Reading List

Skip to a section: AI, Philosophy, Film, Fiction

Philosophy

Articles

• “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!”

Books

• 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

Film

Movies

• 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”

TV Shows

• 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

Documentary

• 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.

Fiction

• 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

AI

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

Computer Vision

• “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”

Language Modeling

• “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

Emergent Language

• “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

Meta

• “On the Measure of Intelligence” by Francois Chollet
• “Computing Machinery and Intelligence” by Alan Turing
• “The Bitter Lesson” by Rich Sutton