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RNNs

Last updated May 21, 2025, generated by Sumble

What is RNNs?

Recurrent Neural Networks (RNNs) are a class of neural networks designed to process sequential data. Unlike feedforward networks, RNNs have feedback connections, allowing them to maintain a 'memory' of past inputs. This makes them well-suited for tasks like natural language processing, speech recognition, and time series analysis, where the order of data points is crucial. They are commonly used for machine translation, text generation, and video analysis.

Find 713 organizations using RNNs on Sumble →

What other technologies are related to RNNs?

RNNs Competitor Technologies

CNNs

Convolutional Neural Networks are often used as alternatives to RNNs, especially in tasks involving spatial data, though they can also be applied to sequential data.

Transformers

Transformers are a competing architecture for sequence modeling, often outperforming RNNs in tasks like machine translation and text generation due to their parallel processing capabilities and ability to capture long-range dependencies.

BERT

BERT (Bidirectional Encoder Representations from Transformers) is a transformer-based model that competes with RNNs in NLP tasks, often providing superior performance.

Transformer models

Transformer models are a competing architecture for sequence modeling, often outperforming RNNs in tasks like machine translation and text generation due to their parallel processing capabilities and ability to capture long-range dependencies.

GPT

GPT (Generative Pre-trained Transformer) is a transformer-based model that competes with RNNs in NLP tasks, often providing superior performance.

ARIMA

ARIMA (Autoregressive Integrated Moving Average) models are traditional time series forecasting methods that can be considered competitors to RNNs in certain applications.

Number of organizations that mention technology

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RNNs Complementary Technologies

LSTMs

Long Short-Term Memory networks are a specific type of RNN architecture that addresses the vanishing gradient problem and are used extensively within the RNN framework.

LSTM

Long Short-Term Memory networks are a specific type of RNN architecture that addresses the vanishing gradient problem and are used extensively within the RNN framework.

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Which job functions commonly mention RNNs?

Applied Scientist

0.4% of all Applied Scientist jobs mention RNNs

View 43 jobs on Sumble

Machine Learning

0.3% of all Machine Learning jobs mention RNNs

View 356 jobs on Sumble

AI Engineer

0.3% of all AI Engineer jobs mention RNNs

View 259 jobs on Sumble

Data Scientist

0.2% of all Data Scientist jobs mention RNNs

View 559 jobs on Sumble

Data, Analytics & Machine Learning

0.1% of all Data, Analytics & Machine Learning jobs mention RNNs

View 1.2k jobs on Sumble

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Which organizations are mentioning RNNs?

Ford Motor Company

Manufacturing

HSBC

Finance and Insurance

Arizona State University

Educational Services

1 teams
mentions RNNs

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1 person
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**RNNs**

What is RNNs?

What other technologies are related to RNNs?

RNNs Competitor Technologies

RNNs Complementary Technologies

Which job functions commonly mention RNNs?

Which organizations are mentioning RNNs?

Find the right accounts, contact, message, and time to sell

RNNs