Concepts
The foundational ideas modern AI is built on – tokens, embeddings, attention, scaling, inference – explained from the ground up for engineers and researchers
Concepts
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10 min read
May 21, 2026
AI 101: From Tokens to Answers: What Actually Happens During LLM Inference
How LLM inference works end-to-end: tokenization, embeddings, prefill, decode, KV cache, batching, retrieval, and modern inference orchestration.
Concepts
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10 min read
May 13, 2026
AI 101: Your Ultimate Guide to Attention: Mechanism, QKV, and KV Cache
Learn how attention in AI works, from queries, keys, and values to KV cache, self-attention, and modern approaches
Concepts
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2 min read
May 10, 2026
Concepts: Types of Deep Learning
9 types of deep learning explained: CNNs, RNNs, transformers, GANs, diffusion models & more. Visual flashcards for ML practitioners. Turing Post AI 101.
Concepts
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11 min read
Apr 29, 2026
AI 101: What’s So Magical About Embeddings?
How tokens become learnable coordinates, and geometry shapes how context connects and meaning comes to life
Concepts
+4
13 min read
Apr 22, 2026
AI 101: How Token Taxonomy Affects Your Bill
From reasoning tokens to vision patches – your guide to the species that now shape AI cost, speed, and capability
Concepts
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12 min read
Apr 15, 2026
AI 101: What Is a Token (and why it runs AI)?
What is a token in AI? Learn how tokenization works, why context windows matter, and how tokens became the core unit of LLM performance and API pricing.
Concepts
+3
11 min read
Mar 4, 2026
AI 101: From Vibe Coding to Spec-Driven Development
Why vibe coding breaks at scale — and how spec-driven development (SDD) fixes it. Covers Kiro by AWS, GitHub Spec Kit, Tessl, and when to use each approach.
Concepts
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14 min read
Feb 25, 2026
AI 101: The Inference Chip Wars – MatX, Taalas, and the Cracks in the GPU Era
From NVIDIA Vera Rubin to model-as-hardware, and why “inference chips” are no longer one category
Concepts
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11 min read
Jan 29, 2026
What is Hybrid AI?
It’s not about architectural hybrids, it’s about where to run a model. The big promise in connecting devices and clouds for the nearest future of AI.
Concepts
+3
8 min read
Jan 14, 2026
What are Web World Models?
Princeton’s new recipe for building better world models to support AI agents
Concepts
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15 min read
Dec 10, 2025
AI 101: The State of Reinforcement Learning in 2025
State of RL in 2025: RLVR surprising findings, GRPO, RLHF vs RLAIF, policy optimization, agentic RL, robotics advances, and key trends for 2026.
Concepts
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13 min read
Nov 26, 2025
Continual Learning: How AI Learns Without Forgetting
Continual learning explained: catastrophic forgetting, key methods, Google Nested Learning, and Meta Sparse Memory Finetuning for lifelong AI training.
Concepts
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13 min read
Oct 29, 2025
Inside Robotics
Building the body of AI: How Physical AI is trained and powered – from Figure 03, Neo, Unitree robots to NVIDIA freshest updates
Concepts
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11 min read
Oct 22, 2025
What is Neurosymbolic AI?
Neurosymbolic AI combines neural networks with symbolic logic. Covers 6 integration types, AlphaGeometry, Logic Tensor Networks, and use cases.
Concepts
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15 min read
Oct 1, 2025
Reinforcement Learning: The Ultimate Guide to Past, Present, and Future
From the early trial-and-error concepts to today’s breakthroughs with RLHF, PPO, and GRPO, and where to go next, according to Andrej Karpathy and Richard Sutton.
Concepts
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12 min read
Sep 24, 2025
Rethinking Causal Attention
Causal attention in transformers explained — plus CASTLE lookahead keys and future-aware masks for better reasoning and vision tasks.
Concepts
+2
11 min read
Sep 17, 2025
What are Guardian Models?
Everything you need to know about models that defend AI today
Concepts
+4
10 min read
Aug 27, 2025
What is PAN? How to Build a Better World Model?
Explore how rethinking world model building patterns can turn our vision upside down and lead to a new Physical, Agentic, and Nested (PAN) system
Concepts
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11 min read
Jun 25, 2025
RLHF variations: DPO, RRHF, RLAIF
DPO, RRHF, and RLAIF explained: three RLHF alternatives that skip reward models, use ranking loss, or replace human annotators with AI feedback.
Concepts
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10 min read
Jun 11, 2025
The Human Touch: How HITL is Saving AI from Itself with Synthetic Data
we explore how human-in-the-loop systems are keeping synthetic data grounded, useful, and safe in the age of AI self-training
Concepts
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12 min read
Jun 4, 2025
Meta-Learning in AI: MAML, Prototypical Nets & Model-Based Approaches
Meta-learning teaches AI to learn how to learn. Covers MAML, Prototypical Networks, Meta-LoRA, ReMA, and meta-evaluation with real examples.
Concepts
+2
14 min read
May 7, 2025
What is Defense AI?
Let’s explore how AI is reshaping the battlefield – from drone swarms and cyber defense to logistics, training, and the race for cognitive security
Concepts
+3
10 min read
Apr 2, 2025
LLM Inference Explained: Latency, Throughput & How It Work
How to optimize LLM inference latency and throughput: quantization, batching, KV cache, speculative decoding, GPU vs TPU, and hardware accelerators.
