Alon Oring
Alon Oring is the Head of Research at Dynamic Infrastructure, a predictive maintenance startup focused on using computer vision to identify defects and risks in critical infrastructure before they evolve into large-scale failures. Since joining Dynamic Infrastructure in 2019, Alon has led the development of several core technologies that obtained state-of-the-art performance and are currently serving multiple customers worldwide. Additionally, Alon is an active lecturer on deep learning, machine learning, and data science at Reichman University (IDC Herzliya), international coding boot camps, and an active mentor for up-and-coming data scientists.
Sessions
This talk navigates from Recurrent Neural Networks to Generative Pretrained Transformers (GPTs), with a primary focus on understanding attention mechanisms. We start with the building blocks: The Perceptron and RNN cells, and after identifying the issues that arise with RNNs, we delve into attention mechanisms, examining their role in translation tasks and leading into a detailed dissection of self-attention. The culmination is a comprehensive review of Transformer models and the GPT series, their performances, and their capacities in zero-shot, one-shot, and few-shot learning with prompts.