computer vision – Page 3 – Andrew Fairless, Ph.D.

What I Read: AI, Images

By Andrew Fairless on October 11, 2023September 4, 2023

https://www.quantamagazine.org/the-ai-tools-making-images-look-better-20230823/ The AI Tools Making Images Look BetterAmos ZeebergAugust 23, 2023 “Researchers have discovered ways around a fundamental trade-off between accuracy and beauty in digital images.”

What I Read: Multimodal, Embeddings

By Andrew Fairless on October 5, 2023September 4, 2023

https://app.twelvelabs.io/blog/multimodal-embeddings The Multimodal Evolution of Vector EmbeddingsJames LeAugust 9, 2023 “…companies collect and feed hundreds of millions of terabytes of multimodal data into deep learning models. As a result, embeddings…Continue readingWhat I Read: Multimodal, Embeddings

What I Read: Economic Case for Generative AI

By Andrew Fairless on September 21, 2023September 4, 2023

https://a16z.com/2023/08/03/the-economic-case-for-generative-ai-and-foundation-models/ The Economic Case for Generative AI and Foundation Modelsby Martin Casado and Sarah Wang “…we believe there’s a very strong argument that generative AI is not only economically viable,Continue readingWhat I Read: Economic Case for Generative AI

What I Read: Neural Networks, Data, Fake

By Andrew Fairless on August 3, 2023July 9, 2023

https://www.quantamagazine.org/neural-networks-need-data-to-learn-even-if-its-fake-20230616/ Neural Networks Need Data to Learn. Even If It’s Fake.Amos ZeebergJune 16, 2023 “Real data can be hard to get, so researchers are turning to synthetic data to trainContinue readingWhat I Read: Neural Networks, Data, Fake

What I Read: Multimodal Models

By Andrew Fairless on May 24, 2023May 1, 2023

https://www.kdnuggets.com/2023/03/multimodal-models-explained.html Multimodal Models ExplainedBy Nate RosidiMarch 27, 2023 “…multimodal learning is an exciting new field of AI that seeks to replicate this ability by combining information from multiple models. ByContinue readingWhat I Read: Multimodal Models

What I Read: Competitive Machine Learning

By Andrew Fairless on May 9, 2023March 30, 2023

https://mlcontests.com/state-of-competitive-machine-learning-2022/ The State of Competitive Machine Learning2022 Edition “We summarise the state of the competitive landscape and analyse the 200+ competitions that took place in 2022. Plus a deep diveContinue readingWhat I Read: Competitive Machine Learning

What I Read: Relative representations

By Andrew Fairless on April 18, 2023March 30, 2023

https://arxiv.org/abs/2209.15430 Relative representations enable zero-shot latent space communicationLuca Moschella, Valentino Maiorca, Marco Fumero, Antonio Norelli, Francesco Locatello, Emanuele Rodolà “…we propose to adopt pairwise similarities as an alternative data representation,Continue readingWhat I Read: Relative representations

What I Learn: neural scaling, data pruning

By Andrew Fairless on April 11, 2023February 22, 2023

https://arxiv.org/abs/2206.14486 Beyond neural scaling laws: beating power law scaling via data pruningBen Sorscher, Robert Geirhos, Shashank Shekhar, Surya Ganguli, Ari S. Morcos[Submitted on 29 Jun 2022 (v1), last revised 15Continue readingWhat I Learn: neural scaling, data pruning

What I Read: Machines Learn, Teach Basics

By Andrew Fairless on March 21, 2023February 6, 2023

https://www.quantamagazine.org/machines-learn-better-if-we-teach-them-the-basics-20230201/ Machines Learn Better if We Teach Them the BasicsMax G. LevyFebruary 1, 2023 “A wave of research improves reinforcement learning algorithms by pre-training them as if they were human.”

What I Read: Modern AI Art

By Andrew Fairless on March 6, 2023January 9, 2023

https://www.quantamagazine.org/the-physics-principle-that-inspired-modern-ai-art-20230105/ The Physics Principle That Inspired Modern AI ArtAnil AnanthaswamyJanuary 5, 2023 “Diffusion models generate incredible images by learning to reverse the process that, among other things, causes ink toContinue readingWhat I Read: Modern AI Art

Tag: computer vision