References & Resources
A set of links with more information about the things that I talk about in the lecture I did on 2/12/2025.
Technical Deep Dives
- [1] BERT Embeddings Explained
- [2] arXiv:1504.01255 - Deep Learning Research
- [3] arXiv:1706.03762 - Attention Is All You Need (Transformers)
- [4] arXiv:2410.23884 - Recent AI Research
- [5] YouTube: AI Technical Overview
- [6] Nature: Deep learning (LeCun, Bengio & Hinton)
- [7] YouTube: The Lighthill Debate (1973)
- [8] YouTube: Jeff Dean on Important AI Trends
- [9] Hugging Face: Continuous batching from first principles
AI Perspecives
- [10] AI as Normal Technology
- [11] AI as Cultural and Social Technology
- [12] The danger of Stochastic Parrots
Industry Analysis & Commentary
- [13] AI 2027 - Future Predictions
- [14] WSJ: MIT AI Research
- [15] Navigating AI Chemistry Hype
- [16] Business Insider: AI Frontier Winners and Losers
OpenAI Resources
Critical Perspectives
My blogs that I used in the talk
- [21] Synthetic Data for Language Models
- [22] AI Reality Checks
- [23] Depend on Them
- [24] Utility and Bust Scale in Future AI Provision
- [25] Vector Databases, Large Language Models and Case-Based Reasoning