From papers to practice. LLM research breakthroughs analyzed for AI engineers

Chain-of-Thought Prompting: Not the Universal Solution We Thought

CoT - where AI models explain their reasoning step by step - has become the default approach for complex AI tasks. But new research reveals it might not be the silver bullet many thought it was.

Why Size Matters in LLMs?

How the Number of Parameters Influences LLM Performance

Rerank for Better RAG

Methods to enhance relevance and diversity in your retrievals

Do We Have Enough Data to Train LLMs?

Training optimal Large Language Models

A Language Model From 34 Years Ago

An overview of Statistical Language Models

Optimize your RAG pt.1 - Data ingestion

Advanced data ingestion techniques for RAG

The Future of Generative AI in 2024

Autonomous agents, AI music, new hardware, and more. Our predictions for 2024.

Not all LLMs are born to be chatbots

What is instruction fine-tuning

The End of RAG?

New architectures and models emerging

Is MoE the next frontier for LLMs? Mixtral 8x7b and Mixture of Experts

Exploring the MoE architecture

Understanding AI Text Made Me a Better Writer

Write better by analyzing ChatGPT’s bad writing

Obsidian-3B: The Smallest Multimodal LLM

Can a 3B model compete with the giants?