An easy-to-understand explanation of how the 'Attention' mechanism, the heart of modern AI technology, connects to the essence of human intelligence and what the true core of intelligence really is.
Fine-tuning is a powerful way to sharpen AI with custom data, but here are three things you must know before diving in.
We explore the 'Efficient Frontier,' which balances the intelligence of AI models with computing resources.
We explain simply why local AI models running directly on your computer feel less capable than cloud services and how to fix it.
An easy-to-understand look at the search error issues that occur when using metadata filters in AI search systems, and the ACORN algorithm that solves them.
Using the analogy of 'baking bread' to explain how Large Language Models (LLMs) are created and served.
We explain in simple terms why Large Language Models (LLMs) lag behind traditional methods in analyzing tabular data, along with their limitations.
We dig into the identity of different AI technologies named 'Tidal,' ranging from music streaming to underwater robotics and corporate compliance.