Artificial Intelligence

If you spend any time working with real-world data, you quickly realize that not everything comes in neat, clean numbers.

This article is divided into three parts; they are: • Training a Tokenizer with Special Tokens • Preparing the Training Data • Running the Pretraining The model architecture you will use is the same as the one created in the

Tony Stoyanov is CTO and co-founder of EliseAI In the 2010s, tech companies chased staff-level specialists: Backend engineers, data scientists, system architects. That model worked when technology evolved slowly. Specialists knew their craft, could deliver quickly and built careers on…

This article is divided into two parts; they are: • Simple RoPE • RoPE for Long Context Length Compared to the sinusoidal position embeddings in the original Transformer paper, RoPE mutates the input tensor using a rotation matrix: $$ begin{aligned}…

Large language models (LLMs) like Mistral 7B and Llama 3 8B have shaken the AI field, but their broad nature limits their application to specialized areas.

In August 2025, Wang Lei decided it was finally time to say goodbye to his electric vehicle. Wang, who is 39, had bought the car in 2016, when EVs still felt experimental in Beijing. It was a compact Chinese brand.…

Agentic coding only feels “smart” when it ships correct diffs, passes tests, and leaves a paper trail you can trust.

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Building AI applications often requires searching through millions of documents, finding similar items in massive catalogs, or retrieving relevant context for your LLM.

Patronus AI, the artificial intelligence evaluation startup backed by $20 million from investors including Lightspeed Venture Partners and Datadog, unveiled a new training architecture Tuesday that it says represents a fundamental shift in how AI agents learn to perform complex…