machine learning – Page 21 – Andrew Fairless, Ph.D.

What I Read: Transformers Training

By Andrew Fairless on January 19, 2023December 16, 2022

https://www.borealisai.com/research-blogs/tutorial-17-transformers-iii-training/ Tutorial #17: Transformers III Training08/06/2021P. Xu, S. Prince “…we discuss challenges with transformer training dynamics and introduce some of the tricks that practitioners use to get transformers to converge.”

What I learn: How, learn machine learning

By Andrew Fairless on January 18, 2023December 4, 2022

https://vickiboykis.com/2022/11/10/how-i-learn-machine-learning/ How I learn machine learningVicki BoykisNov 10 2022 “My overarching goal as an MLE is to continuously work towards designing and deploying well-designed, and transparent machine learning systems andContinue readingWhat I learn: How, learn machine learning

What I Read: Learning to Imitate

By Andrew Fairless on January 17, 2023December 4, 2022

https://ai.stanford.edu/blog/learning-to-imitate/ Learning to ImitateDivyansh GargNovember 1, 2022 “A key aspect of human learning is imitation…. How can we enable our artificial agents to similarly acquire such fast learning ability?”

What I Read: Federated, Protects Privacy

By Andrew Fairless on January 12, 2023December 4, 2022

https://pair.withgoogle.com/explorables/federated-learning/ How Federated Learning Protects Privacy “With federated learning, it’s possible to collaboratively train a model with data from multiple users without any raw data leaving their devices.”

What I Read: New Chip, AI

By Andrew Fairless on January 11, 2023December 4, 2022

https://www.quantamagazine.org/a-brain-inspired-chip-can-run-ai-with-far-less-energy-20221110/ New Chip Expands the Possibilities for AIAllison WhittenContributing WriterNovember 10, 2022 “An energy-efficient chip called NeuRRAM fixes an old design flaw to run large-scale AI algorithms on smaller devices,Continue readingWhat I Read: New Chip, AI

What I Read: large language model, UX

By Andrew Fairless on January 9, 2023November 5, 2022

https://medium.com/innovationendeavors/the-biggest-bottleneck-for-large-language-model-startups-is-ux-ef4500e4e786 The biggest bottleneck for large language model startups is UXDavis TreybigNov 1 “Applied large language model startups have exploded in the past year…. UX and product design is theContinue readingWhat I Read: large language model, UX

What I Read: Poisson Flow Generative Models

By Andrew Fairless on January 5, 2023November 5, 2022

https://www.assemblyai.com/blog/an-introduction-to-poisson-flow-generative-models/ An Introduction to Poisson Flow Generative ModelsRyan O’ConnorDeveloper EducatorOct 26, 2022 “Poisson Flow Generative Models (PFGMs) are a new type of generative Deep Learning model, taking inspiration from physicsContinue readingWhat I Read: Poisson Flow Generative Models

What I Read: The Farama Foundation

By Andrew Fairless on December 22, 2022November 5, 2022

https://farama.org/Announcing-The-Farama-Foundation Announcing The Farama FoundationThe future of open source reinforcement learning25 October 2022 “This means that the barrier to reinforcement learning seeing widespread deployment is a tooling problem…. Our grandContinue readingWhat I Read: The Farama Foundation

What I Read: Pre-Trained Models, Robotics

By Andrew Fairless on December 21, 2022November 5, 2022

https://sergeylevine.substack.com/p/general-purpose-pre-trained-models General-Purpose Pre-Trained Models in RoboticsCan we (pre-) train policies to control any robot for any task?Sergey LevineOct 16 “In robotics, learning policies from a small amount of data isContinue readingWhat I Read: Pre-Trained Models, Robotics

What I Read: Speech Recognition Metrics

By Andrew Fairless on December 12, 2022November 5, 2022

https://www.kdnuggets.com/2022/10/evolution-speech-recognition-metrics.html The Evolution of Speech Recognition MetricsBy Piyush Behre, Principal Applied Scientist at MicrosoftOctober 20, 2022 “As Speech Recognition has become more accurate than ever, scenarios like dictation and meetingContinue readingWhat I Read: Speech Recognition Metrics

Tag: machine learning