AI 101

These subjects often turn into buzzwords with little clear explanation. No worries, we will provide straightforward insights into these complex areas in plain English and help you learn how to implement it.

Global AI Affairs"Froth on the Daydream"AI 101The CV HistoryGenAI UnicornsThe History of LLMsCommunity TwistTwitter LibraryAI Infra UnicornsInterviews with InnovatorsAI AgentsFMOps
AI 101AI 101
Topic 31: How to Reduce Memory Use in Reasoning Models

Topic 31: How to Reduce Memory Use in Reasoning Models

we explore how combining LightThinker and Multi-Head Latent Attention cuts memory and boosts performance

Alyona Vert.
Alyona Vert.
AI 101AI 101
Topic 30: Everything You Need to Know about Knowledge Distillation

Topic 30: Everything You Need to Know about Knowledge Distillation

This is one of the hottest topics thanks to DeepSeek. Learn with us: the core idea, its types, scaling laws, real-world cases and useful resources to dive deeper

Alyona Vert.
Alyona Vert.
AI 101AI 101
Topic 29: Inside the family of Smol models

Topic 29: Inside the family of Smol models

We explore the power of datasets and their integration in Hugging Face's small language models family, particularly in SmolLM2.

Alyona Vert.
Alyona Vert.
AI 101AI 101
Topic 28: What is Mixture-of-Mamba?

Topic 28: What is Mixture-of-Mamba?

we discuss how to enable the Mamba Selective State Space Model (SSM) to handle multimodal data using the Mixture-of-Transformers concept and modality-aware sparsity

Alyona Vert.
Alyona Vert.
AI 101AI 101
Topic 27: What are Chain-of-Agents and Chain-of-RAG?

Topic 27: What are Chain-of-Agents and Chain-of-RAG?

We explore Google's and Microsoft's advancements that implement "chain" approaches for long context and multi-hop reasoning

Alyona Vert.
Alyona Vert.
AI 101AI 101
Topic 26: What is test-time compute and how to scale it?

Topic 26: What is test-time compute and how to scale it?

We dive into test-time compute and discuss five+ open-source methods for its effective scaling for deep step-by-step models' reasoning.

Alyona Vert.
Alyona Vert.
AI 101AI 101
Topic 25: The Keys to Prompt Optimization

Topic 25: The Keys to Prompt Optimization

Practical Insights for Large Language Models

Isabel González
Isabel González
AI 101AI 101
Topic 24: What is Cosmos World Foundation Model Platform?

Topic 24: What is Cosmos World Foundation Model Platform?

World models are the next big thing that enables Physical AI. Let's explore how NVIDIA makes it happen

Alyona Vert.
Alyona Vert.
AI 101AI 101
+1+1
Topic 23: What is LLM Inference, it's challenges and solutions for it

Topic 23: What is LLM Inference, it's challenges and solutions for it

Plus a Video Interview with the SwiftKV Authors on Reducing LLM Inference Costs by up to 75%

Ksenia Se
Ksenia Se
AI 101AI 101
Topic 22: What is HtmlRAG, Multimodal RAG and Agentic RAG?

Topic 22: What is HtmlRAG, Multimodal RAG and Agentic RAG?

We explore in details three RAG methods that address limitations of original RAG and meet the upcoming trends of the new year

Alyona Vert.
Alyona Vert.
AI 101AI 101
🎄 Recap: 21 Episodes of AI 101 Guide

🎄 Recap: 21 Episodes of AI 101 Guide

Take some time to learn or refresh the key concepts, techniques, and models that matter most

Ksenia Se
Ksenia Se
AI 101AI 101
Topic 21: What is Natural Language Reinforcement Learning (NLRL)?

Topic 21: What is Natural Language Reinforcement Learning (NLRL)?

Explore how RL can be blended with natural language

Alyona Vert.
Alyona Vert.