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Chatbots, AI Generated Fake Faces & Carbon Footprints — What’s Hot on Reddit?

Synced Global AI Weekly June 9th

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There’s a Subreddit Populated Entirely by AI Personifications of Other Subreddits
Chatbots are finally getting good — or, at the very least, they’re getting entertaining. Case in point is r/SubSimulatorGPT2, an enigmatically-named subreddit with a unique composition: it’s populated entirely by AI chatbots that personify other subreddits.
(The Verge) / (r/SubSimulatorGPT2)

[P] One Million AI Generated Fake Faces for Download
Reddit user Alexander Reben has generated 1 million faces with NVIDIA’s StyleGAN and released them under the same CC BY-NC 4.0 license for free download.
(r/MachineLearning) / (1 million fake faces)

[D] Training A Single AI Model Can Emit as Much Carbon as Five Cars in Their Lifetimes
In a new paper, researchers at the University of Massachusetts, Amherst, performed a life cycle assessment for training several common large AI models. They found that the process can emit more than 626,000 pounds of carbon dioxide equivalent—nearly five times the lifetime emissions of the average American car.
(r/MachineLearning) / (MIT Technology Review)

[P] Using Neural Networks (CycleGAN) to Generate Pokemon as Different Elemental Types
CycleGAN is an image-to-image translation model that allows us to “translate” from one set of images to another. The open-source implementation used to train and generate these images of Pokémon uses PyTorch and can be found on Github here. For this project, Riley Wong trained the model to translate between sets of Pokémon images of different types, e.g. translating images of water types to fire types.
(r/MachineLearning) / (Riley Wong)


Collaborative Evolutionary Reinforcement Learning
Researchers presented CERL, a scalable platform that allows gradient-based learners to jointly explore and exploit solutions in a gradient-free evolutionary framework. Experiments in continuous control demonstrate that CERL’s emergent learner can outperform its composite learners remaining overall sample-efficient compared to traditional approaches.
(Intel AI Lab & Oregon State University)

MixMatch: A Holistic Approach to Semi-Supervised Learning
Ian Goodfellow and researchers from Google Research unify the current dominant approaches for semi-supervised learning to produce a new algorithm, MixMatch, that works by guessing low-entropy labels for data-augmented unlabeled examples and mixing labeled and unlabeled data using MixUp.
(Ian Goodfellow & Google Research)

Autonomous Vehicles for Social Good: Learning to Solve Congestion
Researchers propose 11 new benchmarks in centralized mixed-autonomy traffic control. They released these benchmarks as a part of Flow, a tool developed for applying control and reinforcement learning to autonomous vehicles and traffic lights in the traffic simulators SUMO and AIMSUN.
(Berkeley Artificial Intelligence Research)

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CapsAttacks: Testing Adversarial Attacks on Capsule Networks
Researchers from Technische Universität Wien, Austria, and Politecnico di Torino, Italy, explored adversarial attacks on Capsule Networks, proposing an algorithm which automatically generates targeted adversarial examples in black-box attack scenarios.

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1 comment on “Chatbots, AI Generated Fake Faces & Carbon Footprints — What’s Hot on Reddit?

  1. Pingback: Chatbots, AI Generated Fake Faces & Carbon Footprints — What’s Hot on Reddit? – Tech Check News

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