From test-time compute to mixture-of-experts: the latest breakthroughs in AI
"Attention Is All You Need" paper revolutionizes NLP
Pre-training + fine-tuning becomes dominant paradigm
GPT-3, GPT-4, Claude, LLaMA: bigger models, better performance
Test-time compute, MoE, reasoning models, efficiency breakthroughs
The AI landscape has shifted dramatically in 2024-2025. This chapter covers the latest architectural innovations that define modern LLMs:
The 2024-2025 breakthrough: models that "think longer" perform better
Key Insight: Sometimes it's better to let a smaller model "think longer" than to make the model bigger
Activate only the "experts" you need for each token
All parameters active for every token
Only relevant experts activated per token
From processing paragraphs to processing entire codebases
Beyond text: vision, audio, and unified understanding
Teaching models to reason step-by-step and check their work
How modern LLMs learn: the algorithms that made billion-parameter models trainable
Simple but slow to converge
Fast, stable, industry standard
Running powerful models faster and cheaper in production
We've learned that how you use compute matters as much as how much compute you have. A smaller model that "thinks longer" can outperform a larger model that answers immediately. This realization has fundamentally changed how we build and deploy LLMs.
Understanding what's happening inside the billions of parameters. Anthropic's goal: detect most AI problems by 2027.
Medical LLMs, legal LLMs, coding-specific models. Fine-tuned architectures for specific domains.
Running powerful models on phones and laptops. Quantization and distillation enabling local AI.
LLMs that use tools, browse the web, write and execute code. Multi-agent collaboration.
This chapter will provide a comprehensive tour of 2025's most important LLM innovations. We'll explain not just what these techniques are, but why they matter and how they work—building on everything you've learned in previous chapters.
From the mathematical foundations of MoE routing to the engineering breakthroughs enabling 10M token contexts, you'll gain a deep understanding of modern AI systems.