L7: Key Technologies Behind LLMs (GPT, BERT)

L7: Key Technologies Behind LLMs (GPT, BERT)

2:05:21

Large Language Models (LLMs) like ChatGPT work because of powerful underlying technologies. Two of the most important ones are GPT and BERT.
They are not applications themselves—they are model architectures that teach machines how to understand and generate human language.

Let’s understand them step by step, in simple terms.

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What Does “Key Technologies Behind LLMs” Mean?

It means the core models and techniques that make LLMs smart enough to:

• Understand language

• Generate meaningful text

• Answer questions

• Translate languages

• Summarize documents

Among many models, GPT and BERT are the most influential.

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GPT (Generative Pre-trained Transformer)

What is GPT?

GPT stands for Generative Pre-trained Transformer.

In simple words:

GPT is a model that reads text and predicts the next word.

Example:

“AI is changing the world by making machines more ___”

GPT predicts: intelligent

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How GPT Works (Simple View)

1. GPT reads a large amount of text (books, articles, code, etc.)

2. It learns patterns in language

3. It predicts the next word based on previous words

4. It repeats this process to generate full sentences and paragraphs

This is why GPT is great at text generation.

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Key Characteristics of GPT

• Reads text from left to right

• Very good at:

  • Writing text

  • Chatbots

  • Code generation

  • Storytelling

• Used in:

  • ChatGPT

  • GitHub Copilot

  • AI writing tools

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BERT (Bidirectional Encoder Representations from Transformers)

What is BERT?

BERT is a model that focuses on understanding language , not generating it.

In simple words:

BERT reads a sentence from both sides to understand meaning.

Example:

“He went to the bank to deposit money.”

BERT understands:

• “bank” = financial institution
  (not river bank)

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How BERT Works (Simple View)

1. BERT looks at the full sentence at once

2. It understands context using words before and after

3. It focuses on meaning , not text generation

This makes BERT excellent at language understanding tasks.

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Key Characteristics of BERT

• Reads text both left and right

• Very good at:

  • Search

  • Question answering

  • Text classification

  • Sentiment analysis

• Used in:

  • Google Search

  • Chatbots for understanding queries

  • Document analysis systems

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GPT vs BERT (Conceptual Difference)

AspectGPTBERTMain strengthText generationText understandingDirectionLeft → RightBoth directionsBest forChatbots, writing, codeSearch, classificationOutput styleGenerates textAnalyzes text

👉 GPT = Speaker
👉 BERT = Listener

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Why GPT & BERT Are Important for LLMs

Modern LLMs are inspired by or built upon these models:

• GPT shows how machines can generate human-like language

• BERT shows how machines can deeply understand context

Together, they form the foundation of today’s AI language systems.

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Real-World Examples

• ChatGPT → GPT-based

• Google Search → BERT-based

• AI email assistants → GPT + BERT concepts

• Customer support bots → Understanding (BERT) + Reply (GPT)

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Key Takeaways

• GPT and BERT are core technologies behind LLMs

• GPT focuses on generation

• BERT focuses on understanding

• Most modern AI systems use ideas from both

• Knowing these helps you understand how GenAI really works