English
Russian
French
Spanish
German
Japanese
korean
PortugueseNews
The Layers of AI: From Classical Logic to Autonomous Agents
Most people using AI daily have no idea how it works under the hood. Here's the complete layered breakdown — from 1950s logic syst...
You Should Stop Fine-Tuning Blindly: What to Do Instead
Fine-tuning is not one thing. You’re choosing a point on a spectrum: Full FT → PEFT (Adapters/Prompt Tuning/LoRA) → QLoRA → Prefer...
The Simplest Way to Understand How LLMs Actually Work!
Transformers use a clever trick: for every word (technically tokens), the model creates three different representations: Q, K, V....
Teaching AI to See and Speak: Inside the OW‑VISCap Approach
This article outlines the OW‑VISCap framework, which jointly detects, segments, and captions both seen and unseen objects within a...
See, Track, Describe: How OW‑VISCap Lets AI Tell the Story Behind Every Frame
This article introduces OW‑VISCap, a unified framework for open‑world video instance segmentation and object‑centric captioning.
Technical Setup for RECKONING: Inner Loop Gradient Steps, Learning Rates, and Ha...
This article outlines the implementation details for RECKONING, which uses a GPT-2-base model and runs on NVIDIA A100 GPUs.
Bid Shading Fundamentals - Machine Learning Approaches and Advanced Optimizatio...
Machine learning approaches to bid shading represent the evolutionary leap from rule-based algorithms to adaptive, data-driven opt...
