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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
Grasping the concept of tokens is fundamental to understanding how language models interpret and generate text, making this knowledge crucial for effective model training and usage.
How Large Language Models Work
Parameters vs Tokens: What Makes a Generative AI Model Stronger? 💪
Large Language Models explained briefly