AI Weekly

OCTOBER 26, 2023

cryptopolitan.com Applied use cases Alluxio rolls out new filesystem built for deep learning Alluxio Enterprise AI is aimed at data-intensive deep learning applications such as generative AI, computer vision, natural language processing, large language models and high-performance data analytics. voxeurop.eu

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Sebastian Ruder

JANUARY 19, 2021

2020 ), Turing-NLG , BST ( Roller et al., 2020 ), and GPT-3 ( Brown et al., 2020 ; Fan et al., 2020 ), quantization ( Fan et al., 2020 ), and compression ( Xu et al., 2020 ; Fan et al., 2020 ), quantization ( Fan et al., 2020 ), and compression ( Xu et al., 2020 ) and Big Bird ( Zaheer et al.,

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Viso.ai

OCTOBER 15, 2024

In the field of real-time object identification, YOLOv11 architecture is an advancement over its predecessor, the Region-based Convolutional Neural Network (R-CNN). Using an entire image as input, this single-pass approach with a single neural network predicts bounding boxes and class probabilities.

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Viso.ai

FEBRUARY 25, 2023

Vision Transformer (ViT) have recently emerged as a competitive alternative to Convolutional Neural Networks (CNNs) that are currently state-of-the-art in different image recognition computer vision tasks. This article will cover the following topics: What is a Vision Transformer (ViT)?

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Bugra Akyildiz

NOVEMBER 17, 2024

This uses advanced computer vision techniques, specifically a Vision Transformer model, to analyze and organize photos of properties. Vision Transformers(ViT) ViT is a type of machine learning model that applies the transformer architecture, originally developed for natural language processing, to image recognition tasks.

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Viso.ai

OCTOBER 7, 2024

This is an iterative approach where the user interacts with a machine-learning algorithm such as a computer vision (CV) system and provides feedback on its outputs. This iterative approach involves user interaction with a machine-learning algorithm, such as a computer vision (CV) system, providing feedback on its outputs.

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Heartbeat

JANUARY 11, 2023

The beginning of 2023 brings with it a shift in focus for Heartbeat and we’re excited to dive deeper into Comet related tutorials, more deep learning content, and some NLP and computer vision projects. Until 2020, the process of measuring a convolutional neural network was never well understood.

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Viso.ai

FEBRUARY 27, 2024

Farhadi, signifying a step forward in the real-time object detection space, outperforming its predecessor – the Region-based Convolutional Neural Network (R-CNN). It is a single-pass algorithm having only one neural network to predict bounding boxes and class probabilities using a full image as input. Divvala, R.

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Viso.ai

DECEMBER 18, 2023

YOLOv8 is the newest model in the YOLO algorithm series – the most well-known family of object detection and classification models in the Computer Vision (CV) field. offers the world’s leading end-to-end no-code Computer Vision Platform Viso Suite. Get a demo. at 22 milliseconds. The model achieved 43.5

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Viso.ai

MAY 6, 2024

By eliminating the need to purchase and manage point solutions, Viso Suite presents teams with a truly end-to-end computer vision infrastructure. The latest version is Kinetics 700-2020, which contains over 700 human action classes from up to 650,000 video clips. An introduction to Graph Neural Networks (GNNs).

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How to Learn Machine Learning

MAY 14, 2023

When selecting projects, consider tackling problems in different domains, such as natural language processing, computer vision, or recommendation systems. Some popular areas of specialization include natural language processing, computer vision, and reinforcement learning. Publisher) Buy on Amazon 5.

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Viso.ai

MAY 20, 2023

The YOLOv7 algorithm is making big waves in the computer vision and machine learning communities. It requires several times cheaper hardware than other neural networks and can be trained much faster on small datasets without any pre-trained weights. About us: Viso.ai Get a Demo for your company.

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Heartbeat

JUNE 6, 2023

GCNs have been successfully applied to many domains, including computer vision and social network analysis. GCNs use a combination of graph-based representations and convolutional neural networks to analyze large amounts of textual data. References Paperwithcode | Graph Convolutional Network Kai, S.,

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AWS Machine Learning Blog

FEBRUARY 10, 2023

For a given frame, our features are inspired by the 2020 Big Data Bowl Kaggle Zoo solution ( Gordeev et al. ): we construct an image for each time step with the defensive players at the rows and offensive players at the columns. Computer Vision with NFL Player Tracking Data using torch for R: Coverage classification Using CNNs.”

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Google Research AI blog

JANUARY 18, 2023

I will begin with a discussion of language, computer vision, multi-modal models, and generative machine learning models. Over the next several weeks, we will discuss novel developments in research topics ranging from responsible AI to algorithms and computer systems to science, health and robotics. Let’s get started!

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Snorkel AI

MARCH 1, 2023

This model debuted in June 2020, but remained a tool for researchers and ML practitioners until its creator, OpenAI, debuted a consumer-friendly chat interface in November 2022. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Radford et al. Attention Is All You Need Vaswani et al.

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Lexalytics

APRIL 5, 2021

While working as an RA in the computer vision group, I had the opportunity to sit in a robotic Humvee as it used Pomerleau’s code to drive around the University of Massachusetts’ stadium.) The CNN was a 6-layer neural net with 132 convolution kernels and (don’t laugh!) Hinton (again!)

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ML Review

DECEMBER 16, 2019

NeurIPS’18 presented several papers with deep theoretical studies of building hyperbolic neural nets. Source: Chami et al Chami et al present Hyperbolic Graph Convolutional Neural Networks (HGCN) and Liu et al propose Hyperbolic Graph Neural Networks (HGNN). Top-5 accuracy grows from previous SOTA of 84.3%

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