Datasets
3 Questions: How to help students recognize potential bias in their AI datasets
Every year, thousands of students take courses that teach them how to deploy artificial intelligence models that can help doctors diagnose disease and determine appropriate treatments. However, many of these courses omit a key element: training students to detect flaws in the training data used to develop the models. Leo Anthony Celi, a senior research…
A Step-by-Step Coding Guide to Efficiently Fine-Tune Qwen3-14B Using Unsloth AI on Google Colab with Mixed Datasets and LoRA Optimization
Fine-tuning LLMs often requires extensive resources, time, and memory, challenges that can hinder rapid experimentation and deployment. Unsloth AI revolutionizes this process by enabling fast, efficient fine-tuning state-of-the-art models like Qwen3-14B with minimal GPU memory, leveraging advanced techniques such as 4-bit quantization and LoRA (Low-Rank Adaptation). In this tutorial, we walk through a practical implementation…
Nearly 80% of Training Datasets May Be a Legal Hazard for Enterprise AI
A recent paper from LG AI Research suggests that supposedly ‘open’ datasets used for training AI models may be offering a false sense of security – finding that nearly four out of five AI datasets labeled as ‘commercially usable’ actually contain hidden legal risks. Such risks range from the inclusion of undisclosed copyrighted material to…