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GTC ON-DEMAND

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Abstract:
We'll talk about how we're applying deep learning to weather forecasting at Weather News, one of the world's largest forecasting companies. We're now able to provide Japanese TV news shows with AI-generated weather information, and we plan to expand elsewhere in Asia. We'll explain how we used TensorFlow on an NVIDIA DGX-2 machine and innovative learning model to add measurement results and increase accuracy of our forecaster. We'll also talk about how we're creating new learning models with TensorRT on the DGX-2. We'll touch on other potential uses for our weather technology in settings such as autonomous cars and solar power plants.
We'll talk about how we're applying deep learning to weather forecasting at Weather News, one of the world's largest forecasting companies. We're now able to provide Japanese TV news shows with AI-generated weather information, and we plan to expand elsewhere in Asia. We'll explain how we used TensorFlow on an NVIDIA DGX-2 machine and innovative learning model to add measurement results and increase accuracy of our forecaster. We'll also talk about how we're creating new learning models with TensorRT on the DGX-2. We'll touch on other potential uses for our weather technology in settings such as autonomous cars and solar power plants.  Back
 
Topics:
Climate, Weather & Ocean Modeling, Advanced AI Learning Techniques
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9164
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Abstract:

To convert phonemes of telephone conversations and responses at meetings into texts in real time, pass the text to the computational model created by DGX-1, label with a learning without teacher, and add the clusters, we are developing a system which compares objects and analyzes meaning of conversation and profiles of interlocutors. With this technology, customers can receive appropriate responses at the beginning of a conversation with a help desk, and patients can receive correspondence during a remote diagnosis with a doctor based solely off of their dialogue and examination results. By using TensorFlow as a platform and running the K-Means method, Word2vec, Doc2Vec, etc. in DGX-1 clustered environment on DGX-1, the result of arithmetic processing is found at high speed conversation. Even if the amount of sentences is increased, the learning effect increases linearly, demonstrating that the proportion of validity can be raised without taking grammar of languages ??other than English (e.g. Japanese) into account.

To convert phonemes of telephone conversations and responses at meetings into texts in real time, pass the text to the computational model created by DGX-1, label with a learning without teacher, and add the clusters, we are developing a system which compares objects and analyzes meaning of conversation and profiles of interlocutors. With this technology, customers can receive appropriate responses at the beginning of a conversation with a help desk, and patients can receive correspondence during a remote diagnosis with a doctor based solely off of their dialogue and examination results. By using TensorFlow as a platform and running the K-Means method, Word2vec, Doc2Vec, etc. in DGX-1 clustered environment on DGX-1, the result of arithmetic processing is found at high speed conversation. Even if the amount of sentences is increased, the learning effect increases linearly, demonstrating that the proportion of validity can be raised without taking grammar of languages ??other than English (e.g. Japanese) into account.

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Topics:
AI & Deep Learning Research, Speech & Language Processing, AI Startup
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8371
Streaming:
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