Marek Rei

JANUARY 2, 2018

Venues First, let’s look at different publication venues between 2012-2017. Most other venues are also growing rapidly, with 2017 being the biggest year ever for ICML, ICLR, EMNLP, EACL and CoNLL. NAACL and COLING were notably missing from 2017, but we can look forward to both of them in 2018. That’s it for 2017.

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Marktechpost

APRIL 6, 2024

in 2017, marking a departure from the previous reliance on recurrent neural networks (RNNs) and convolutional neural networks (CNNs) for processing sequential data. This includes the weights of the neural network layers and the parameters of the attention mechanisms.

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Towards AI

MARCH 4, 2024

Long before Attention, Recurrent Neural Networks (RNNs) could handle entire sentences, processing them word by word in order and giving a meaningful output based on the task at hand. For instance, if it’s about translation, it would take an English sentence and turn it into Spanish.

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Marktechpost

MARCH 25, 2024

These models use deep learning techniques, particularly neural networks, to process and produce text that mimics human-like understanding and responses. LLMs Core: Transformer Architecture The transformer architecture, introduced in 2017, is at the core of LLMs. What are Large Language Models?

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Towards AI

MARCH 4, 2024

Long before Attention, Recurrent Neural Networks (RNNs) could handle entire sentences, processing them word by word in order and giving a meaningful output based on the task at hand. For instance, if it’s about translation, it would take an English sentence and turn it into Spanish.

Neural Network 87

Neural Network Large Language Models ChatGPT AI 87

AssemblyAI

MARCH 21, 2023

While AI systems like ChatGPT or Diffusion models for Generative AI have been in the limelight in the past months, Graph Neural Networks (GNN) have been rapidly advancing. And why do Graph Neural Networks matter in 2023? We find that the term Graph Neural Network consistently ranked in the top 3 keywords year over year.

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Towards AI

FEBRUARY 20, 2024

The state-of-the-art Natural Language Processing (NLP) models used to be Recurrent Neural Networks (RNN) among others. in their 2017 paper “Attention is All You Need,” Transformers revolutionized NLP by leveraging self-attention mechanisms, allowing the model to learn the relevance and context of all words in a sentence.

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NVIDIA

FEBRUARY 22, 2024

All eight authors of “ Attention Is All You Need ,” the seminal 2017 NeurIPS paper that introduced the trailblazing transformer neural network architecture will appear in person at GTC on a panel hosted by NVIDIA Founder and CEO Jensen Huang. Gomez, Lukasz Kaiser, and Illia Polosukhin.

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Towards AI

JUNE 6, 2023

unsplash Attention-based transformers have revolutionized the AI industry since 2017. Now it’s possible to have deep learning models with no limitation for the input size.

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Unite.AI

MAY 8, 2024

He began his career at Yandex in 2017, concurrently studying at the Yandex School of Data Analysis. The most crucial point during this process was when I learned about neural networks and deep learning. Alexandr Yarats is the Head of Search at Perplexity AI.

Machine Learning 298

Machine Learning Software Engineer Large Language Models Data Analysis 298

Marktechpost

MARCH 26, 2024

Existing IR systems heavily rely on models such as BM25, E5, and various neural network architectures, focusing primarily on enhancing semantic search capabilities through keyword-based queries and short sentences. FOLLOWIR integrates three TREC collections: TREC News 2021, TREC Robust 2004, and TREC Common Core 2017.

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Mlearning.ai

APRIL 8, 2023

Over the years, we evolved that to solving NLP use cases by adopting Neural Network-based algorithms loosely based on the structure and function of a human brain. The birth of Neural networks was initiated with an approach akin to structuring solving problems with algorithms modeled after the human brain.

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Viso.ai

DECEMBER 19, 2023

Today, the use of convolutional neural networks (CNN) is the state-of-the-art method for image classification. For example, in 2017, the Mask R-CNN algorithm was the fastest real-time object detector on the MS COCO benchmark, with an inference time of 330 ms per frame. How Does Image Classification Work?

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Convolutional Neural Networks Neural Network Computer Vision Deep Learning 98

Marktechpost

MARCH 20, 2024

The field has oscillated between Convolutional Neural Networks (CNNs) and Transformer-based architectures, each with unique strengths and limitations. In the evolving landscape of computer vision, the quest for models that adeptly navigate the tightrope between high accuracy and low computational cost has led to significant strides.

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Convolutional Neural Networks Computer Vision Neural Network AI 104

Unite.AI

NOVEMBER 8, 2023

Recurrent Neural Networks (RNNs) became the cornerstone for these applications due to their ability to handle sequential data by maintaining a form of memory. Functionality : Each encoder layer has self-attention mechanisms and feed-forward neural networks. However, RNNs were not without limitations.

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Towards AI

AUGUST 25, 2023

Deep learning (DL) is a subset of machine learning that uses neural networks which have a structure similar to the human neural system. Packt, ISBN: 978–1787125933, 2017. O’Reilly Media, ISBN: 978–1491957660, 2017. In ML, there are a variety of algorithms that can help solve problems. 3, IEEE, 2014. Klein, and E.

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Software Engineer Machine Learning Neural Network Artificial Intelligence 96

Machine Learning Research at Apple

JUNE 19, 2023

2020) consider maps , where is an input convex neural network (ICNN), as defined by Amos et al. 2017, and fit with SGD using… To exploit that result, , Makkuva et al. 2020); Korotin et al.

Neural Network 40

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Marktechpost

SEPTEMBER 27, 2023

These neural network architectures, introduced in 2017, have revolutionized how machines understand and generate human language. Recent years have shown us how capable artificial neural networks have become in a variety of tasks. They changed the language tasks, vision tasks, etc. Time to meet the answer.

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Neural Network Artificial Intelligence Artificial Intelligence AI Researcher 82

Heartbeat

DECEMBER 14, 2023

is well known for his work on optical character recognition and computer vision using convolutional neural networks (CNN), and is a founding father of convolutional nets. in 1998, In general, LeNet refers to LeNet-5 and is a simple convolutional neural network. > Finished chain.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Deep Learning Computer Scientist 52

AssemblyAI

MARCH 15, 2023

." Advances in neural information processing systems 30 (2017). [3] "Contextnet: Improving convolutional neural networks for automatic speech recognition with global context." " Advances in neural information processing systems 33 (2020): 1877-1901. [8] 3] Burchi, Maxime, and Valentin Vielzeuf. "Efficient

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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. 2017 – Giant leap in image classification capability, over 95% accuracy in computer vision tasks is achieved. Their theoretically-best performance is also superior to regular neural networks.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 52

Heartbeat

JUNE 14, 2023

Introduction Deep neural network classifiers have been shown to be mis-calibrated [1], i.e., their prediction probabilities are not reliable confidence estimates. For example, if a neural network classifies an image as a “dog” with probability p , p cannot be interpreted as the confidence of the network’s predicted class for the image.

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Neural Network Computer Vision Deep Learning Explainability 59

NVIDIA

OCTOBER 31, 2023

the AI neural network recognizes a wide variety of scenes, producing high-quality preview images and drastically reducing time spent rendering scenes. I switched to NVIDIA graphics cards in 2017. With DLSS 3.5,

Neural Network 117

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Mlearning.ai

MAY 16, 2023

Deployment of deep neural network on mobile phone. (a) Introduction As more and more deep neural networks, like CNNs, Transformers, and Large Language Models (LLMs), generative models, etc., to boost the usages of the deep neural networks in our lives. 1], (d) image by Shiwa ID on Unsplash. 2] Android.

Neural Network 98

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Mlearning.ai

JULY 2, 2023

In natural language processing (NLP), the “Attention is All You Need” paper introduced a groundbreaking neural network architecture called the Transformer. Recurrent neural networks (RNNs) struggle with parallel computation due to sequential processing, and convolutional networks have fixed context windows.

Neural Network 52

Neural Network NLP Natural Language Processing Large Language Models 52

ODSC - Open Data Science

JUNE 9, 2023

The 1970s introduced bell bottoms, case grammars, semantic networks, and conceptual dependency theory. In the 90’s we got grunge, statistical models, recurrent neural networks and long short-term memory models (LSTM). It uses a neural network to learn the vector representations of words from a large corpus of text.

Natural Language Processing 52

Natural Language Processing ChatGPT Generative AI BERT 52

Towards AI

APRIL 8, 2024

Developed by researchers at Google in 2013 [1], Word2Vec leverages neural networks to learn dense vector representations of words, capturing their semantic and contextual relationships. million unique users, capturing listens across 25 million unique songs gathered between 2017 and 2023.

Natural Language Processing 68

Natural Language Processing NLP Neural Network Algorithm 68

Bugra Akyildiz

DECEMBER 10, 2023

It uses a graph neural network (GNN) to model the relationships between different weather variables. degree resolution, 13 pressure levels) pre-trained on ERA5 data from 1979 to 2017 and fine-tuned on HRES data from 2016 to 2021. This allows it to capture complex relationships that traditional models cannot.

Neural Network 52

Neural Network Prompt Engineer Prompt Engineering ChatGPT 52

Heartbeat

DECEMBER 8, 2023

is well known for his work on optical character recognition and computer vision using convolutional neural networks (CNN), and is a founding father of convolutional nets. in 1998, In general, LeNet refers to LeNet-5 and is a simple convolutional neural network.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Deep Learning LLM 52

Mlearning.ai

MAY 8, 2023

A comprehensive step-by-step guide with data analysis, deep learning, and regularization techniques Introduction In this article, we will use different deep-learning TensorFlow neural networks to evaluate their performances in detecting whether cell nuclei mass from breast imaging is malignant or benign. This model has 2 hidden layers.

Neural Network 52

Neural Network Deep Learning Machine Learning Data Analysis 52

TheSequence

NOVEMBER 22, 2023

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. 💥 Miscellaneous – a set of rapid-fire questions What is your favorite area of research outside of generative AI?

Neural Network 40

Neural Network Generative AI AI AI 40

Viso.ai

JANUARY 16, 2024

Artificial Neural Networks (ANNs) are the cornerstone of modern artificial intelligence (AI). This diagram showcases how various layers interact in a neural network – source. Over the 5 years between 2017-2021, AI patent grants grew on average by 18.2% Case Background: Emotional Perception AI Ltd v.

Neural Network 52

Neural Network Computer Vision Categorization Algorithm 52

Towards AI

JULY 20, 2023

That’s great news for researchers who often work on SLRs because the traditional process is mind-numbingly slow: An analysis from 2017 found that SLRs take, on average, 67 weeks to produce. Over the past several years, researchers have increasingly attempted to improve the data extraction process through various ML techniques. dollars apiece.

Data Extraction 82

Data Extraction NLP Natural Language Processing Automation 82

NVIDIA

OCTOBER 31, 2023

the AI neural network recognizes a wide variety of scenes, producing high-quality preview images and drastically reducing time spent rendering scenes. I switched to NVIDIA graphics cards in 2017. With DLSS 3.5,

Neural Network 52

Neural Network AI AI 52

Mlearning.ai

MAY 12, 2023

Deployment of deep neural network on mobile phone. (a) NCNN (Neural Network Computing Library) NCNN is a high-performance neural network inference framework developed by Tencent, which is designed specifically for mobile and embedded devices [2]. 2] Tencent, Neural Network Computer Vision, [link] , 2019. [3]

Neural Network 52

Neural Network Deep Learning Computer Vision Large Language Models 52

Flipboard

MAY 17, 2023

You wrote a famous article in 2017, “ The Seven Deadly Sins of AI Prediction. “ Convolutional neural networks being able to label regions of an image. So there’s a case where AI, convolutional neural networks—which, by the way, applied to vision is 10 years old—is going to make a difference.

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Large Language Models Robotics Convolutional Neural Networks Neural Network 182

Heartbeat

MARCH 14, 2023

Some of the methods used for scene interpretation include Convolutional Neural Networks (CNNs) , a deep learning-based methodology, and more conventional computer vision-based techniques like SIFT and SURF. Additional resources: Adrian, R. Deep learning for computer vision with Python.

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