Alyona Vert.

Alyona Vert.

Joined Turing Post in April 2024. Studied control systems of aircrafts at BMSTU (Moscow, Russia), where conducted several researchers on helicopter models. Now is more into AI and writing.

AI 101AI 101
AI 101: The State of Reinforcement Learning in 2025

AI 101: The State of Reinforcement Learning in 2025

What we have – and what we can carry from 2025 into 2026 – in reinforcement learning

Ksenia Se
Alyona Vert.
Ksenia Se, +1
AI 101AI 101
AI 101: Fusing Modalities: Basics + the New MoS Approach

AI 101: Fusing Modalities: Basics + the New MoS Approach

We discuss how models fuse different data types, why it is important now, and what is special in the new Meta and KAUST's fusion method – Mixture of States

Alyona Vert.
Alyona Vert.
AI 101AI 101
AI 101: What is Continual Learning?

AI 101: What is Continual Learning?

Can models add new knowledge without wiping out what they already know? We look at why continual learning is becoming important right now and explore the new methods emerging for it, including Google’s Nested Learning and Meta’s Sparse Memory Fine-tuning

Alyona Vert.
Alyona Vert.
AI 101AI 101
AI 101: What is LeJEPA? The Theory Upgrade JEPA Has Been Missing

AI 101: What is LeJEPA? The Theory Upgrade JEPA Has Been Missing

We discuss how Yann LeCun and Randall Balestriero's latest research drives JEPA foundations and puts it into solid, meaningful practice – and what it means for the community. Time to work on world models!

Alyona Vert.
Ksenia Se
Alyona Vert., +1
AI 101AI 101
AI 101: What is so special about Kimi K2 Thinking?

AI 101: What is so special about Kimi K2 Thinking?

Tracing the rise of China’s agentic intelligence strategy – from Kimi’s early vision to today’s open-source breakthrough

Alyona Vert.
Ksenia Se
Alyona Vert., +1
AI 101AI 101
AI 101: What matters for RL? Precision! Switching BF16 → FP16

AI 101: What matters for RL? Precision! Switching BF16 → FP16

How this switch in precision influences the reinforcement learning accuracy and stability and why everyone, including Andrej Karpathy and Nathan Lambert, paid attention to this method

Ksenia Se
Alyona Vert.
Ksenia Se, +1
AI 101AI 101
AI 101: Inside Robotics

AI 101: Inside Robotics

Building the body of AI: How Physical AI is trained and powered – from Figure 03, Neo, Unitree robots to NVIDIA freshest updates

Alyona Vert.
Alyona Vert.
AI 101AI 101
AI 101: What is Neuro-Symbolic AI?

AI 101: What is Neuro-Symbolic AI?

Everything you need to know about hybrid neuro-symbolic AI, how it blends strict logic and rules with neural networks, and why it shouldn't be overlooked

Alyona Vert.
Alyona Vert.
AI 101AI 101
AI 101: What are Modular Manifolds?

AI 101: What are Modular Manifolds?

How Thinking Machines Lab is redefining neural network optimization through geometry-awareness

Alyona Vert.
Alyona Vert.
AI 101AI 101
AI 101: What's New in World Models?

AI 101: What's New in World Models?

A glimpse at Code World Model, PSI, and others – redefining how models catch the world in their nets

Alyona Vert.
Alyona Vert.