Generative AI

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What is RAFT? RAG + Fine-Tuning

In simple terms, retrieval-augmented fine-tuning, or RAFT, is an advanced AI technique in which retrieval-augmented generation is joined with fine-tuning to enhance generative responses from a large language model for specific applications in that particular domain. It allows the large language models to provide more accurate, contextually relevant, and robust results, especially for targeted sectors […]

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Instruction Tuning for Large Language Models

The model is exposed to diverse examples of instructions, ranging from simple queries to complex multi-step tasks. This helps the model learn to interpret and execute instructions accurately, making it more usable and adaptable. To strengthen LLMs’ ability to comprehend and act on instructions, instruction tuning datasets from LLM data companies like Cogito Tech can

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Top Agentic AI Training Data Companies 2026

Agentic AI is defined as a system of AI agents. This system collaborates to complete complex tasks with minimal human intervention. Data is assessed, options are observed, and actions are sequentially planned, executed, and implemented autonomously. Large Language Models (LLMs) are integrated with modules for decision-making, memory, workflow control, and planning. Consequently, multistage problems are

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Top Generative AI Training Data Companies 2026

Large-scale training datasets help generative AI models learn linguistic and perceptual structures, enabling pattern recognition and contextual comprehension. Exposure to diverse text, visual, and auditory data builds world knowledge and common-sense reasoning, while emotion-labeled and dialogue data train models to simulate empathy and tonal variation. Human feedback through RLHF further aligns model behavior with social

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The AI Training Data Watershed: Why the $1.5B Anthropic Settlement Changes Everything

For years, creative professionals have unknowingly provided raw materials making modern AI possible. Photographers sharing portfolios online, models contributing biometric data through professional shoots, and writers publishing content across digital platforms—all have been building the datasets that power today’s AI […] The post The AI Training Data Watershed: Why the $1.5B Anthropic Settlement Changes Everything

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Google’s AI-Powered Ambition: A New Pixel Ecosystem Takes Aim at Apple

This past week in New York, Google didn’t just launch a new set of phones; it laid out its most cohesive and aggressive vision yet for an AI-powered future, presenting a direct and compelling challenge to Apple’s dominance. The event […] The post Google’s AI-Powered Ambition: A New Pixel Ecosystem Takes Aim at Apple appeared

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7 Latest AI Drops by Google Will Make You a Powerhouse at Work

Google has just dropped its biggest wave of AI updates in months. The best part – each one rewires how we get things done. And to add to that, this range of AI tools and features span across generating content, solving problems, and even getting multi-step, complicated tasks done by the power of AI. From

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Deep Agents Tutorial: Create Advanced AI Agents with LangGraph and Web Search Tools 

Imagine an AI that doesn’t just answer your questions, but thinks ahead, breaks tasks down, creates its own TODOs, and even spawns sub-agents to get the work done. That’s the promise of Deep Agents. AI Agents already take the capabilities of LLMs a notch higher, and today we’ll look at Deep Agents to see how

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DeepSeek Math V2 Guide: Smarter AI for Real Math

If you’ve been following the AI space lately, you’ve probably noticed something big: people don’t just care what an AI answers anymore, they care how it reaches that answer. And that’s exactly where DeepSeek Math V2 steps in. It’s an open-source model built specifically for real mathematical reasoning. In this guide, I’ll walk you through what DeepSeek Math V2

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