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Introducing NYU Center for Data Science Research Groups

NYU Center for Data Science

CDS includes a range of research groups that bring together NYU professors, faculty fellows, and PhD students working at various intersections of data science, machine learning, and artificial intelligence. Read our research group roundup below and check out their linked websites for more information!

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Frugality meets Accuracy: Cost-efficient training of GPT NeoX and Pythia models with AWS Trainium

AWS Machine Learning Blog

In this post, we’ll summarize training procedure of GPT NeoX on AWS Trainium , a purpose-built machine learning (ML) accelerator optimized for deep learning training. In this post, we showed cost-efficient training of LLMs on AWS deep learning hardware. Ben Snyder is an applied scientist with AWS Deep Learning.

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Top 10 Generative AI Companies Revealed

Towards AI

Generative Artificial Intelligence is guiding the forward for businesses worldwide. Generative AI, being an excellent successor of Artificial Intelligence, has made its presence felt with ever-amazing explorations. Get a closer view of the top generative AI companies making waves in 2024.

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Fast and cost-effective LLaMA 2 fine-tuning with AWS Trainium

AWS Machine Learning Blog

He focuses on developing scalable machine learning algorithms. His research interests are in the area of natural language processing, explainable deep learning on tabular data, and robust analysis of non-parametric space-time clustering. He was a recipient of the NSF Faculty Early Career Development Award in 2009.

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Top recommended AI companies in Vietnam to collaborate in 2024

Dataconomy

In the upcoming years, Vietnam is projected to identify itself as a significant hub for artificial intelligence (AI) development. KMS Technology KMS Technology is a pioneer in the AI sector in Vietnam, providing businesses with robust AI and machine learning solutions.

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How Open Source Developers Can Push the Universe’s Frontier

ODSC - Open Data Science

2009, a paper by Postberg et al. Additionally, he applies Machine Learning algorithms to analyze astronomy- and space-related data to derive new scientific insights or to create new methods for calibrating instruments. Editor’s note: Dr.-Ing. Thomas Albin is a speaker for ODSC Europe this June 14th-15th. was published in Nature.

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Amazon SageMaker built-in LightGBM now offers distributed training using Dask

AWS Machine Learning Blog

For the NYC taxi data, we use the yellow trip taxi records from 2009–2022. He focuses on developing scalable machine learning algorithms. His research interests are in the area of natural language processing, explainable deep learning on tabular data, and robust analysis of non-parametric space-time clustering.

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