machine learning – Page 29 – Andrew Fairless, Ph.D.

What I Read: DALL·E 2, Explained

By Andrew Fairless on August 8, 2022June 27, 2022

https://towardsdatascience.com/dall-e-2-explained-the-promise-and-limitations-of-a-revolutionary-ai-3faf691be220 DALL·E 2, Explained: The Promise and Limitations of a Revolutionary AIWith images and videos that you most likely haven’t seen.Alberto RomeroJun 16 “DALL·E 2 is the newest AI modelContinue readingWhat I Read: DALL·E 2, Explained

What I Read: Minerva, Quantitative Reasoning

By Andrew Fairless on August 4, 2022July 8, 2022

https://ai.googleblog.com/2022/06/minerva-solving-quantitative-reasoning.html Minerva: Solving Quantitative Reasoning Problems with Language ModelsThursday, June 30, 2022Posted by Ethan Dyer and Guy Gur-Ari, Research Scientists, Google Research, Blueshift Team “…we present Minerva, a language modelContinue readingWhat I Read: Minerva, Quantitative Reasoning

What I Read: Neural-Implicit Representations, 3D Shapes

By Andrew Fairless on August 2, 2022July 8, 2022

https://towardsdatascience.com/neural-implicit-representations-for-3d-shapes-and-scenes-c6750dff49db?gi=dd4876367dbb Neural-Implicit Representations for 3D Shapes and ScenesOmri KaduriJun 26 “Tracing the progress of deep learning-based solutions to computer graphics tasks”

What I Read: Annotated Diffusion Model

By Andrew Fairless on August 1, 2022June 27, 2022

https://huggingface.co/blog/annotated-diffusion The Annotated Diffusion ModelPublished June 7th, 2022Niels RoggeKashif Rasul “In this blog post, we’ll take a deeper look into Denoising Diffusion Probabilistic Models… as researchers have been able toContinue readingWhat I Read: Annotated Diffusion Model

What I Read: Against Naive AI Scaling

By Andrew Fairless on July 27, 2022June 27, 2022

https://jacobbuckman.com/2022-06-14-an-actually-good-argument-against-naive-ai-scaling/ An Actually-Good Argument Against Naive AI ScalingJacob BuckmanPosted on June 14, 2022 “…the debate is whether scaled-up language models in the style of GPT-3 will eventually become general intelligences,Continue readingWhat I Read: Against Naive AI Scaling

What I Read: Text Embeddings Visually Explained

By Andrew Fairless on July 26, 2022July 8, 2022

https://txt.cohere.ai/text-embeddings/ Text Embeddings Visually ExplainedMeor AmerJun 28, 2022 “We take a visual approach to gain an intuition behind text embeddings, what use cases they are good for, and how theyContinue readingWhat I Read: Text Embeddings Visually Explained

What I Read: What is Reinforcement Learning

By Andrew Fairless on July 20, 2022June 27, 2022

https://castlelab.princeton.edu/what-is-rl/ What is Reinforcement LearningWarren B PowellProfessor Emeritus, Princeton University “…I provide a brief introduction to modeling sequential decision problems… and then designing policies. As I watch the evolution ofContinue readingWhat I Read: What is Reinforcement Learning

What I Read: Exploring Virtual Worlds, AI

By Andrew Fairless on July 14, 2022July 8, 2022

https://www.quantamagazine.org/ai-makes-strides-in-virtual-worlds-more-like-our-own-20220624/ By Exploring Virtual Worlds, AI Learns in New WaysAllison WhittenContributing WriterJune 24, 2022 “Intelligent beings learn by interacting with the world. Artificial intelligence researchers have adopted a similar strategyContinue readingWhat I Read: Exploring Virtual Worlds, AI

What I Read: Make the Universe Think

By Andrew Fairless on July 13, 2022June 27, 2022

https://www.quantamagazine.org/how-to-make-the-universe-think-for-us-20220531/ How to Make the Universe Think for UsCharlie WoodStaff WriterMay 31, 2022 “Physicists are building neural networks out of vibrations, voltages and lasers, arguing that the future of computingContinue readingWhat I Read: Make the Universe Think

What I Read: Bundling into the Database

By Andrew Fairless on July 5, 2022June 27, 2022

https://www.ethanrosenthal.com/2022/05/10/database-bundling/ Let’s Continue Bundling into the DatabaseEthan RosenthalMay 10, 2022 “Truthfully, I just want to argue that feature stores, metrics layers, and machine learning monitoring tools are all abstraction layersContinue readingWhat I Read: Bundling into the Database

Tag: machine learning