GTC 2020 --
NVIDIA today
announced the release of NVIDIA Jarvis, a GPU-accelerated
application framework that allows companies to use video and speech
data to build state-of-the-art conversational AI services
customized for their own industry, products and customers.
The shift toward working from home, telemedicine and remote
learning has created a surge in demand for custom, language-based
AI services, ranging from customer support to real-time
transcriptions and summarization of video calls to keep people
productive and connected.
Among the first companies to take advantage of Jarvis-based
conversational AI products and services for their customers are
Voca, an AI agent for call center support; Kensho, for automatic
speech transcriptions for finance and business; and Square, with
its virtual assistant for appointment scheduling.
“Conversational AI is central to the future of many industries,
as applications gain the ability to understand and communicate with
nuance and contextual awareness,” said Jensen Huang, founder and
CEO of NVIDIA. “NVIDIA Jarvis can help the healthcare, financial
services, education and retail industries automate their overloaded
customer support with speed and accuracy.”
Applications built with Jarvis can take advantage of innovations
in the new NVIDIA A100 Tensor Core GPU for AI computing and the
latest optimizations in NVIDIA TensorRT™ for inference. For the
first time, it’s now possible to run an entire multimodal
application, using the most powerful vision and speech models,
faster than the 300-millisecond threshold for real-time
interactions.
Jarvis provides a complete, GPU-accelerated software stack and
tools making it easy for developers to create, deploy and run
end-to-end, real-time conversational AI applications that can
understand terminology unique to each company and its
customers.
“IDC continues to see rapid growth within the conversational AI
market largely because organizations of all sizes are beginning to
realize the value of using well-trained virtual assistants and
chatbots to help service their customers and grow their
businesses,” said David Schubmehl, research director of AI Software
Platforms at IDC. “IDC expects worldwide spending on conversational
AI use cases like automated customer service agents and digital
assistants to grow from $5.8 billion in 2019 to $13.8 billion in
2023, a compound annual growth rate of 24 percent.”
To offer an interactive, personalized experience, companies need
to train their language-based applications on data that is specific
to their own product offerings and customer requirements. However,
building a service from scratch requires deep AI expertise, large
amounts of data and compute resources to train the models, and
software to regularly update models with new data.
Jarvis addresses these challenges by offering an end-to-end deep
learning pipeline for conversational AI. It includes
state-of-the-art deep learning models, such as NVIDIA’s Megatron
BERT for natural language understanding. Enterprises can further
fine-tune these models on their data using NVIDIA NeMo, optimize
for inference using TensorRT, and deploy in the cloud and at the
edge using Helm charts available on NGC, NVIDIA’s catalog of
GPU-optimized software.
Early Adopters — Voca, Kensho, Square
Companies worldwide are using NVIDIA’s conversational AI
platform to improve their services.
Voca’s AI virtual agents — which use NVIDIA for faster, more
interactive, human-like engagements — are used by Toshiba, AT&T
and other world-leading companies. Voca uses AI to understand the
full intent of a customer’s spoken conversation and speech. This
makes it possible for the agents to automatically identify
different tones and vocal clues to discern between what a customer
says and what a customer means. Additionally, using scalability
features built into NVIDIA’s AI platform, they can dramatically
reduce customer wait time.
“Low latency is critical in call centers and with NVIDIA GPUs
our agents are able to listen, understand and respond in under a
second with the highest levels of accuracy,” said Alan Bekker,
co-founder and CTO of Voca. “Now our virtual agents are able to
successfully handle 70-80 percent of all calls — ranging from
general customer service requests to payment transactions and
technical support.”
Kensho, the innovation hub for S&P Global located in
Cambridge, Mass., that deploys scalable machine learning and
analytics systems, has used NVIDIA’s conversational AI to develop
Scribe, a speech recognition solution for finance and business.
With NVIDIA, Scribe outperforms other commercial solutions on
earnings calls and similar financial audio in terms of accuracy by
a margin of up to 20 percent.
“We’re working closely with NVIDIA on ways to push end-to-end
automatic speech recognition with deep learning even further,” said
Georg Kucsko, head of AI research at Kensho. “By training new
models with NVIDIA, we’re able to offer higher transcription
accuracy for financial jargon compared to traditional approaches
that do not use AI, offering our customers timely information in
minutes versus days.”
Square has created an AI virtual assistant that allows Square
sellers to use AI to automatically confirm, cancel or change
appointments with their customers, and free themselves to conduct
more strategic customer engagement.
“Square Assistant can understand and provide help for 75 percent
of customer questions, along with ensuring that 10 percent more
people are showing up to their appointments,” said Gabor Angeli,
head of conversational AI at Square. “With GPUs, we’re able to
train models 10x faster versus CPUs to deliver more accurate,
human-like interactions, ultimately helping our customers grow
their businesses.”
AvailabilityAn early access program for NVIDIA
Jarvis is available to a limited number of applicants. Developers
interested in evaluating the application framework can sign up
here.
Additional Resources
- NVIDIA Video: Using Conversational AI in Enterprise
Applications
- Webinar: Training and Deploying Conversational AI Applications
with NeMo and Jarvis
- NVIDIA Developer Blog: Introducing Jarvis: Framework for
GPU-Accelerated Conversational AI Applications
- NVIDIA Developer Blog: Jumpstart Training for Speech
Recognition Models in Different Languages with NeMo
- NVIDIA Developer Blog: NVIDIA NeMo: Fast Development of Speech
and Language Models
- NVIDIA Developer Blog: State-of-the-Art Language Modeling Using
Megatron on A100
About NVIDIANVIDIA‘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/.
Media Contact:Kristin UchiyamaSenior PR
Managerkuchiyama@nvidia.com+1-408-313-0448
Certain statements in this press release including, but not
limited to, statements as to: the benefits, performance and
features of our products and technologies, including NVIDIA Jarvis,
NVIDIA TensorRT, and NVIDIA A100 GPU; what Jarvis helps enable and
allows companies to offer, including custom AI services and
real-time transcriptions; the companies using Jarvis;
conversational AI being central to the future of many industries;
NVIDIA Jarvis enabling organizations to serve millions, improve
customer satisfaction and support growing needs in industries;
growth in the conversational AI market and its causes; the
expectation for spending on conversational AI in the future; the
requirements to offer language-based applications and how Jarvis
addresses those challenges; enterprises being able to fine tune
their models using NVIDIA products and technologies; how Voca,
Kensho and Square use NVIDIA’s platform and AI and its benefits and
performance; and the availability of NVIDIA Jarvis 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.
© 2020 NVIDIA Corporation. All rights reserved. NVIDIA, the
NVIDIA logo and TensorRT are trademarks and/or registered
trademarks of NVIDIA Corporation in the U.S. and 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.
A photo accompanying this announcement is available at
https://www.globenewswire.com/NewsRoom/AttachmentNg/a0012ec3-847a-4c4b-a490-f4ea8f5cc881
NVIDIA (NASDAQ:NVDA)
과거 데이터 주식 차트
부터 6월(6) 2024 으로 7월(7) 2024
NVIDIA (NASDAQ:NVDA)
과거 데이터 주식 차트
부터 7월(7) 2023 으로 7월(7) 2024