#71: Alex O'Connor — Transformers, Generative AI, and the Deep Learning Revolution

Alex O’Connor—researcher and ML manager—on the latest trends of generative AI. Language and image models, prompt engineering, the latent space, fine-tuning, tokenization, textual inversion, adversarial attacks, and more.

Alex O’Connor got his PhD in Computer Science from Trinity College, Dublin. He was a postdoctoral researcher and funded investigator for the ADAPT Centre for digital content, at both TCD and later DCU. In 2017, he joined Pivotus, a Fintech startup, as Director of Research. Alex has been Sr Manager for Data Science & Machine Learning at Autodesk for the past few years, leading a team that delivers machine learning for e-commerce, including personalization and natural language processing.

Favorite quotes

• “None of these models can read.”
• “Art in the future may not be good, but it will be prompt.” Mastodon

Books

• Machine Learning Systems Design by Chip Huyen
• Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron

Papers

• The Illustrated Transformer by Jay Alammar
• Attention Is All You Need by Google Brain
• Transformers: a Primer by Justin Seonyong Lee

Links

• Alex in Mastodon ★
• Training Dream Booth Multimodal Art on HuggingFace by @akhaliq
• NeurIPS
• arxiv.org: Where most papers get published
• Nono’s Discord
• Suggestive Drawing: Nono’s master’s thesis
• Crungus is a fictional character from Stable Diffusion’s latent space

Machine learning models

• Stable Diffusion
• Arcane Style Stable Diffusion fine-tuned model ★
• Imagen
• DALL-E
• CLIP
• GPT and ChatGPT
• BERT, ALBERT & RoBERTa
• Bloom
• word2vec
• Mupert.ai and Google’s MusicLM
• t-SNE and UMAP: Dimensionality reduction techniques
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