Flipboard

JUNE 20, 2023

It imitates how the human brain works using artificial neural networks (explained below), allowing the AI to learn highly complex patterns in data. Deep learning was pioneered between 2010 and 2015 by DeepMind , a company founded in London by UCL researchers Demis Hassabis and Shane Legg and acquired by Google in 2014.

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NVIDIA

JUNE 27, 2023

The company uses NVIDIA Tensor Core GPUs in its generative AI drug design engine, Chemistry42, to generate novel molecular structures — and was one of the first adopters of an early precursor to NVIDIA DGX systems in 2015. AI Enables End-to-End Preclinical Drug Discovery Insilico’s Pharma.AI

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Viso.ai

FEBRUARY 11, 2024

2015 – Microsoft researchers report that their Convolutional Neural Networks (CNNs) exceed human ability in pure ILSVRC tasks. Object Detection and Instance Segmentation – DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network, published by Xuan Shen et al.,

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Heartbeat

DECEMBER 20, 2023

This blog aims to equip you with a thorough understanding of these powerful neural network architectures. In a typical neural network, you flatten your input one vector, take those input values in at once, multiply them by the weights in the first layer, add the bias, and pass the result into a neuron.

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Convolutional Neural Networks Neural Network Deep Learning Computer Vision 52

Artificial Corner

JUNE 23, 2023

Like U-Net, TransUnet includes two main sections: Encoder (Vision Transformer): Vision Transformer encodes patches of feature maps that are generated by a convolution neural network. Brox, U-Net: Convolutional Networks for Biomedical Image Segmentation (2015) [2] A. References [1] O. Ronneberger, P. Fischer, T.

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ODSC - Open Data Science

JUNE 9, 2023

In the 90’s we got grunge, statistical models, recurrent neural networks and long short-term memory models (LSTM). 2000–2015 The new millennium gave us low-rise jeans, trucker hats, and bigger advancements in language modeling, word embeddings, and Google Translate. Word2vec is one of the most common word vectorization methods.

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Natural Language Processing ChatGPT Generative AI BERT 52

TheSequence

NOVEMBER 22, 2023

I’ve been interested in AI for a long time, but didn’t work in it as a core area until about 2015. I co-authored my first AI-related paper in 2000 ( using neural networks to manage on-CPU hardware resources ). Understanding biological neural networks is one current focus.

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Topbots

MARCH 5, 2024

In 2015, engineer and creative storyteller Samim trained a neural network on 14 million lines of passages from romance novels and asked the model to generate original stories based on new images. The research advancements quickly transformed into practical applications.

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AWS Machine Learning Blog

DECEMBER 7, 2023

Getir was founded in 2015 and operates in Turkey, the UK, the Netherlands, Germany, and the United States. CNN-QR is a proprietary ML algorithm developed by Amazon for forecasting scalar (one-dimensional) time series using causal Convolutional Neural Networks (CNNs). Getir is the pioneer of ultrafast grocery delivery.

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Topbots

MAY 17, 2023

In 2015, a research paper from Stanford University and UC Berkeley introduced diffusion models, coming originally from statistical physics, into the field of machine learning. However, the quality of generated images was quite poor back in 2015, as there was still huge room for improvement. Midjourney Evolution.

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Towards AI

FEBRUARY 14, 2023

Generative AI involves the use of neural networks to create new content such as images, videos, or text. OpenAI, on the other hand, is an AI research laboratory that was founded in 2015. Its ability to create realistic and novel content has promising applications in fields such as entertainment, design, and medicine.

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Snorkel AI

FEBRUARY 13, 2024

A different approach: knowledge distillation Knowledge distillation uses a larger “teacher” neural network model to sharpen the performance of a smaller “student’ neural network.

LLM 52

LLM Data Scientist Neural Network Data Science 52

Snorkel AI

FEBRUARY 13, 2024

A different approach: knowledge distillation Knowledge distillation uses a larger “teacher” neural network model to sharpen the performance of a smaller “student’ neural network.

LLM 52

LLM Data Scientist Neural Network Data Science 52

Bugra Akyildiz

DECEMBER 10, 2023

It uses a graph neural network (GNN) to model the relationships between different weather variables. GraphCast is already being used by some weather agencies, and the model code is open sourced(in below Libraries section, I gave couple of pointers). This allows it to capture complex relationships that traditional models cannot.

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Neural Network Prompt Engineer Prompt Engineering ChatGPT 52

PyImageSearch

JANUARY 30, 2023

Figure 6: Changing demand for core work-related skills from 2015 to 2020 (source: IFC ). In Deep Learning, we need to train Neural Networks. These Neural Networks can be trained on a CPU but take a lot of time. Moreover, sometimes these networks do not even fit (run) on a CPU.

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Computer Vision Deep Learning Neural Network Artificial Intelligence 107

Dlabs.ai

JANUARY 12, 2021

And with every new release — spanning ES2 in 1998, ES3 in 1999, ES5 in 2009, and ES6 in 2015 — the language has gained more and more traction. Still, over the years, it has proved a reliable library for building neural networks. But JavaScript is only the commercial name for it. But there’s one exception.

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Viso.ai

APRIL 23, 2024

Introduced in 2015 by Olaf Ronneberger’s team, U-Net aimed to create a high-performing network that could work with limited training data, addressing the challenge of scarce annotated images in the medical field. U-Net, a deep learning model specifically designed for biomedical image segmentation, exemplifies this.

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Deep Learning Convolutional Neural Networks Neural Network Computer Vision 52

Viso.ai

APRIL 25, 2024

Today’s boom in CV started with the implementation of deep learning models and convolutional neural networks (CNN). 2015) published a paper called EdgeFace or Efficient Face Recognition Model. This paper introduced EdgeFace, a lightweight and efficient face recognition network inspired by the hybrid architecture of EdgeNeXt.

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Computer Vision Deep Learning Convolutional Neural Networks Python 52

Flipboard

AUGUST 25, 2023

Deep learning is a type of machine learning where artificial neural networks ( similar but not exactly like the neurons in our brain) allow a machine to learn and advance independent of human intervention. Throughout the 2000s , pharmaceutical giants and plucky startups saw an opportunity to accelerate the drug development process.

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PyImageSearch

NOVEMBER 13, 2023

For example, image classification, image search engines (also known as content-based image retrieval, or CBIR), simultaneous localization and mapping (SLAM), and image segmentation, to name a few, have all been changed since the latest resurgence in neural networks and deep learning. 2015 ), SSD ( Fei-Fei et al.,

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Explosion

MAY 12, 2016

The library gives access to a line of neural network parsing models published by Google researchers over the last two years. A parallel line of work that achieves equivalent accuracy using LSTM models instead of feed-forward networks was published at the same time as the first SyntaxNet paper. How big is the advance?

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The MLOps Blog

NOVEMBER 30, 2022

Interestingly, the mathematical concept of neural networks existed for a long time, but it is only now that training a model with billions of parameters has become possible. Starting from AlexNet with 8 layers in 2012 to ResNet with 152 layers in 2015 – the deep neural networks have become deeper with time.

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ML Metadata Machine Learning Software Development 52

The Stanford AI Lab Blog

OCTOBER 13, 2021

3730–3738, 2015. ↩ Shiori Sagawa, Pang Wei Koh, Tatsunori B. Distributionally robust neural networks for group shifts: On the importance of regularization for worst-case generalization. SelectiveNet: A deep neural network with an integrated reject option. Selective classification for deep neural networks.

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Neural Network Machine Learning Computational Linguistics Deep Learning 40

Viso.ai

MARCH 12, 2024

Today’s boom in computer vision (CV) started at the beginning of the 21 st century with the breakthrough of deep learning models and convolutional neural networks (CNN). proposed a deep convolutional neural network architecture codenamed Inception. Find the SURF paper here. Find the VGG paper here.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Deep Learning 52

Mlearning.ai

MARCH 9, 2023

2015; Huang et al., 2015), which consists of 20 object categories with varying levels of complexity. 2015) to generate adversarial examples for each image. Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al.,

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Computer Vision Deep Learning Machine Learning Algorithm 52

Viso.ai

MAY 7, 2024

However, GoogLeNet demonstrated by using the inception module that depth and width in a neural network could be increased without exploding computations. GooLeNet – source Historical Context The concept of Convolutional Neural Networks ( CNNs ) isn’t new. We will investigate the inception module in depth.

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Explainability Neural Network Convolutional Neural Networks Deep Learning 52

NVIDIA

DECEMBER 4, 2023

An AI model, also called a neural network, is essentially a mathematical lasagna, made from layer upon layer of linear algebra equations. The latest GPUs include Tensor Cores that are 60x more powerful than the first-generation designs for processing the matrix math neural networks use.

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AWS Machine Learning Blog

MAY 15, 2023

Getir was founded in 2015 and operates in Turkey, the UK, the Netherlands, Germany, France, Spain, Italy, Portugal, and the United States. Algorithm Selection Amazon Forecast has six built-in algorithms ( ARIMA , ETS , NPTS , Prophet , DeepAR+ , CNN-QR ), which are clustered into two groups: statististical and deep/neural network.

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Neural Network Convolutional Neural Networks Metadata Data Scientist 68

Viso.ai

FEBRUARY 27, 2024

Since its inception in 2015, the YOLO (You Only Look Once) object-detection algorithm has been closely followed by tech enthusiasts, data scientists, ML engineers, and more, gaining a massive following due to its open-source nature and community contributions. The proposed PGI mechanism can be applied to deep neural networks of various sizes.

Neural Network 52

Neural Network Computer Vision Convolutional Neural Networks Python 52

Mlearning.ai

JUNE 16, 2023

Practitioners first trained a Convolutional Neural Network (CNN) to perform image classification on ImageNet (i.e. Instance-Aware Semantic Segmentation via Multi-task Network Cascades.” December 14, 2015. April 14, 2015. January 29, 2015. pre-training). fine-tuning). December 10, 2016. June 17, 2019.

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Convolutional Neural Networks Computer Vision AI AI 52

Viso.ai

DECEMBER 3, 2023

Hence, rapid development in deep convolutional neural networks (CNN) and GPU’s enhanced computing power are the main drivers behind the great advancement of computer vision based object detection. Various two-stage detectors include region convolutional neural network (RCNN), with evolutions Faster R-CNN or Mask R-CNN.

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Convolutional Neural Networks Computer Vision Neural Network Deep Learning 98

AWS Machine Learning Blog

APRIL 25, 2024

It uses neural networks like BERT to measure semantic similarity beyond just exact word or phrase matching. Hurricane Patricia has been rated as a categor… Human: 23 October 2015 Last updated at 17:44 B… [{‘name’: meteor’, “value’: 0.102339181286549.

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Unite.AI

OCTOBER 27, 2023

For example, multimodal generative models of neural networks can produce such images, literary and scientific texts that it is not always possible to distinguish whether they are created by a human or an artificial intelligence system.

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Explosion

MAY 10, 2016

By late 2015 I had the machine learning, hash table, outer parsing loop, and most of the feature extraction as nogil functions. When we finally switch over to a neural network model, the considerations will be a little bit different. But the state object had a complicated interface, and was implemented as a cdef class.

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Python NLP Auto-complete Neural Network 40

Explosion

NOVEMBER 21, 2019

In 2016 we trained a sense2vec model on the 2015 portion of the Reddit comments corpus, leading to a useful library and one of our most popular demos. Try the new interactive demo to explore similarities and compare them between 2015 and 2019 sense2vec (Trask et. Interestingly, “to ghost” wasn’t very common in 2015.

NLP 52

NLP Convolutional Neural Networks Neural Network Natural Language Processing 52

Lexalytics

APRIL 5, 2021

This book effectively killed off interest in neural networks at that time, and Rosenblatt, who died shortly thereafter in a boating accident, was unable to defend his ideas. (I Around this time a new graduate student, Geoffrey Hinton, decided that he would study the now discredited field of neural networks.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Viso.ai

DECEMBER 18, 2023

TensorFlow is an open-source software library for AI and machine learning with deep neural networks. TensorFlow was developed by Google Brain for internal use at Google and open-sourced in 2015. Edge intelligence , the ability to move deep learning tasks (object detection, image recognition, etc.) What is TensorFlow?

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