AI in 2026: A Technical Recap of Memory, Inference, Fine-Tuning, and Modular Architectures
By
Alyona Vert.
Summary
This article provides a comprehensive technical recap of key AI concepts and techniques shaping modern systems in 2026. It covers DeepSeek mHC (multi-head caching), conditional memory architectures, post-RL fine-tuning strategies, on-policy self-distillation, inference chip design, and depth-addressable Transformers. The unifying theme is that AI is becoming more selective, modular, and infrastructure-aware — moving beyond brute-force scaling toward efficiency and specialization.
Source
Twitter / XAI in 2026: A Technical Recap of Memory, Inference, Fine-Tuning, and Modular Architecturesturingpost.comKey quotes
· 3 pulledAI is becoming more selective, modular, and infrastructure-aware.
This recap connects two layers of the same story.
The first layer is new research ideas: conditional memory, post-RL fine-tuning, on-policy distillation, inference chips, and deeper ways to reuse Transformer representations.
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