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Author Information
Megan Peters (UC Irvine)
Jürgen Schmidhuber (Swiss AI Lab, IDSIA (USI & SUPSI); NNAISENSE; KAUST)
Since age 15 or so, the main goal of professor Jürgen Schmidhuber has been to build a self-improving Artificial Intelligence (AI) smarter than himself, then retire. His lab's Deep Learning Neural Networks based on ideas published in the "Annus Mirabilis" 1990-1991 have revolutionised machine learning and AI. By the mid 2010s, they were on 3 billion devices, and used billions of times per day through users of the world's most valuable public companies, e.g., for greatly improved (CTC-LSTM-based) speech recognition on all Android phones, greatly improved machine translation through Google Translate and Facebook (over 4 billion LSTM-based translations per day), Apple's Siri and Quicktype on all iPhones, the answers of Amazon's Alexa, and numerous other applications. In 2011, his team was the first to win official computer vision contests through deep neural nets, with superhuman performance. In 2012, they had the first deep NN to win a medical imaging contest (on cancer detection). All of this attracted enormous interest from industry. His research group also established the fields of mathematically rigorous universal AI and recursive self-improvement in metalearning machines that learn to learn (since 1987). In 1990, he introduced unsupervised adversarial neural networks that fight each other in a minimax game to achieve artificial curiosity (GANs are a special case). In 1991, he introduced very deep learning through unsupervised pre-training, and neural fast weight programmers formally equivalent to what's now called linear Transformers. His formal theory of creativity & curiosity & fun explains art, science, music, and humor. He also generalized algorithmic information theory and the many-worlds theory of physics, and introduced the concept of Low-Complexity Art, the information age's extreme form of minimal art. He is recipient of numerous awards, author of over 350 peer-reviewed papers, and Chief Scientist of the company NNAISENSE, which aims at building the first practical general purpose AI. He is a frequent keynote speaker, and advising various governments on AI strategies.
Simona Ghetti (University of California, Davis)
Nick Roy (MIT)
Oiwi Parker Jones (University of Oxford)
Ingmar Posner (Oxford University)
More from the Same Authors
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2021 : Learning Adaptive Control Flow in Transformers for Improved Systematic Generalization »
Róbert Csordás · Kazuki Irie · Jürgen Schmidhuber -
2021 : Augmenting Classic Algorithms with Neural Components for Strong Generalisation on Ambiguous and High-Dimensional Data »
Imanol Schlag · Jürgen Schmidhuber -
2021 : Improving Baselines in the Wild »
Kazuki Irie · Imanol Schlag · Róbert Csordás · Jürgen Schmidhuber -
2021 : A Modern Self-Referential Weight Matrix That Learns to Modify Itself »
Kazuki Irie · Imanol Schlag · Róbert Csordás · Jürgen Schmidhuber -
2021 : Exploring through Random Curiosity with General Value Functions »
Aditya Ramesh · Louis Kirsch · Sjoerd van Steenkiste · Jürgen Schmidhuber -
2021 : Unsupervised Learning of Temporal Abstractions using Slot-based Transformers »
Anand Gopalakrishnan · Kazuki Irie · Jürgen Schmidhuber · Sjoerd van Steenkiste -
2021 : Object-Factored Models with Partially Observable State »
Isaiah Brand · Michael Noseworthy · Sebastian Castro · Nick Roy -
2021 : Unsupervised Learning of Temporal Abstractions using Slot-based Transformers »
Anand Gopalakrishnan · Kazuki Irie · Jürgen Schmidhuber · Sjoerd van Steenkiste -
2022 : Causal Discovery for Modular World Models »
Anson Lei · Bernhard Schölkopf · Ingmar Posner -
2022 : Learning to Control Rapidly Changing Synaptic Connections: An Alternative Type of Memory in Sequence Processing Artificial Neural Networks »
Kazuki Irie · Jürgen Schmidhuber -
2022 : On Narrative Information and the Distillation of Stories »
Dylan Ashley · Vincent Herrmann · Zachary Friggstad · Jürgen Schmidhuber -
2022 : The Benefits of Model-Based Generalization in Reinforcement Learning »
Kenny Young · Aditya Ramesh · Louis Kirsch · Jürgen Schmidhuber -
2022 : Learning gaze control, external attention, and internal attention since 1990-91 »
Jürgen Schmidhuber -
2022 Poster: Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules »
Kazuki Irie · Francesco Faccio · Jürgen Schmidhuber -
2022 Poster: Exploring through Random Curiosity with General Value Functions »
Aditya Ramesh · Louis Kirsch · Sjoerd van Steenkiste · Jürgen Schmidhuber -
2021 : Panel A: Deployable Learning Algorithms for Embodied Systems »
Shuran Song · Martin Riedmiller · Nick Roy · Aude G Billard · Angela Schoellig · SiQi Zhou -
2021 : Learning Abstractions for Robust and Tractable Planning »
Nick Roy -
2021 : Credit Assignment & Meta-Learning in a Single Lifelong Trial »
Jürgen Schmidhuber -
2021 : How does a brain compute confidence? »
Megan Peters -
2021 Workshop: Metacognition in the Age of AI: Challenges and Opportunities »
Ingmar Posner · Francesca Rossi · Lior Horesh · Steve Fleming · Oiwi Parker Jones · Rohan Paul · Biplav Srivastava · Andrea Loreggia · Marianna Ganapini -
2021 : Introduction to the Workshop on Metacognition in the Age of AI: Challenges and Opportunities »
Ingmar Posner · Steve Fleming · Francesca Rossi -
2021 Poster: Going Beyond Linear Transformers with Recurrent Fast Weight Programmers »
Kazuki Irie · Imanol Schlag · Róbert Csordás · Jürgen Schmidhuber -
2021 Poster: GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement »
Martin Engelcke · Oiwi Parker Jones · Ingmar Posner -
2021 Poster: E(n) Equivariant Normalizing Flows »
Victor Garcia Satorras · Emiel Hoogeboom · Fabian Fuchs · Ingmar Posner · Max Welling -
2021 Poster: Meta Learning Backpropagation And Improving It »
Louis Kirsch · Jürgen Schmidhuber -
2021 Oral: E(n) Equivariant Normalizing Flows »
Victor Garcia Satorras · Emiel Hoogeboom · Fabian Fuchs · Ingmar Posner · Max Welling -
2020 : Indigenous Protocols and Artificial Intelligence, Working Group Roundtable »
Suzanne Kite · Ashley Cordes · Oiwi Parker Jones · Jason Edward Lewis -
2020 Poster: RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent Spaces »
Sebastien Ehrhardt · Oliver Groth · Aron Monszpart · Martin Engelcke · Ingmar Posner · Niloy Mitra · Andrea Vedaldi -
2020 Poster: Belief-Dependent Macro-Action Discovery in POMDPs using the Value of Information »
Genevieve Flaspohler · Nick Roy · John Fisher III -
2019 : Panel Discussion »
Jacob Andreas · Edward Gibson · Stefan Lee · Noga Zaslavsky · Jason Eisner · Jürgen Schmidhuber -
2019 : Coffee Break & Poster Session 1 »
Yan Zhang · Jonathon Hare · Adam Prugel-Bennett · Po Leung · Patrick Flaherty · Pitchaya Wiratchotisatian · Alessandro Epasto · Silvio Lattanzi · Sergei Vassilvitskii · Morteza Zadimoghaddam · Theja Tulabandhula · Fabian Fuchs · Adam Kosiorek · Ingmar Posner · William Hang · Anna Goldie · Sujith Ravi · Azalia Mirhoseini · Yuwen Xiong · Mengye Ren · Renjie Liao · Raquel Urtasun · Haici Zhang · Michele Borassi · Shengda Luo · Andrew Trapp · Geoffroy Dubourg-Felonneau · Yasmeen Kussad · Christopher Bender · Manzil Zaheer · Junier Oliva · Michał Stypułkowski · Maciej Zieba · Austin Dill · Chun-Liang Li · Songwei Ge · Eunsu Kang · Oiwi Parker Jones · Kelvin Ka Wing Wong · Joshua Payne · Yang Li · Azade Nazi · Erkut Erdem · Aykut Erdem · Kevin O'Connor · Juan J Garcia · Maciej Zamorski · Jan Chorowski · Deeksha Sinha · Harry Clifford · John W Cassidy -
2019 Poster: Are Disentangled Representations Helpful for Abstract Visual Reasoning? »
Sjoerd van Steenkiste · Francesco Locatello · Jürgen Schmidhuber · Olivier Bachem -
2018 : Invited Talk: Ingmar Posner, Oxford and Oxbotica »
Ingmar Posner -
2018 : Invited Speaker #4 Juergen Schmidhuber »
Jürgen Schmidhuber -
2018 : Ingmar Posner »
Ingmar Posner -
2018 Poster: Recurrent World Models Facilitate Policy Evolution »
David Ha · Jürgen Schmidhuber -
2018 Oral: Recurrent World Models Facilitate Policy Evolution »
David Ha · Jürgen Schmidhuber -
2018 Poster: Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects »
Adam Kosiorek · Hyunjik Kim · Yee Whye Teh · Ingmar Posner -
2018 Spotlight: Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects »
Adam Kosiorek · Hyunjik Kim · Yee Whye Teh · Ingmar Posner -
2018 Poster: Learning to Reason with Third Order Tensor Products »
Imanol Schlag · Jürgen Schmidhuber -
2017 : Morning panel discussion »
Jürgen Schmidhuber · Noah Goodman · Anca Dragan · Pushmeet Kohli · Dhruv Batra -
2017 : HRL with gradient-based subgoal generators, asymptotically optimal incremental problem solvers, various meta-learners, and PowerPlay (Jürgen Schmidhuber) »
Jürgen Schmidhuber -
2017 : Invited Talk »
Jürgen Schmidhuber -
2017 Workshop: Acting and Interacting in the Real World: Challenges in Robot Learning »
Ingmar Posner · Raia Hadsell · Martin Riedmiller · Markus Wulfmeier · Rohan Paul -
2017 Poster: Hierarchical Attentive Recurrent Tracking »
Adam Kosiorek · Alex Bewley · Ingmar Posner -
2017 Poster: Neural Expectation Maximization »
Klaus Greff · Sjoerd van Steenkiste · Jürgen Schmidhuber -
2016 : Juergen Schmidhuber (Scientific Director of the Swiss AI Lab IDSIA) »
Jürgen Schmidhuber -
2016 Symposium: Recurrent Neural Networks and Other Machines that Learn Algorithms »
Jürgen Schmidhuber · Sepp Hochreiter · Alex Graves · Rupesh K Srivastava -
2016 Poster: Tagger: Deep Unsupervised Perceptual Grouping »
Klaus Greff · Antti Rasmus · Mathias Berglund · Hotloo Xiranood · Harri Valpola · Jürgen Schmidhuber -
2015 : Deep Learning RNNaissance »
Jürgen Schmidhuber -
2015 : On General Problem Solving and How to Learn an Algorithm »
Jürgen Schmidhuber -
2015 Poster: Training Very Deep Networks »
Rupesh K Srivastava · Klaus Greff · Jürgen Schmidhuber -
2015 Spotlight: Training Very Deep Networks »
Rupesh K Srivastava · Klaus Greff · Jürgen Schmidhuber -
2015 Poster: Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation »
Marijn F Stollenga · Wonmin Byeon · Marcus Liwicki · Jürgen Schmidhuber -
2014 Poster: Deep Networks with Internal Selective Attention through Feedback Connections »
Marijn F Stollenga · Jonathan Masci · Faustino Gomez · Jürgen Schmidhuber -
2013 Poster: Compete to Compute »
Rupesh K Srivastava · Jonathan Masci · Sohrob Kazerounian · Faustino Gomez · Jürgen Schmidhuber -
2012 Poster: Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images »
Dan Ciresan · Alessandro Giusti · luca Maria Gambardella · Jürgen Schmidhuber -
2010 Poster: Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices »
Yi Sun · Faustino Gomez · Jürgen Schmidhuber -
2008 Poster: Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks »
Alex Graves · Jürgen Schmidhuber -
2008 Spotlight: Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks »
Alex Graves · Jürgen Schmidhuber -
2007 Poster: Unconstrained On-line Handwriting Recognition with Recurrent Neural Networks »
Alex Graves · Santiago Fernandez · Marcus Liwicki · Horst Bunke · Jürgen Schmidhuber