From ba5c09bf503887aa79f1b3c4e8c0a605b35a7bf5 Mon Sep 17 00:00:00 2001 From: ealemadi Date: Tue, 28 Jul 2026 15:14:34 +0300 Subject: [PATCH] Add 3 HTML mockups --- mockup1.html | 103 +++++++++++++++++++++++++++++++ mockup2.html | 164 +++++++++++++++++++++++++++++++++++++++++++++++++ mockup3.html | 168 +++++++++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 435 insertions(+) create mode 100644 mockup1.html create mode 100644 mockup2.html create mode 100644 mockup3.html diff --git a/mockup1.html b/mockup1.html new file mode 100644 index 0000000..d5111ac --- /dev/null +++ b/mockup1.html @@ -0,0 +1,103 @@ + + + + + + MyWeb1 - AI Model Differences + + + + +
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AI Model Differences

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Explore how AI models compare in architecture, performance, and real-world capabilities.

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Architecture

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Understand the structural differences between transformer, CNN, RNN, and hybrid models.

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Performance

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Compare speed, accuracy, and resource usage across leading AI models.

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Use Cases

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Discover which model works best for text, images, audio, and multimodal tasks.

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Quick Comparison

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ModelTypeBest ForParameters
GPT-4Transformer (LLM)Text Generation~1.7T
ResNet-50CNNImage Classification25M
WhisperEncoder-DecoderSpeech Recognition1.5B
Stable DiffusionDiffusion ModelImage Generation~1B
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Understanding
AI Models

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A deep dive into the differences between AI architectures, training methods, and real-world performance benchmarks.

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Architecture Breakdown

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From transformers to CNNs, learn what makes each model type unique and how they process information differently.

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02
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Benchmark Data

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Side-by-side performance metrics on standard benchmarks like MMLU, HumanEval, and ImageNet.

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Practical Insights

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Real-world guidance on choosing the right model for your specific application and budget.

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Model Comparisons

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GPT-4 vs Claude 3

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Both are frontier LLMs, but differ in context window size, reasoning style, and safety alignment approaches.

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+ Vision +

GPT-4V vs Gemini

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Multi-modal models compared on image understanding, document parsing, and visual reasoning tasks.

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+ Generation +

DALL-E vs Midjourney

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Image generation models compared on prompt adherence, artistic quality, and photorealism.

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+ Open Source +

Llama 3 vs Mistral

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Open-weight models compared on efficiency, fine-tuning flexibility, and community support.

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AI Research · Updated 2026
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The Differences Behind AI Models

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An interactive guide to understanding how AI models differ in design, training, and output.

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What You'll Learn

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Key areas where AI models differ from each other

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🏗️
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Model Architecture

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Transformers, diffusion models, GANs, and more — how each processes data internally.

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Training Data

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How dataset size, quality, and diversity shape model behavior and bias.

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Fine-Tuning

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RLHF, LoRA, and prompt engineering — adapting models to specific tasks.

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Benchmarks

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Standardized tests that reveal strengths and weaknesses across models.

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💰
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Cost & Access

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Open-source vs proprietary, pricing, and API limitations compared.

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🔮
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Future Trends

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Emerging architectures and where the AI field is heading next.

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Models Compared
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Categories
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Benchmarks Tracked
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Start Comparing

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Dive into detailed model breakdowns and find the right AI for your needs.

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