11 videos · 6 hr 19 minBefore It Worked
Most AI videos on HN are about what works now. This playlist goes back to the talks HN kept linking while neural nets were still a fringe bet: the debates, the demos and the pioneers explaining ideas almost nobody used yet. It runs in chronological order, from 1973 to 2017. The last two talks are critiques from people inside the field.
Play all on YouTube- 11:23:12
The Lighthill debate on Artificial Intelligence: "The general purpose robot is a mirage"
Pierre-Yves Oudeyer · Picked by 1 · 2019–2025The full 1973 BBC debate in which Lighthill argues against McCarthy and Michie, the argument that came before the first AI winter, with vintage footage of the Freddy robot.
- 218:27
Richard Feynman: Can Machines Think?
Lex Clips · Picked by 1 · 2022–2025In 1985 Feynman notes how hard it is to name anything a computer will never do, and HN still quotes that point in AGI arguments.
- 34:10
Karl Sims - Evolved Virtual Creatures, Evolution Simulation, 1994
MediaArtTube · Picked by 2 · 2014–2022Four minutes of evolved block creatures from 1994, which HN cites as the classic example of optimization exploiting simulator bugs.
- 452:52
Google Developers Day US - Theorizing from Data
GoogleDeveloperDay · Picked by 3 · 2007–2009Norvig's 2007 case that more data beats cleverer models, the statistical approach that came before deep learning took over.
- 5
48:10Bay Area Vision Meeting: Unsupervised Feature Learning and Deep Learning
Google TechTalks · Picked by 9 · 2011–2013Andrew Ng in 2011 showing networks learn their own features from unlabeled data, a talk nine HN commenters recommended over two years as the simple overview of the coming wave.
- 6
4:12PREDATOR - Tracker that learns and improves
Zdenek Kalal · Picked by 1 · 2011–2023A 2011 vision demo that learns as it tracks, which HN remembers as primitive but effective and a reminder that pre-deep-learning methods could already impress.
- 7
1:00:19Brains, Sex, and Machine Learning
Google TechTalks · Picked by 7 · 2012–2017Hinton in 2012 explains dropout through sexual reproduction and spiking neurons, which HN calls a simple, elegant account of the technique.
- 8
9:05Speech Recognition Breakthrough for the Spoken, Translated Word
Microsoft Research · Picked by 1 · 2013–2024Microsoft's 2012 live demo turning English speech into Chinese in the speaker's own voice, one of the first public signs that deep nets had arrived.
- 9
3:54Deep Visualization Toolbox
Jason Yosinski · Picked by 1 · 2016–2025A 2015 look inside a convnet watching a live camera, with individual units lighting up for faces and text.
- 10
1:11:36Geoffrey Hinton talk "What is wrong with convolutional neural nets ?"
trwappers · Picked by 2 · 2017–2018Once convnets had won, Hinton came back to argue that pooling is a mistake and to pitch capsules instead.
- 11
23:20Ali Rahimi's talk at NIPS(NIPS 2017 Test-of-time award presentation)
ObservantVids · Picked by 3 · 2018–2025The ending: the field's most-quoted critique of itself, which argues that machine learning had become alchemy just as it started to work.