The fast-paced development of the artificial intelligence (AI) sector has posed considerable challenges for traditional data management technologies. Manual procedures, disjointed workflows, and data group errors have resulted in inconsistency and inefficiency. In a rapidly changing environment, where the concept of “modern” data stack is almost obsolete, managing distributed data has become labor-intensive requiring specialized…
Large language models, such as BERT, GPT-3, and T5, while powerful in identifying intricate patterns, pose privacy concerns due to the risk of exposing sensitive user information. A possible solution is machine unlearning, a method that allows for specific data elimination from trained models without the need for thorough retraining. Nevertheless, prevailing unlearning techniques designed…
