Author Archives: Martin Irvine

About Martin Irvine

Martin Irvine is a professor at Georgetown University and the Founding Director of Georgetown's graduate program in Communication, Culture & Technology. He is interested in a wide range of interdisciplinary topics, including media theory, semiotics, cognitive science approaches to language and symbolic culture, computation and the Internet/Web, philosophy and intellectual history, art theory, contemporary music, vintage guitars, and all things post-postmodern.

Online Learning Sources for AI/ML

Video Lessons and Good Background Sources for Learning AI/ML Technologies

Video Lessons

Code Emporium: Center for AI and CS Dojo

- Main Channel Page: https://www.youtube.com/channel/UC5_6ZD6s8klmMu9TXEB_1IA
- How does the YouTube Recommender System Work?: https://www.youtube.com/watch?v=wDxTWp3KMMs
- How Does Google Translate’s AI Work?: https://www.youtube.com/watch?v=sIoHFPGOY0I
- How to Keep up with AI Research – Best Resources Explained!: https://www.youtube.com/watch?v=HciM9HdI1Hs

Welch Labs (Truly Excellent video tutorials on science, math, and AI)

- Main Channel Page: https://www.youtube.com/c/WelchLabsVideo/videos
- Neural Networks Demystified (series)
  - https://www.youtube.com/playlist?list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU
- Learning to See (Computer Vision for ML)
  - https://www.youtube.com/playlist?list=PLiaHhY2iBX9ihLasvE8BKnS2Xg8AhY6iV
- “How To Science” Series
  - (1) Music (follow others): https://www.youtube.com/playlist?list=PLiaHhY2iBX9ihLasvE8BKnS2Xg8AhY6iV

Two Minute Papers Site (The Major Papers on AI/ML for Neural Nets Explained!)

- Main Channel Page: https://www.youtube.com/channel/UCbfYPyITQ-7l4upoX8nvctg
  - How To Get Started With Machine Learning?: https://www.youtube.com/watch?v=4h0uC9FPVMQ
  - AI and Deep Learning Playlist: https://www.youtube.com/playlist?list=PLujxSBD-JXglGL3ERdDOhthD3jTlfudC2
  - OpenAI DALLE: https://www.youtube.com/watch?v=C7D5EzkhT6A
  - Everybody Can Make Deepfakes Now!: https://www.youtube.com/watch?v=mUfJOQKdtAk
  - OpenAI GPT 3: Good at Almost Anything: https://www.youtube.com/watch?v=_x9AwxfjxvE
  - OpenAI CLIP: Connecting Text and Images: https://www.youtube.com/watch?v=T9XSU0pKX2E

OpenAI: A Leading Company in Neural Net ML

Home Page: https://openai.com/ | Blog (Tech Development Announcements)

Technologies:

- Language Processing Model: GPT-2 (2019) [General Processor Transformer for NLP text]
- Image GPT: https://openai.com/blog/image-gpt/
- OpenAI – GPT 3 API: https://openai.com/blog/openai-api/
- DALL-E: Images from Text: https://openai.com/blog/dall-e/
- CLIP: Connecting Text and Images: https://openai.com/blog/clip/
- OpenAI CLIP: ConnectingText and Images (Paper Explained): https://www.youtube.com/watch?v=T9XSU0pKX2E

About OpenAI’s GPT-3

- https://en.wikipedia.org/wiki/GPT-3
- Computerphile: https://www.youtube.com/watch?v=_8yVOC4ciXc
- Will Douglas Heaven, “OpenAI’s New Language Generator GPT-3 Is Shockingly Good—and Completely Mindless,” MIT Technology Review, July 20, 2020, https://www.technologyreview.com/2020/07/20/1005454/openai-machine-learning-language-generator-gpt-3-nlp/;
- Will Douglas Heaven, “Why GPT-3 Is the Best and Worst of AI Right Now,” MIT Technology Review, February 24, 2021, https://www.technologyreview.com/2021/02/24/1017797/gpt3-best-worst-ai-openai-natural-language/;
- Gary Marcus and Ernest Davis, “GPT-3, Bloviator: OpenAI’s Language Generator Has No Idea What It’s Talking about,” MIT Technology Review, August 22, 2020, https://www.technologyreview.com/2020/08/22/1007539/gpt3-openai-language-generator-artificial-intelligence-ai-opinion/;
- Tiernan Ray, “What Is GPT-3? Everything Your Business Needs to Know about OpenAI’s Breakthrough AI Language Program,” ZDNet (blog), August 25, 2020, https://www.zdnet.com/article/what-is-gpt-3-everything-business-needs-to-know-about-openais-breakthrough-ai-language-program/;
- Two Minute Papers, OpenAI GPT-3 – Good At Almost Everything!, 2020, https://www.youtube.com/watch?v=_x9AwxfjxvE.

Stanford Courses

CS231n: Convolutional Neural Networks for Visual Recognition

http://cs231n.stanford.edu/

Detailed syllabus: http://cs231n.stanford.edu/syllabus.html

Andrew Ng’s Machine Learning Course on Coursera

https://www.coursera.org/learn/machine-learning