Simons Institute for the Theory of Computing

Simons Institute for the Theory of Computing

Views:
6,304,334
Subscribers:
68,600
Videos:
5,454
Duration:
173:07:02:50
United States
United States

Simons Institute for the Theory of Computing is an American YouTube content creator with at least 68.6 thousand subscribers. He published around 5.45 thousand videos which altogether total roughly 6.3 million views.

Created on ● Channel Link: https://www.youtube.com/channel/UCW1C2xOfXsIzPgjXyuhkw9g





All Videos by Simons Institute for the Theory of Computing



PublishedVideo TitleDurationViewsCategoryGame
2025-06-26Expedition to Obfustopia: Indistinguishability Obfuscation from Well-Studied Assumptions to New...0:00189
2025-06-25To interact or not to interact: Cryptographic proof systems and the Fiat-Shamir heuristic0:00210
2025-06-18Succinct arguments for QMA from standard assumptions, without quantum PCPs0:00174
2025-05-30Crypto + Meta-complexity 20:00167
2025-05-30Crypto + Meta-complexity 10:00152
2025-05-30Crypto + ML 20:00432
2025-05-30Crypto + ML 10:00535
2025-05-30Private Information Retrieval and Oblivious RAM0:00148
2025-05-30Secure Computation 30:0064
2025-05-30Secure Computation 20:0070
2025-05-30Secure Computation 10:00113
2025-05-30Proofs - Practice 20:0098
2025-05-30Proofs - Practice 10:00101
2025-05-30Proofs - Theory0:00150
2025-05-30Quantum 40:0099
2025-05-30Quantum 30:0089
2025-05-30Quantum 20:00151
2025-05-30Foundations 20:00197
2025-05-19Foundations 10:00387
2025-05-01Future Directions In AI Safety Research0:00400
2025-04-28Introduction (Sanjit Seshia)0:00371
2025-04-23How to Locate Unentanglement | Quantum Colloquium0:00586
2025-04-16Talk by Sophie Morel (ENS de Lyon)0:00102
2025-04-16Challenges in State-of-the-Art Bit-Precise Reasoning0:0060
2025-04-16Talk by Yannick Forster (INRIA)0:0070
2025-04-16Testing Artificial Mathematical Intelligence0:00131
2025-04-16Adventures with an Automatic Prover0:0065
2025-04-16Formal Reasoning Meets LLMs: Toward AI for Mathematics and Verification0:00187
2025-04-16How can Machine Learning Help Mathematicians?0:00117
2025-04-16Computer-Assisted Intuition: SAT Solvers in Mathematical Discovery0:00129
2025-04-07The Move Toward AGI: Why Large Language Models Surprised Almost Everyone... | Theoretically Speaking0:002,930
2025-04-07Transformers can learn compositional function0:00736
2025-04-07Advancing Diffusion Models for Text Generation0:001,168
2025-04-07Inference Scaling: A New Frontier for AI Capability0:001,827
2025-04-07Predicting and optimizing the behavior of large ML models0:00538
2025-04-07Mixed-modal Language Modeling: Chameleon, Transfusion, and Mixture of Transformers0:00384
2025-04-07Reducing the Dimension of Language: A Spectral Perspective on Transformers0:00330
2025-04-07LLM skills and meta-cognition: scaffolding for new forms of learning?0:00314
2025-04-07The Key Ingredients of Optimizing Test-Time Compute and What's Still Missing0:00500
2025-04-07Controllable and Creative Natural Language Generation0:00101
2025-04-04Field-based decoders revisited (partial)0:00199
2025-03-24Topological quantum spin glass order and its realization in qLDPC codes (partial)0:00430
2025-03-19How to Construct Random Unitaries | Quantum Colloquium0:00923
2025-02-28Neuroscience and AI: a symbiosis0:001,219
2025-02-18Panel Discussion0:00935
2025-02-18Rules vs. Neurons and what may be next0:001,044
2025-02-18How DeepSeek changes the LLM story0:004,742
2025-02-18How Linguistics Learned to Stop Worrying and Love the Language Models0:00412
2025-02-18Why it Matters That Babies and Language Models are the Only Known Language Learners0:00414
2025-02-18Neural algorithms of human language0:00459
2025-02-18Do LLMs Use Language?0:00275
2025-02-18More accurate behavioral predictions with hybrid Bayesian-Transformer models0:00219
2025-02-18Knowledge is structured and domain-specific: lessons from developmental cognitive science0:00185
2025-02-18Virtual Lab of AI Scientists0:00298
2025-02-18You Know It Or You Don’t: Compositionality and Phase Transitions in LMs0:00201
2025-02-18Interpreting LLMs to Interpret the Brain0:00213
2025-02-18Language and thought in brains: Implications for AI0:00115
2025-02-18Dissociating language and thought in large language models0:00113
2025-02-18The Cognitive Boundaries of Language Models: Hallucinations and Understanding0:00122
2025-02-18How Do Transformers Learn Variable Binding?0:00207
2025-02-07Automating scientific discovery and hypothesis generation with language model agents0:00176
2025-01-27Resilience in Action0:00344
2025-01-25Boaz Barak | Polylogues0:001,156
2024-12-24Debate: Sparks versus embers0:008,724
2024-12-24Off-the-shelf Algorithmic Stability0:001,010
2024-12-24Learning Theory of Transformers: Generalization and Optimization of In-Context Learning0:002,729
2024-12-24First-Person Fairness in Chatbots0:00258
2024-12-24Panel on the future of scientific research and education0:00760
2024-12-24Generalization in the representations and computations of frontier language models.0:001,087
2024-12-24Temporal Context in Brains and AI0:00604
2024-12-24Frame-shifting and Conceptual Blending: What do large language models have to say?0:00206
2024-12-24How machine learning is influencing protein engineering0:00305
2024-12-24Strong generalization from small brains and no training data0:00783
2024-12-24How neural networks learns simple functions?0:00660
2024-12-24The Curious Incident of Developing Artificial General Intelligence0:00637
2024-12-24Fireside Chat0:00220
2024-12-24On Memorization of Large Language Models in Logical Reasoning0:00256
2024-12-24Convex Analysis at Infinity: An Introduction to Astral Space and Fireside Chat0:00151
2024-12-17Talk by Ali Kavis (UT Austin)0:00214
2024-12-17Testing Noise Assumptions of Learning Algorithms0:00159
2024-12-06Generalization via analogy in young children and Large Models.0:0061
2024-12-06Generalization insights from actual cognition0:0065
2024-12-05A New Paradigm for Learning with Distribution Shift0:0055
2024-12-05Understanding the abilities of AI systems: Memorization, generalization, and points in between0:0050
2024-12-05Weak-to-Strong Generalization0:0091
2024-12-05Fireside Chat0:0093
2024-11-20Robust Mixture Learning when Outliers Overwhelm Small Groups0:0082
2024-11-20Learning General Gaussian Mixtures With Efficient Score Matching0:0092
2024-11-20Talk by Mahdi Soltanolkotabi (University of Southern California)0:0097
2024-11-19Beyond Decoding: Meta-Generation Algorithms for Large Language Models (Remote Talk)0:00280
2024-11-19Revisiting Scalarization in Multi-Task Learning0:00142
2024-11-19Omnipredicting Single-Index Models with Multi-Index Models0:00122
2024-11-19Some Easy Optimization Problems Have the Overlap-Gap Property0:00451
2024-11-19Understanding Contrastive Learning and Self-training0:00277
2024-11-18A Discrepancy-Based Theory of Adaptation0:00369
2024-11-18Learning from Dynamics0:001,590
2024-11-18Bypassing the Impossibility of Online Learning Thresholds: Unbounded Losses and Transductive Priors0:00245
2024-11-18The Truth About Your Lying Calibrated Forecaster: How to Design Truthful Calibration Measures0:00313
2024-11-15Open-Source and Science in the Era of Foundation Models0:00212
2024-11-15Panel Discussion0:00287