747: Technical Intro to Transformers and LLMs, with Kirill Eremenko

Attention and transformers in LLMs, the five stages of data processing, and a brand-new Large Language Models A-Z course: Kirill Eremenko joins host Jon Krohn to explore what goes into well-crafted LLMs, what makes Transformers so powerful, and how to succeed as a data scientist in this new age of generative AI. This episode is brought to you by Intel and HPE Ezmeral Software Solutions (https://hpe.com/ezmeral/chatwithyourdata), and by Prophets of AI (https://prophetsofai.com), the leading agency for AI experts. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: • Supply and demand in AI recruitment [08:30] • Kirill and Hadelin's new course on LLMs, “Large Language Models (LLMs), Transformers & GPT A-Z” [15:37] • The learning difficulty in understanding LLMs [19:46] • The basics of LLMs [22:00] • The five building blocks of transformer architecture [36:29] - 1: Input embedding [44:10] - 2: Positional encoding [50:46] - 3: Attention mechanism [54:04] - 4: Feedforward neural network [1:16:17] - 5: Linear transformation and softmax [1:19:16] • Inference vs training time [1:29:12] • Why transformers are so powerful [1:49:22] Additional materials: www.superdatascience.com/747