- “The Revolt of the Salaried Bourgeoisie”, Slavoj Žižek – an important update to Marxist analysis for the 21st century economy, especially for tech workers
- “Philosophy: Who Needs It?”, Ayn Rand – a rhetorically effective and accessible explanation for why philosophy is more important than ever, which I recommend to anyone who is skeptical of or new to philosophy
- “Rawls’ Law of Peoples: Rules for a Vanished Westphalian World”, Allen Buchanan – an interesting philosophical historicization of Rawls which strikes at a deep gash in political philosophy itself.
- “Rawls, Hegel, and Communitarianism”, Sibyl A. Schwarzenbach – an interesting attempt at the very difficult project of writing coherently on Rawls and Hegel in the same paragraph.
- “The Ethical Significance of Nationality”, David Miller – what I would call (no doubt with controversy) a proto-phenomenological approach to political philosophy: a return to the Delphic motto, “know thyself!”
- The Poverty of Ethics, Anat Amar – a brilliant synthesis of analytic ethics and Continental discontent.
- Queer Phenomenology, Sara Ahmed – a phenomenological account of queer bodies and spaces which leads us towards a socially-aware phenomenology of phenomenology
- Sex and the Failed Absolute, Slavoj Zizek – an ingenious and culturally aware synthesis of psycholanalysis and Hegel, through a triadic topological analogy
- Oppenheimer – the most powerful film I have experienced. More horrific than any horror movie I have watched. Exploration of the utter contradiction of man and God, of violence and peace, of necessity and freedom – of the atomic bomb and Oppenheimer.
- Summer of ‘85 – a more sensitive and textually self-aware Call Me By Your Name
- Brokeback Mountain – a classic masterpiece of environmental cinematography and queer film
- La La Land – beautiful cinematography and play with destiny and time
- Parasite – biting social critique of globalized capitalism
- 2001: A Space Odyssey – an unhurried and thoughtful meditation on technology and Nietzschian transcendence
- The Menu – an entertaining watch and commentary on bourgeois consumption and production
- Midsommar – a beautiful film, and a deeply disturbing exploration of the “anthropologist’s gaze”
- Succession – an edgy portrayal of family, politics, and corporate power
- The White Lotus – brilliantly nuanced portrays of colonial, racial, and sexual tensions in bourgeois society
- Hearts and Minds – a brutally material portrayal of horror and patriotism in the Vietnam War, terrifying in its nakedness
- The Pervert’s Guide to Ideology – a fun watch, an accessible overview of Slavoj Zizek’s psychoanalytic-Hegelian treatment of cinema
- AlphaGo – a close look at humanity from the nonhuman: indeed, the only perspective from which humanity can truly be gazed at.
- Crime and Punishment, Fyodor Dostevsky – a meditation on sin, guilt, and redemption
- Infinite Jest, David Foster Wallace – we are addicted to entertainment, and entertained by addiction
- Never Let Me Go, Kazuo Ishiguro – the beauty of our fragile life becomes palpable when it’s about to be broken
- Lolita, Vladimir Nabokov
A collection of hand-picked interesting AI papers.
Deep Learning Theory
- “Beyond Neural Scaling Laws: Beating Power Law Scaling via Data Pruning” by Ben Sorscher et al.
- “Learning in High Dimension Always Amounts to Extrapolation” by Randall Balestriero et al.
- “The Lottery Ticket Hypothesis” by Jonathan Frankle and Michael Carbin
- “Deep Double Descent” by Preetum Nakkiran et al.
- “Adversarial Examples Are Not Bugs, They Are Features” by Andrew Ilyas et al.
- “Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets” by Alethea Power et al.
- “What’s Hidden in a Randomly Weighted Neural Network?” by Vivek Ramanjuan and Michell Wortsman
- “Learning to learn by gradient descent by gradient descent” by Marcin Andrychowicz et al.
- “On Exact Computation with an Infinitely Wide Neural Net” by Sanjeev Arora
- “Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning” by Yarin Gal and Zoubin Ghahramani
Bias and Fairness
- “Characterising Bias in Compressed Models” by Sara Hooker et al.
- “Moving Beyond ‘Algorithmic Bias is a Data Problem’” by Sara Hooker
- “DeepInsight: A methodology to transform a non-image data to an image for convolution neural network architecture”
- “Explaining and Harnessing Adversarial Examples by Ian J. Goodfellow et al.
- “Robust Physical-World Attacks on Deep Learning Visual Classification” by Kevin Eykholt & Ivan Evtimov et al.
- “EfficientNet: Rethinking Model Scaling for Convoltuional Neural Networks” by Mingxing Tan et al.
- “Natural Language Descriptions of Deep Visual Features” by Evan Hernandez et al.
- “Feature Visualization” by Chris Olah et al.
- “ResMLP: Feedforward networks for image classification with data-efficient training”
- “Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold”
- “Why Can GPT Learn In-Context? Language Models Secretly Perform Gradient Descent as Meta-Optimizers” by Damai Dai et al.
- “Single Headed Attention RNN: Stop Thinking With Your Head” by Stephen Merity
- “GPT-D: Inducing Dementia-related Linguistic Anomalies by Deliberate Degradation of Artificial Neural Language Models” by Changye Li et al.
- “Predictability and Surprise in AI Models” by Deep Ganguli et al.
- “A Mathematical Framework for Transformer Circuits” by Nelson Elhage
- “Language Models as Knowledge Bases?” by Fabio Petroni
- “An Attention Free Transformer” by Shuangfei ZHai et al.
- “Transformers are Graph Neural Networks” by Chaitanya Joshi
- “Generating Words from Embeddings” from Rajat’s Blog
- “Compositional Observer Communication Learning from Raw Visual Input” by Edward Choi, Angeliki Lazaridou, Nando de Freitas
- “Emergence of Grounded Compositional Language in Multi-Agent Populations” by Igor Mordatch and Pieter Abbeel
- “On the Spontaneous Emergence of Discrete and Compositional Signals” by Nur Geffen Lan, Emmanuel Chemla, and Shane Steinert-Threlkel
- “Learning Emergent Discrete Message Communication for Cooperative Reinforcement Learning” by Sheng Li, Yutai Zhou, Ross Allen, Mykel J. Kochenderfer
- “AI Programmer: Autonomously Creating Software Programs Using Genetic Algorithms” by Kory Becker and Justin Gottschlich
- “On the Measure of Intelligence” by Francois Chollet
- “Computing Machinery and Intelligence” by Alan Turing
- “The Bitter Lesson” by Rich Sutton