What is the difference between a standard Transformer and a Mixture-of-Experts (MoE) architecture?

A standard transformer model typically activates all of its parameters for every single word it generates, which can be computationally expensive. In contrast, a Mixture-of-Experts architecture like Gemini or DeepSeek functions like a specialized hospital with different departments. It uses a gating network to act as a triage nurse, routing specific requests to a small sub-network of "expert" parameters best suited for the task, such as coding or legal analysis. This modular approach allows the model to be much more efficient and faster while maintaining a massive knowledge base.

How does Reinforcement Learning from Human Feedback (RLHF) differ from Constitutional AI?

RLHF relies on human annotators to rank different versions of a model's responses, essentially rewarding the AI for clarity, politeness, and accuracy, much like training a puppy with treats. Constitutional AI, a method used by teams like Anthropic, takes this a step further by providing the model with a written "constitution" of ethical principles. The model then uses these rules to critique its own responses during training. This self-critique mechanism helps the AI develop an internal "conscience" to mitigate hallucinations and maintain safety without requiring constant human supervision.

Why is "Data Management" considered the most critical stage of the Model Lifecycle Management (MLM)?

Data Management is the foundation of the entire AI lifecycle because the quality of the output is entirely dependent on the quality of the input, a principle known as "garbage in, garbage out." This stage involves the unglamorous work of sourcing, cleaning, and visualizing information to fix inconsistent formats and remove biases. If the data is messy or biased, the resulting model will produce flawed predictions regardless of how powerful the underlying algorithm is.

What are "Data Drift" and "Concept Drift," and how are they managed?

Data drift and concept drift occur when a model becomes less accurate over time because the real-world data it encounters begins to change from the data it was originally trained on. To manage this, developers enter a Monitoring and Maintenance phase after the model is deployed. They often use a "canary deployment" to test the model on a small percentage of users first and implement Continuous Integration and Continuous Deployment (CI/CD) pipelines to automatically retrain and update the model as new data becomes available.

How has the increase in "context length" changed the way we interact with AI?

Context length refers to the amount of information a model can "hold in its head" at one time. While early models could only remember a few pages of text, modern models can process up to a million tokens, allowing them to analyze entire codebases, long legal contracts, or hour-long videos without forgetting the beginning. Technical innovations like FlashAttention and Rotary Positional Embeddings allow the model to track the position of words across these vast distances efficiently, turning the AI into a tool that can find a "needle in a haystack" within massive datasets.

Under the Hood: The Life Cycle of LLMs

14 min

2 мар. 2026 г.

AI Technology Science

Explore the evolution of Large Language Models from raw pre-training to human-aligned tools. This deep dive covers transformer architecture, fine-tuning, and the ethical governance required for production-ready AI.

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We have moved from a 'one-size-fits-all' approach to a modular, dynamic system that adapts its internal structure to the complexity of your prompt.

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Artificial Intelligence and Generative AI for Beginners

What Is ChatGPT Doing ... and Why Does It Work?

A Brief History of Artificial Intelligence

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Under the Hood: The Life Cycle of LLMs

14 min

2 мар. 2026 г.

AI Technology Science

Лучшая цитата из Under the Hood: The Life Cycle of LLMs

We have moved from a 'one-size-fits-all' approach to a modular, dynamic system that adapts its internal structure to the complexity of your prompt.

Часть плана обучения

large language models

ПЛАН ОБУЧЕНИЯ

large language models

1 h 57 m•4 Эпизоды

deep learning, ML

ПЛАН ОБУЧЕНИЯ

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3 h 12 m•4 Эпизоды

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Advance Beyond Beginner AI Courses

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2 h 40 m•4 Эпизоды

Ключевые выводы

Under the Hood of the Transformer

0:00

The Evolution of the Digital Architect—From GPT to the Modern Frontier

1:04

1:53

Mastering the Life Cycle—The Disciplined Path to Production

2:57

3:57

The Human Touch—How Alignment Bridges the Gap to Helpful AI

5:02

5:57

Expanding the Horizon—The Power of Long Context and Multimodality

6:55

7:56

Navigating the Ethical Maze—Governance and the Responsibility of Scale

8:53

9:49

A Practical Playbook—Your Step-by-Step Guide to AI Success

10:43

11:31

Closing Reflections—The Human Element in the Machine

12:30

13:22

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Этот аудиоурок был создан участником сообщества BeFreed

Вопрос для ввода

The ins and outs of AI, LLMs, training and more. I want a well rounded and thorough understanding.

Голоса ведущих

Jackson

Стиль обучения

Быстрый

Источники знаний

Часто задаваемые вопросы

Узнать больше

I want to learn the fundamentals of LLMs

ПЛАН ОБУЧЕНИЯ

I want to learn the fundamentals of LLMs

1 h 56 m•4 Разделы

Neural Networks and LLM

ПЛАН ОБУЧЕНИЯ

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ПЛАН ОБУЧЕНИЯ

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ПЛАН ОБУЧЕНИЯ

Frontier knowledge is llm

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ПЛАН ОБУЧЕНИЯ

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Создано выпускниками Колумбийского университета в Сан-Франциско

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"Reading used to feel like a chore. Now it’s just part of my lifestyle."

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"Reading used to feel like a chore. Now it’s just part of my lifestyle."

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"Feels effortless compared to reading. I’ve finished 6 books this month already."

@djmikemoore

"BeFreed turned my guilty doomscrolling into something that feels productive and inspiring."

@Pitiful

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"BeFreed turned my commute into learning time. 20-min podcasts are perfect for finishing books I never had time for."

@SofiaP

"BeFreed replaced my podcast queue. Imagine Spotify for books — that’s it. 🙌"

@Jaded_Falcon

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"It is great for me to learn something from the book without reading it."

@OojasSalunke

"The themed book list podcasts help me connect ideas across authors—like a guided audio journey."

@Leo, Law Student, UPenn

483

"Makes me feel smarter every time before going to work"

@Cashflowbubu

"Instead of endless scrolling, I just hit play on BeFreed. It saves me so much time."

@Moemenn

"I never knew where to start with nonfiction—BeFreed’s book lists turned into podcasts gave me a clear path."

@Chloe, Solo founder, LA

117

"Perfect balance between learning and entertainment. Finished ‘Thinking, Fast and Slow’ on my commute this week."

@Raaaaaachelw

"Crazy how much I learned while walking the dog. BeFreed = small habits → big gains."

@Matt, YC alum

108

"Reading used to feel like a chore. Now it’s just part of my lifestyle."

@Erin, Investment Banking Associate , NYC

254

"Feels effortless compared to reading. I’ve finished 6 books this month already."

@djmikemoore

"BeFreed turned my guilty doomscrolling into something that feels productive and inspiring."

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"Reading used to feel like a chore. Now it’s just part of my lifestyle."

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254

"Feels effortless compared to reading. I’ve finished 6 books this month already."

@djmikemoore

"BeFreed turned my guilty doomscrolling into something that feels productive and inspiring."

@Pitiful

4.5K

"BeFreed turned my commute into learning time. 20-min podcasts are perfect for finishing books I never had time for."

@SofiaP

"BeFreed replaced my podcast queue. Imagine Spotify for books — that’s it. 🙌"

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