natural language processing – Page 14

What I Read: How Train Large Deep Learning Models

By Andrew Fairless on November 8, 2021October 24, 2021

https://www.assemblyai.com/blog/how-to-train-large-deep-learning-models-as-a-startup/ How to Train Large Deep Learning Models as a StartupDylan FoxOct 7, 2021Training large deep learning models is expensive and slow. Yet, startups are all about iterating fast. InContinue readingWhat I Read: How Train Large Deep Learning Models

What I Read: AI Story Generation

By Andrew Fairless on September 22, 2021September 4, 2021

https://thegradient.pub/an-introduction-to-ai-story-generation/ An Introduction to AI Story Generation21.Aug.2021Mark Riedl “To tell a story, an intelligent system has to have a lot of knowledge, both about how to tell a story andContinue readingWhat I Read: AI Story Generation

What I Read: Learning Neural Network Subspaces

By Andrew Fairless on September 20, 2021September 4, 2021

https://arxiv.org/abs/2102.10472 Learning Neural Network SubspacesMitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari “These neural network subspaces contain diverse solutions that can be ensembled, approaching the ensemble performance ofContinue readingWhat I Read: Learning Neural Network Subspaces

What I Read: Machine Learning Won’t Solve Natural Language Understanding

By Andrew Fairless on September 6, 2021August 17, 2021

https://thegradient.pub/machine-learning-wont-solve-the-natural-language-understanding-challenge/ Machine Learning Won’t Solve Natural Language UnderstandingWalid S. Saba07.Aug.2021 “While NLP (Natural Language Processing) and NLU (Natural Language Understanding) are often used interchangeably, there is a substantial difference betweenContinue readingWhat I Read: Machine Learning Won’t Solve Natural Language Understanding

What I Read: Geometric, Deep Learning

By Andrew Fairless on August 16, 2021July 22, 2021

https://towardsdatascience.com/geometric-foundations-of-deep-learning-94cdd45b451d?gi=d7fa7307aa63 Geometric foundations of Deep LearningGeometric Deep Learning is an attempt for geometric unification of a broad class of ML problems from the perspectives of symmetry and invariance. These principlesContinue readingWhat I Read: Geometric, Deep Learning

What I Read: Training AI, Analogies

By Andrew Fairless on August 13, 2021July 22, 2021

https://www.quantamagazine.org/melanie-mitchell-trains-ai-to-think-with-analogies-20210714/ The Computer Scientist Training AI to Think With AnalogiesMelanie Mitchell has worked on digital minds for decades. She says they’ll never truly be like ours until they can makeContinue readingWhat I Read: Training AI, Analogies

What I Read: Identifying Document Types

By Andrew Fairless on August 11, 2021July 22, 2021

https://tech.scribd.com/blog/2021/identifying-document-types.html Identifying Document Types at ScribdJonathan RamkissoonJuly 12, 2021 “User-uploaded documents have been a core component of Scribd’s business from the very beginning, understanding what is actually in the documentContinue readingWhat I Read: Identifying Document Types

What I Read: Prompting, Language Models, NLP

By Andrew Fairless on August 9, 2021July 22, 2021

https://thegradient.pub/prompting/ Prompting: Better Ways of Using Language Models for NLP Tasks03.Jul.2021Tianyu Gao “The giant model size of GPT-3 is an important factor for its success, while the concept of promptsContinue readingWhat I Read: Prompting, Language Models, NLP

What I Read: Understanding Levenshtein Distance

By Andrew Fairless on August 5, 2021July 12, 2021

https://medium.com/@ethannam/understanding-the-levenshtein-distance-equation-for-beginners-c4285a5604f0 Understanding the Levenshtein Distance Equation for BeginnersEthan NamFeb 26, 2019 “The Levenshtein distance is a number that tells you how different two strings are. The higher the number, theContinue readingWhat I Read: Understanding Levenshtein Distance

What I Read: Semantic Search

By Andrew Fairless on July 20, 2021July 2, 2021

https://www.pinecone.io/learn/semantic-search/ Semantic Search: Measuring Meaning From Jaccard to BertJames BriggsData Scientist “Similarity search is a complex topic and there are countless techniques for building effective search engines. In this article,Continue readingWhat I Read: Semantic Search

Tag: natural language processing