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🦸🏻#14: What Is MCP, and Why Is Everyone – Suddenly!– Talking About It?

🦸🏻#14: What Is MCP, and Why Is Everyone – Suddenly!– Talking About It?

everything you need to know about Model Context Protocol

Ksenia Se
Ksenia Se
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.
"Froth on the Daydream""Froth on the Daydream"
🌁#91: AI Literacy – How Much Do We Know About AI?

🌁#91: AI Literacy – How Much Do We Know About AI?

As AI models graduate to more sophisticated reasoning, humans – especially policymakers – remain stuck in the basics

Ksenia Se
Ksenia Se
AI AgentsAI Agents
🦸🏻#13: Action! How AI Agents Execute Tasks with UI and API Tools

🦸🏻#13: Action! How AI Agents Execute Tasks with UI and API Tools

we explore UI-driven versus API-driven interactions, demystify function calling in LLMs, and compare leading open-source frameworks powering autonomous AI actions

Ksenia Se
Ksenia Se
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.
"Froth on the Daydream""Froth on the Daydream"
🌁#90: Why AI’s Reasoning Tests Keep Failing Us

🌁#90: Why AI’s Reasoning Tests Keep Failing Us

we discuss benchmark problems, such as benchmark saturation, and explore potential solutions. And as always, we offer a curated list of relevant news and important papers to keep you informed

Ksenia Se
Ksenia Se
AI AgentsAI Agents
🦸🏻#12: How Do Agents Learn from Their Own Mistakes? The Role of Reflection in AI

🦸🏻#12: How Do Agents Learn from Their Own Mistakes? The Role of Reflection in AI

we explore how reflection enables AI to self-correct without always needing external feedback, making systems more reliable and autonomous

Ksenia Se
Ksenia Se
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.
"Froth on the Daydream""Froth on the Daydream"
🌁#89: AI in Action: How AI Engineers, Self-Optimizing Models, and Humanoid Robots Are Reshaping 2025

🌁#89: AI in Action: How AI Engineers, Self-Optimizing Models, and Humanoid Robots Are Reshaping 2025

we look into the accelerating trends in AI – soaring demand for engineers, self-optimizing models, and humanoid robots stepping into reality

Ksenia Se
Ksenia Se
AI AgentsAI Agents
🦸🏻#11: How Do Agents Plan and Reason?

🦸🏻#11: How Do Agents Plan and Reason?

we explore recent breakthroughs in reasoning (DeepSeek!) as well as main planning techniques that enable precision and adaptability

Ksenia Se
Ksenia Se
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.
"Froth on the Daydream""Froth on the Daydream"
🌁#88: Can DeepSeek Inspire Global Collaboration?

🌁#88: Can DeepSeek Inspire Global Collaboration?

we highlight the overlooked impact of DeepSeek’s surprise release on countries like Korea, Japan, and those in Europe and what it might mean for the global open-source community

Ksenia Se
Ben Eum
Ksenia Se, +1
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