Leading startup makes ‘needle-in-a-haystack’
video searches possible using natural language, turning the world’s
largest unsearchable data source—video—into a trove of accessible
information
Developers can now find specific movie scenes
from decades of video archives, or assess video footage of
athletes’ performances, with conversational queries
Twelve Labs uses AWS to train its multimodal
foundation models up to 10% faster, while reducing training costs
by more than 15%
At AWS re:Invent, Amazon Web Services, Inc. (AWS), an
Amazon.com, Inc. company (NASDAQ: AMZN), today announced that
Twelve Labs, a startup that uses multimodal artificial intelligence
(AI) to bring human-like understanding to video content, is
building and scaling its proprietary foundation models on AWS.
Twelve Labs will use AWS technologies to accelerate the development
of its foundation models that map natural language to what’s
happening inside a video. This includes actions, objects, and
background sounds, allowing developers to create applications that
can search through videos, classify scenes, summarize, and split
video clips into chapters.
Creating applications that can pinpoint any video moment or
frame
Available on AWS Marketplace, these foundation models enable
developers to create applications for semantic video search and
text generation, serving media, entertainment, gaming, sports, and
additional industries reliant on large volumes of video. For
example, sports leagues can use the technology to streamline the
process of cataloging vast libraries of game footage, making it
easier to retrieve specific frames for live broadcasts.
Additionally, coaches can use these foundation models to analyze a
swimmer’s stroke technique or a sprinter’s starting block position,
making adjustments that lead to better performance. Finally, media
and entertainment companies can use Twelve Labs technology to
create highlight reels from TV programs tailored to each viewer’s
interests, such as compiling all action sequences in a thriller
series featuring a favorite actor.
“Twelve Labs was founded on a vision to help developers build
multimodal intelligence into their applications,” said Jae Lee,
co-founder and CEO of Twelve Labs. “Nearly 80% of the world’s data
is in video, yet most of it is unsearchable. We are now able to
address this challenge, surfacing highly contextual videos to bring
experiences to life, similar to how humans see, hear, and
understand the world around us.”
“AWS has given us the compute power and support to solve the
challenges of multimodal AI and make video more accessible, and we
look forward to a fruitful collaboration over the coming years as
we continue our innovation and expand globally,” added Lee. “We can
accelerate our model training, deliver our solution safely to
thousands of developers globally, and control compute costs—all
while pushing the boundaries of video understanding and creation
using generative AI.”
Generating accurate and insightful video summaries and
highlights
Twelve Labs’ Marengo and Pegasus foundation models deliver
groundbreaking video analysis that not only provides text summaries
and audio translations in more than 100 languages, but also
analyzes how words, images, and sounds all relate to one other,
such as matching what’s said in speech to what’s shown in video.
Content creators can also access exact moments, angles, or events
within a show or game using natural language searches. For example,
major sports leagues use Twelve Labs technology on AWS to
automatically and rapidly create highlight reels from their
extensive media libraries to improve the viewing experience and
drive fan engagement.
“Twelve Labs is using cloud technology to turn vast volumes of
multimedia data into accessible and useful content, driving
improvements in a wide range of industries,” said Jon Jones, vice
president and global head of Startups at AWS. “Video is a treasure
trove of valuable information that has, until now, remained
unavailable to most viewers. AWS has helped Twelve Labs build the
tools needed to better understand and rapidly produce more relevant
content.”
Accelerating and lowering the cost of model training
Twelve Labs uses Amazon SageMaker HyperPod to train its
foundation models, which are capable of comprehending different
data formats like videos, images, speech, and text all at once.
This allows its models to unlock deeper insights compared to other
AI models focused on just one data type. The training workload is
split across multiple AWS compute instances working in parallel,
which means Twelve Labs can train their foundation models for weeks
or even months without interruption. Amazon SageMaker HyperPod
provides everything needed to get AI models up to speed quickly,
fine-tune their performance, and scale up operations
seamlessly.
Leveraging the scale of AWS to expand globally
As part of a three-year Strategic Collaboration Agreement (SCA),
Twelve Labs will work with AWS to deploy its advanced video
understanding foundation models across new industries and enhance
its model training capabilities using Amazon SageMaker Hyperpod.
AWS Activate, a program that helps startups grow their business,
has empowered Twelve Labs to scale its generative AI technology
globally and unlock deeper insights from hundreds of petabytes of
videos—down to split-second accuracy. This support includes
hands-on expertise for optimizing machine learning performance and
implementing go-to-market strategies. Additionally, AWS Marketplace
enables Twelve Labs to seamlessly deliver its innovative video
intelligence services to a global customer base.
About Amazon Web Services
Since 2006, Amazon Web Services has been the world’s most
comprehensive and broadly adopted cloud. AWS has been continually
expanding its services to support virtually any workload, and it
now has more than 240 fully featured services for compute, storage,
databases, networking, analytics, machine learning and artificial
intelligence (AI), Internet of Things (IoT), mobile, security,
hybrid, media, and application development, deployment, and
management from 108 Availability Zones within 34 geographic
regions, with announced plans for 18 more Availability Zones and
six more AWS Regions in Mexico, New Zealand, the Kingdom of Saudi
Arabia, Taiwan, Thailand, and the AWS European Sovereign Cloud.
Millions of customers—including the fastest-growing startups,
largest enterprises, and leading government agencies—trust AWS to
power their infrastructure, become more agile, and lower costs. To
learn more about AWS, visit aws.amazon.com.
About Amazon
Amazon is guided by four principles: customer obsession rather
than competitor focus, passion for invention, commitment to
operational excellence, and long-term thinking. Amazon strives to
be Earth’s Most Customer-Centric Company, Earth’s Best Employer,
and Earth’s Safest Place to Work. Customer reviews, 1-Click
shopping, personalized recommendations, Prime, Fulfillment by
Amazon, AWS, Kindle Direct Publishing, Kindle, Career Choice, Fire
tablets, Fire TV, Amazon Echo, Alexa, Just Walk Out technology,
Amazon Studios, and The Climate Pledge are some of the things
pioneered by Amazon. For more information, visit amazon.com/about
and follow @AmazonNews.
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