Marktechpost

JULY 17, 2023

What Relationship Exists Between Predictive Analytics, Deep Learning, and Artificial Intelligence? For machine learning to identify common patterns, large datasets must be processed. Deep learning is a branch of machine learning frequently used with text, audio, visual, or photographic data.

Machine Learning 98

Machine Learning Data Mining Data Scientist Data Science 98

Towards AI

JULY 21, 2023

Photo by Will Truettner on Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher | 07.26.20 Last Updated on July 21, 2023 by Editorial Team Author(s): Ricky Costa Originally published on Towards AI. Primus The Liber Primus is unsolved to this day.

NLP 98

NLP Natural Language Processing Inference Engine Chatbots 98

Pickl AI

JULY 24, 2024

” During this time, researchers made remarkable strides in natural language processing, robotics, and expert systems. Notable achievements included the development of ELIZA, an early natural language processing program created by Joseph Weizenbaum, which simulated human conversation.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Natural Language Processing Neural Network 52

Lexalytics

APRIL 5, 2021

They were not wrong: the results they found about the limitations of perceptrons still apply even to the more sophisticated deep-learning networks of today. And indeed we can see other machine learning topics arising to take their place, like “optimization” in the mid-’00s, with “deep learning” springing out of nowhere in 2012.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Mlearning.ai

MARCH 9, 2023

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., 2012; Otsu, 1979; Long et al., 2019) proposed a novel adversarial training framework for improving the robustness of deep learning-based segmentation models.

Deep Learning 52

Deep Learning Computer Vision Machine Learning Algorithm 52

AWS Machine Learning Blog

FEBRUARY 12, 2025

This concept is similar to knowledge distillation used in deep learning, except that were using the teacher model to generate a new dataset from its knowledge rather than directly modifying the architecture of the student model. The following diagram illustrates the overall flow of the solution. Yiyue holds a Ph.D.

LLM 75

LLM Generative AI Deep Learning Data Scarcity 75

Heartbeat

AUGUST 21, 2023

AlexNet is a more profound and complex CNN architecture developed by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton in 2012. AlexNet significantly improved performance over previous approaches and helped popularize deep learning and CNNs. It has eight layers, five of which are convolutional and three fully linked.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Natural Language Processing Deep Learning 52

NVIDIA

FEBRUARY 11, 2025

That work inspired researchers who created BERT and other large language models , making 2018 a watershed moment for natural language processing, a report on AI said at the end of that year. This chart highlights the exponential growth in training compute requirements for notable machine learning models since 2012.

Neural Network 54

Neural Network Large Language Models Robotics BERT 54

Explosion

SEPTEMBER 3, 2015

Natural Language Processing moves fast, so maintaining a good library means constantly throwing things away. The new, awesome deep-learning model is there, but so are lots of others. But most Natural Language Processing libraries do, and it’s terrible. The new models supercede the old ones.

Natural Language Processing 40

Natural Language Processing NLP Python Deep Learning 40

Topbots

JANUARY 11, 2023

Neural Networks and Deep Learning algorithms, combined with synthetic data, are near to the current frontier in artificial intelligence (AI). These tools are becoming increasingly effective to provide new insights into natural systems. Enjoy this article? Sign up for more AI research updates.

Generative AI 40

Generative AI Explainability Deep Learning Neural Network 40

Viso.ai

JANUARY 2, 2024

This early model set the stage for future developments by demonstrating the usefulness of CNNs in processing visual data using feature maps – source. In 2012, the AlexNet architecture, designed by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton , marked a breakthrough in the ImageNet challenge by significantly reducing error rates.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Data Scarcity 52

Unite.AI

JANUARY 9, 2024

Apple prioritizes computer vision , natural language processing , voice recognition, and healthcare to enhance its products. Google focuses on expanding AI in search, advertising, cloud, healthcare, and education, with a particular emphasis on deep learning.

Natural Language Processing 147

Natural Language Processing Computer Vision Robotics AI 147

Bugra Akyildiz

AUGUST 10, 2024

Articles Quantization in deep learning refers to the process of reducing the precision of the numbers used to represent the model's parameters and activations. Typically, deep learning models use 32-bit floating-point numbers (float32) for computations. million per year in 2014 currency) in Shanghai.

BERT 59

BERT Large Language Models Categorization Deep Learning 59

AWS Machine Learning Blog

SEPTEMBER 11, 2024

in 2012 is now widely referred to as ML’s “Cambrian Explosion.” Thirdly, the presence of GPUs enabled the labeled data to be processed. Together, these elements lead to the start of a period of dramatic progress in ML, with NN being redubbed deep learning. Work by Hinton et al.

ML 112

ML Deep Learning Algorithm Large Language Models 112

Unite.AI

SEPTEMBER 26, 2024

It all started in 2012 with AlexNet, a deep learning model that showed the true potential of neural networks. Then, in 2015, Google released TensorFlow, a powerful tool that made advanced machine learning libraries available to the public. The necessary hardware, software, and data storage costs were very high.

AI 147

AI AI Neural Network Data Quality 147

Viso.ai

DECEMBER 21, 2023

Solidifying this influence, Koller received the Time’s 100 Most Influential People recognition in 2012. His doctoral thesis studied the design of convolutional/recurrent neural networks and their applications across computer vision, natural language processing, and their intersections.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

AWS Machine Learning Blog

NOVEMBER 15, 2024

of persons present’ for the sustainability committee meeting held on 5th April, 2012? 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.

Auto-complete 107

Auto-complete ML Python Machine Learning 107

AWS Machine Learning Blog

OCTOBER 11, 2024

For example: Data such as images, text, and audio need to be represented in a structured and efficient manner Understanding the semantic similarity between data points is essential in generative AI tasks like natural language processing (NLP), image recognition, and recommendation systems As the volume of data continues to grow rapidly, scalability (..)

Metadata 105

Metadata Generative AI LLM Data Ingestion 105

Viso.ai

MARCH 29, 2024

Modern Structured Knowledge: The term “knowledge graph” came into popularity in 2012 following its adoption by Google’s search engine, highlighting a knowledge fusion framework known as the Knowledge Vault (Google Knowledge Graph) for constructing large-scale knowledge graphs. within text data.

ML 40

ML Deep Learning NLP BERT 40