about.subtitle
Understanding how modern intelligent systems are built is impossible without analyzing their «blueprints».In this collection, we gather materials dedicated to the internal logic of neural networks – from the fundamental basics of transformers to experimental topologies. We view architecture not merely as a technical parameter, but as the defining factor of a specific model's capabilities and limitations.
We explain how the Mixture of Experts architecture works – an approach that makes models smarter without making them 'think' harder.
AI: Events
Infrastructure
Why modern AI can't be truly smart without structured data, and how metadata, reference data, and knowledge graphs shape its 'brain'.
NeuroBlog
Artificial intelligence • Technologies
The longer the conversation with AI lasts, the more it loses the thread – like a conversational partner getting too tired to keep everything said earlier in their head.
AI: Events
Development
Allen AI has introduced Olmix, an open-source framework for data mixing in the language model training process, including pre-training, instruction tuning, and alignment.
AI: Events
Technical context • Development
Unsloth's new kernels and mathematical optimizations slash memory requirements by 35%, boost training speeds by 12x, and enable context windows six times longer than the original.
AI: Events
Technical context • Infrastructure
The Perplexity AI team has demonstrated how direct server-to-server data transfer technology helps language models run faster and more efficiently by eliminating bottlenecks in network infrastructure.
Want to know about new
experiments first?
Subscribe to our Telegram channel — we share all the latest
and exciting updates from NeuraBooks.