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Introduction to GPT-4 and Transformer Architectures
- Difference between GPT-3 and GPT-4 architectures
- Understanding transformer models
- Role of attention mechanisms in NLP
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Core Concepts in Language Models
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Integrating ChatGPT API into Applications
- Making HTTP requests to ChatGPT API
- Handling JSON responses from API
- Error handling in API integrations
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Building Applications with ChatGPT
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Ethical Considerations and Responsible AI Usage
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Customizing and Evaluating AI Models
- Customizing AI models for specific tasks
- Training and fine-tuning on custom datasets
- Evaluating performance against benchmarks
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Implications of AI-generated Content
A deep dive into transformer models is necessary as they are the foundational architecture for modern language models like GPT-4, providing insights into their functionality and application.
Attention in transformers, step-by-step | DL6
Attention is all you need (Transformer) - Model explanation (including math), Inference and Training
The Attention Mechanism 1 hour explanation