NVIDIA today announced breakthroughs in language understanding that
allow businesses to engage more naturally with customers using
real-time conversational AI.
NVIDIA's AI platform is the first to train one of the most
advanced AI language models -- BERT -- in less than an hour and
complete AI inference in just over 2 milliseconds. This
groundbreaking level of performance makes it possible for
developers to use state-of-the-art language understanding for
large-scale applications they can make available to hundreds of
millions of consumers worldwide.
Early adopters of NVIDIA's performance advances include
Microsoft and some of the world's most innovative startups, which
are harnessing NVIDIA's platform to develop highly intuitive,
immediately responsive language-based services for their
customers.
Limited conversational AI services have existed for several
years. But until this point, it has been extremely difficult for
chatbots, intelligent personal assistants and search engines to
operate with human-level comprehension due to the inability to
deploy extremely large AI models in real time. NVIDIA has addressed
this problem by adding key optimizations to its AI platform -
achieving speed records in AI training and inference and building
the largest language model of its kind to date.
"Large language models are revolutionizing AI for natural
language," said Bryan Catanzaro, vice president of Applied Deep
Learning Research at NVIDIA. "They are helping us solve
exceptionally difficult language problems, bringing us closer to
the goal of truly conversational AI. NVIDIA's groundbreaking work
accelerating these models allows organizations to create new,
state-of-the-art services that can assist and delight their
customers in ways never before imagined."
Fastest Training, Fastest Inference, Largest
ModelAI services powered by natural language understanding
are expected to grow exponentially in the coming years. Digital
voice assistants alone are anticipated to climb from 2.5 billion to
8 billion within the next four years, according to Juniper
Research. Additionally, Gartner predicts, by 2021, 15% of all
customer service interactions will be completely handled by AI, an
increase of 400% from 2017.1
Helping lead this new era, NVIDIA has fine-tuned its AI platform
with key optimizations that have resulted in three new natural
language understanding performance records:
- Fastest training: Running the large version of
one of the world's most advanced AI language models --
Bidirectional Encoder Representations from Transformers (BERT) --
an NVIDIA DGX SuperPOD™ using 92 NVIDIA DGX-2H™ systems running
1,472 NVIDIA V100 GPUs slashed the typical training time for
BERT-Large from several days to just 53 minutes. Additionally,
NVIDIA trained BERT-Large on just one NVIDIA DGX-2 system in 2.8
days - demonstrating NVIDIA GPUs' scalability for conversational
AI.
- Fastest inference: Using NVIDIA T4 GPUs
running NVIDIA TensorRT™, NVIDIA performed inference on the
BERT-Base SQuAD dataset in only 2.2 milliseconds - well under the
10-millisecond processing threshold for many real-time
applications, and a sharp improvement from over 40 milliseconds
measured with highly optimized CPU code.
- Largest model: With a focus on developers'
ever-increasing need for larger models, NVIDIA Research built and
trained the world's largest language model based on Transformers,
the technology building block used for BERT and a growing number of
other natural language AI models. NVIDIA's custom model, with 8.3
billion parameters, is 24 times the size of BERT-Large.
Ecosystem AdoptionHundreds of developers
worldwide are already using NVIDIA's AI platform to advance their
own language understanding research and create new services.
Microsoft Bing is using the power of its Azure AI platform and
NVIDIA technology to run BERT and drive more accurate search
results.
"Microsoft Bing relies on the most advanced AI models and
computing platform to deliver the best global search experience
possible for our customers," said Rangan Majumder, group program
manager, Microsoft Bing. "In close collaboration with NVIDIA, Bing
further optimized the inferencing of the popular natural language
model BERT using NVIDIA GPUs, part of Azure AI infrastructure,
which led to the largest improvement in ranking search quality Bing
deployed in the last year. We achieved two times the latency
reduction and five times throughput improvement during inference
using Azure NVIDIA GPUs compared with a CPU-based platform,
enabling Bing to offer a more relevant, cost-effective, real-time
search experience for all our customers globally."
Several startups in NVIDIA's Inception program, including Clinc,
Passage AI and Recordsure, are also using NVIDIA's AI platform to
build cutting-edge conversational AI services for banks, car
manufacturers, retailers, healthcare providers, travel and
hospitality companies, and more.
Clinc has made NVIDIA GPU-enabled conversational AI solutions
accessible to more than 30 million people globally through a
customer roster that includes leading car manufacturers, healthcare
organizations and some of the world's leading financial
institutions, including Barclays, USAA and Turkey's largest bank,
Isbank.
"Clinc's leading AI platform understands complex questions and
transforms them into powerful, actionable insights for the world's
leading brands," said Jason Mars, CEO of Clinc. "The breakthrough
performance that NVIDIA's AI platform provides has allowed us to
push the boundaries of conversational AI and deliver revolutionary
services that help our customers use technology to engage with
their customers in powerful, more meaningful ways."
Optimizations Available TodayNVIDIA has made
the software optimizations used to accomplish these breakthroughs
in conversational AI available to developers:
- NVIDIA GitHub BERT training code with PyTorch *
- NGC model scripts and check-points for TensorFlow
- TensorRT optimized BERT Sample on GitHub
- Faster Transformer: C++ API, TensorRT plugin, and
TensorFlow OP
- MXNet Gluon-NLP with AMP support for BERT (training and
inference)
- TensorRT optimized BERT Jupyter notebook on AI Hub
- Megatron-LM: PyTorch code for training massive Transformer
models
*NVIDIA’s implementation of BERT is an optimized version of the
popular Hugging Face repo
Additional Resources
- NVIDIA video: What’s Next in Conversational AI
- NVIDIA Developer Blog: NVIDIA Clocks World’s Fastest BERT
Training Time and Largest Transformer Based Model Ever, Paving Path
For Advanced Conversational AI
- NVIDIA Developer Blog: Real-Time Natural Language Understanding
with BERT using TensorRT
- NVIDIA Applied Deep Learning Blog: MegatronLM: Training
Billion+ Parameter Language Models Using GPU Model Parallelism
Keep Current on NVIDIASubscribe to the NVIDIA
blog, follow us on Facebook, Twitter, LinkedIn and Instagram, and
view NVIDIA videos on YouTube and images on Flickr.
About NVIDIA NVIDIA‘s (NASDAQ: NVDA) invention
of the GPU in 1999 sparked the growth of the PC gaming market,
redefined modern computer graphics and revolutionized parallel
computing. More recently, GPU deep learning ignited modern AI — the
next era of computing — with the GPU acting as the brain of
computers, robots and self-driving cars that can perceive and
understand the world. More information at
http://nvidianews.nvidia.com/.
For further information, contact:Kristin
BrysonPR DirectorNVIDIA
Corporation+1-203-241-9190kbryson@nvidia.com
Certain statements in this press release including, but not
limited to, statements as to: NVIDIA achieving real-time
breakthroughs in language understanding enabling real-time
conversational AI and allowing businesses to engage more naturally
with customers using real-time AI; the performance, impact and
benefit of NVIDIA’s technologies, NVIDIA’s AI platform and BERT;
NVIDIA’s AI platform making it possible for developers to use
language understanding for large-scale applications that they can
make available to consumers worldwide; early adopters harnessing
NVIDIA’s platform to develop highly intuitive, responsive
language-based services for their customers; NVIDIA achieving speed
records in AI training and inference and building the largest
language model of its kind to date; large language models
revolutionizing AI for natural language, helping to solve language
problems, and bringing us closer to conversational AI; NVIDIA’s
work accelerating models to create services that can assist
customers in ways never before imagined; the expectation that AI
services using natural language growing exponentially; the expected
growth of digital voice assistants and the predicted growth of
customer service interactions to be handled by AI; hundreds of
developers using NVIDIA’s AI platform to advance their research and
create new services; Microsoft Bing using NVIDIA technology to run
BERT and drive more accurate search results; NVIDIA and Microsoft
collaborating to optimize Bing, and its benefits, impact and
performance; startups using NVIDIA’s AI platform to build
cutting-edge AI services; NVIDIA’s AI platform allowing Clinc to
push the boundaries of conversation AI and deliver revolutionary
services that help customers and engage them in new ways; and the
availability of NVIDIA’s code for BERT optimizations are
forward-looking statements that are subject to risks and
uncertainties that could cause results to be materially different
than expectations. Important factors that could cause actual
results to differ materially include: global economic conditions;
our reliance on third parties to manufacture, assemble, package and
test our products; the impact of technological development and
competition; development of new products and technologies or
enhancements to our existing product and technologies; market
acceptance of our products or our partners’ products; design,
manufacturing or software defects; changes in consumer preferences
or demands; changes in industry standards and interfaces;
unexpected loss of performance of our products or technologies when
integrated into systems; as well as other factors detailed from
time to time in the most recent reports NVIDIA files with the
Securities and Exchange Commission, or SEC, including, but not
limited to, its annual report on Form 10-K and quarterly reports on
Form 10-Q. Copies of reports filed with the SEC are posted on the
company’s website and are available from NVIDIA without charge.
These forward-looking statements are not guarantees of future
performance and speak only as of the date hereof, and, except as
required by law, NVIDIA disclaims any obligation to update these
forward-looking statements to reflect future events or
circumstances.
© 2019 NVIDIA Corporation. All rights reserved. NVIDIA, the
NVIDIA logo, NVIDIA DGX, NVIDIA DGX SuperPOD and TensorRT are
trademarks and/or registered trademarks of NVIDIA Corporation in
the U.S. and/or other countries. Other company and product names
may be trademarks of the respective companies with which they are
associated. Features, pricing, availability, and specifications are
subject to change without notice.
Photos accompanying this announcement are available at:
https://www.globenewswire.com/NewsRoom/AttachmentNg/de7e142e-a107-405b-a3a9-332d5a1afd33
https://www.globenewswire.com/NewsRoom/AttachmentNg/57a01fb6-4bbc-48c6-98d8-b59c862acda0
A video accompanying this announcement is available at:
https://www.globenewswire.com/NewsRoom/AttachmentNg/47a4da55-e11b-4cf2-9424-909941cf556b
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