Mac: An Installation Guide

Qwen 3 8B is a powerful open-source large language model (LLM) developed by Alibaba’s QwenLM team. With 8 billion parameters, it strikes a balance between capability and resource requirements, making it suitable for local deployment on modern Macs with Apple Silicon (M1, M2, M3, or newer). System Requirements Before

Run Kimi-Audio on Ubuntu: Installation and Usage Guide

Run Kimi-Audio on Ubuntu: Installation and Usage Guide

Kimi-Audio is Moonshot AI's state-of-the-art 7B parameter audio foundation model capable of speech recognition, audio generation, and multimodal conversations. System Requirements Hardware * GPU: Minimum NVIDIA RTX 3090 (24GB VRAM) / Recommended RTX 6000 Ada (48GB VRAM)16 * RAM: 64GB DDR4 minimum * Storage: 100GB+ free SSD space (for models and

Running Kimi-Audio on Windows: An Installation Guide

Running Kimi-Audio on Windows: An Installation Guide

Kimi-Audio is an open-source audio foundation model capable of speech recognition, audio generation, and conversational AI tasks. While primarily designed for Linux environments, this guide provides detailed instructions for Windows users to leverage its capabilities through multiple methods. I. System Requirements 1. Hardware Specifications * GPU: NVIDIA GPU with ≥24GB VRAM

Running Kimi-Audio on Mac: A Complete Guide

Running Kimi-Audio on Mac: A Complete Guide

Kimi-Audio is a universal audio foundation model capable of audio understanding, generation, and processing. Kimi-Audio is an open-source AI model designed for audio-to-text (ASR) and audio-to-audio/text conversation tasks This guide adapts the workflow for macOSSystem Requirements and Compatibility Hardware Requirements * Apple Silicon (M1/M2/M3) or Intel-based Mac: * M-series

How to use DeepWiki?

How to use DeepWiki?

DeepWiki is a revolutionary AI-powered platform that transforms the way developers, students, and open-source enthusiasts interact with code repositories. Launched by Cognition AI in April 2025. DeepWiki leverages advanced large language models (LLMs) and sophisticated code analysis techniques to generate dynamic, interactive documentation for public GitHub repositories. With over 30,

What is DeepWiki?

What is DeepWiki?

DeepWiki is an advanced AI-powered platform designed to revolutionize how developers and researchers interact with code repositories, particularly those hosted on GitHub. By leveraging state-of-the-art large language models (LLMs) and sophisticated code analysis techniques, DeepWiki automatically generates comprehensive, interactive, and dynamic documentation for software projects. It transforms complex codebases into