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Synthesis AI Raises a $17 Million Series A To Expand Its Synthetic Data Platform for Computer Vision AI

Led by 468 Capital, the investment will drive team and product growth to further establish Synthesis AI as the leader in synthetic data

SAN FRANCISCO, April 28, 2022 /PRNewswire/ — Synthesis AI, a pioneer in synthetic data technologies to build advanced computer vision AI models, today announced it has closed $17 million in Series A financing led by new investor 468 Capital, with additional participation from Sorenson Ventures and Strawberry Creek Ventures and existing investors, Bee Partners, PJC, iRobot Boom Capital and Kubera Venture Capital.

The latest round brings Synthesis AI’s total funding to over $24 million. The new funds will allow Synthesis AI to grow its world-class team and introduce new products to enable companies to build more advanced computer vision models faster. The company also plans to expand research surrounding the intersection of CGI and AI with a focus on neural rendering, mixed training (real and synthetic), and modeling of complex human behavior.

“Synthesis AI is uniquely positioned to win in the emerging synthetic data space. The breadth and depth of Synthesis AI’s platform, the quality of the team, and the extensive list of Fortune 50 customers firmly establish Synthesis AI as a category leader, ” states Florian Leibert, partner at 468 Capital. “We are excited to support Synthesis AI as they push forward their vision to transform how AI models are fundamentally developed.”

Synthesis AI’s leading technology and proven customer traction with leading AI and technology companies were critical to the company’s successful round. The company has a track record of innovation and, over the last year, the company recorded several noteworthy firsts in the industry. The company released the first book on synthetic data, produced the first white paper surrounding facial analysis with synthetic data, published the first industry survey, and launched the first self-serve product (HumanAPI) in the space that has delivered well over 10 million generated images.

Accelerating Company Momentum

The Series A financing follows the launch of OpenSynthetics, the first dedicated community for creating and using synthetic data in AI/ML and computer vision with centralized access to synthetic datasets, research, papers, and code. Through OpenSynthetics, AI/ML practitioners, regardless of experience, can share tools and techniques for creating and using synthetic data to build more capable AI models and work to power the next generation of computer vision.

Additionally, Synthesis AI is expanding its HumanAPI solution to support the development of advanced digital humans, with new functionalities for pose estimation, action recognition, and high-density landmarks. The new capabilities enable advanced applications in the metaverse, Augmented Reality (AR), Virtual Reality (VR), and others in generated media, home & enterprise security, and AI fitness.

“Last year was a momentous year, and we’re excited to continue growing our teams and products with the support of our terrific investors,” said Yashar Behzadi, CEO of Synthesis AI. “Synthetic data is at an inflection point of adoption, and our goal is to develop the technology further and drive a paradigm change in how computer vision systems are built. The industry will soon fully design and train computer vision models in virtual worlds enabling for more advanced and ethical AI.”

Synthesis AI was recently recognized as #4 in Fast Company‘s prestigious global list of the most innovative small companies and as one of the top 10 breakthrough technologies of 2022 by MIT Technology Review.

To learn more about Synthesis AI, visit https://synthesis.ai/

About Synthesis AISynthesis AI, a San Francisco-based technology company, is pioneering the use of synthetic data to build more capable and ethical computer vision models. Through a proprietary combination of generative neural networks and cinematic CGI pipelines, Synthesis’ platform can programmatically create vast amounts of perfectly-labeled image data at orders of magnitude increased speed and reduced cost compared to current approaches. Synthesis AI’s customers include Fortune 500 technology, AR/VR/metaverse, automobile, teleconferencing, and AI companies.

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Synthesis AI Raises a $17 Million Series A To Expand Its Synthetic Data Platform for Computer Vision AI

Led by 468 Capital, the investment will drive team and product growth to further establish Synthesis AI as the leader in synthetic data

SAN FRANCISCO, CA, April 26, 2022 – Synthesis AI, a pioneer in synthetic data technologies to build advanced computer vision AI models, today announced it has closed $17 million in Series A financing led by new investor 468 Capital, with additional participation from Sorenson Ventures and Strawberry Creek Ventures and existing investors, Bee Partners, PJC, iRobot Boom Capital and Kubera Venture Capital.

The latest round brings Synthesis AI’s total funding to over $24 million. The new funds will allow Synthesis AI to grow its world-class team and introduce new products to enable companies to build more advanced computer vision models faster. The company also plans to expand research surrounding the intersection of CGI and AI with a focus on neural rendering, mixed training (real and synthetic), and modeling of complex human behavior. 

“Synthesis AI is uniquely positioned to win in the emerging synthetic data space. The breadth and depth of Synthesis AI’s platform, the quality of the team, and the extensive list of Fortune 50 customers firmly establish Synthesis AI as a category leader, “ states Florian Leibert, partner at 468 Capital. “We are excited to support Synthesis AI as they push forward their vision to transform how AI models are fundamentally developed.”

Synthesis AI’s leading technology and proven customer traction with leading AI and technology companies were critical to the company’s successful round. The company has a track record of innovation and, over the last year, the company recorded several noteworthy firsts in the industry. The company released the first book on synthetic data, produced the first white paper surrounding facial analysis with synthetic data, published the first industry survey, and launched the first self-serve product (HumanAPI) in the space that has delivered well over 10 million generated images.

Accelerating Company Momentum

The Series A financing follows the launch of OpenSynthetics, the first dedicated community for creating and using synthetic data in AI/ML and computer vision with centralized access to synthetic datasets, research, papers, and code. Through OpenSynthetics, AI/ML practitioners, regardless of experience, can share tools and techniques for creating and using synthetic data to build more capable AI models and work to power the next generation of computer vision. 

Additionally, Synthesis AI is expanding its HumanAPI solution to support the development of advanced digital humans, with new functionalities for pose estimation, action recognition, and high-density landmarks. The new capabilities enable advanced applications in the metaverse, Augmented Reality (AR), Virtual Reality (VR), and others in generated media, home & enterprise security, and AI fitness.

“Last year was a momentous year, and we’re excited to continue growing our teams and products with the support of our terrific investors,” said Yashar Behzadi, CEO of Synthesis AI. “Synthetic data is at an inflection point of adoption, and our goal is to develop the technology further and drive a paradigm change in how computer vision systems are built. The industry will soon fully design and train computer vision models in virtual worlds enabling for more advanced and ethical AI.”

Synthesis AI was recently recognized as #4 in Fast Company’s prestigious global list of the most innovative small companies and as one of the top 10 breakthrough technologies of 2022 by MIT Technology Review. 

To learn more about Synthesis AI, visit https://synthesis.ai/.  

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About Synthesis AI 

Synthesis AI, a San Francisco-based technology company, is pioneering the use of synthetic data to build more capable and ethical computer vision models. Through a proprietary combination of generative neural networks and cinematic CGI pipelines, Synthesis’ platform can programmatically create vast amounts of perfectly-labeled image data at orders of magnitude increased speed and reduced cost compared to current approaches. Synthesis AI’s customers include Fortune 500 technology, AR/VR/metaverse, automobile, teleconferencing, and AI companies. 

Media Contact

Laura Kubitz, Merritt Group

850.865.1038 synthesis.ai@merrittgrp.com

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Synthesis AI CEO and Founder Featured in NVIDIA GTC 2022 Panel on Synthetic Data

Yashar Behzadi to be featured in a panel covering synthetic data business strategy across industries featuring experts from Microsoft, NVIDIA, and Ford

SAN FRANCISCO, March 22, 2022 /PRNewswire/ — Synthesis AI, a pioneer in synthetic data technologies, today announced its founder and CEO Yashar Behzadi, will be featured in a panel at NVIDIA GTC 2022 alongside other distinguished experts from Microsoft, NVIDIA, and Ford.

The panel titled “Why Synthetic Data is Important for Your Business: Strategies and Implementations Across Industries” will focus on 3D synthetic data generation spanning partners and customers and will showcase the underlying value of Omniverse for high-fidelity, accurate data generation across different use cases and industries. The panel will take place on March 24 from 12:00 – 12:50 p.m. EDT.

Behzadi will appear alongside other synthetic data experts including:

Rev Lebaredian, VP Omniverse & Simulation Technology, NVIDIAGerard Andrews, Product Marketing, NVIDIAPedro Urbina, Software Developer Manager, MicrosoftNikita Jaipuria, Technical Expert – AI Based Modeling For DAT, FordGil Elbaz, CTO and Co-founder, Datagen

“I am honored to share my expertise alongside such distinguished industry leaders,” said Behzadi. “Sharing our collective experiences and knowledge will help accelerate the understanding and adoption of synthetic data across industries, which is the ultimate goal. The adoption of synthetic data is at an inflection point, but there is still work to be done to educate across use cases and establish more resources to help develop a knowledge base and understanding on ways synthetic data can reduce bias, further democratize, and build more robust AI models.”

The virtual conference will take place March 21-24 and feature additional workshops, trainings, and programs from tech visionaries, business leaders, and peers who are using the latest advancements in AI and accelerated computing to solve their biggest challenges.

To attend the conference and watch the panel, click here.

About Synthesis AISynthesis AI, a San Francisco-based technology company, is pioneering the use of synthetic data to build more capable computer vision models. Through a proprietary combination of generative neural networks and cinematic CGI pipelines, Synthesis’ platform can programmatically create vast amounts of perfectly-labeled image data at orders of magnitude increased speed and reduced cost compared to current approaches.

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Synthesis AI Ranked #4 on Fast Company’s Annual List of the World’s Most Innovative Companies for 2022

The recognition emphasizes the company’s leading role in enabling the next generation of AI systems with synthetic data and simulation technologies. 

SAN FRANCISCO, CA, March 8, 2022 – Synthesis AI, a pioneer in synthetic data technologies, ranked number four on Fast Company’s prestigious annual list of the World’s Most Innovative Companies for 2022. This ranking cements Synthesis AI’s role in pioneering synthetic data technologies to create more capable AI models. Synthetic data is a disruptive approach to training AI models through the use of computer-generated images and simulations.  Synthesis AI’s on-demand platform provides vast amounts of perfectly labeled 3D data. The company’s clients include leading technology, robotics, metaverse, smartphone, and autonomy companies.

“We are at an inflection point of utilization for synthetic data,” said Yashar Behzadi, CEO and founder of Synthesis AI. “Every day, more companies are adopting synthetic data approaches to build better models at a fraction of the time and cost of traditional human-labeling methods. With synthetic data, data practitioners can generate the data they need on-demand, ensuring robust and unbiased model performance. Moreover, synthetic data provides never-before-available 3D labels necessary to build new models for robotics, autonomy, and metaverse applications.” 

“Many thanks to Fast Company for recognizing Synthesis AI as a leader in synthetic data. The recognition is a great validation of the emerging role of synthetic data to the future of AI development,” continued Behzadi.

In addition to the recognition by Fast Company, Synthesis AI was also recently listed by MIT Technology Review as one of the Breakthrough Technologies of 2022.

From Startup to Global Innovator 

Synthesis AI emerged out of stealth in 2021 with its unique and disruptive approach to training AI models.  In the last year, Synthesis AI has spearheaded the effort to introduce synthetic data to the world. Synthesis AI’s head of artificial intelligence published the first book on synthetic data. The company also published the first industry survey on the benefits of synthetic data and published the first white paper on the development of state-of-the-art facial models with synthetic data.  The company was also the first to release self-serve synthetic data products. Synthesis AI launched HumanAPI, enabling the programmatic generation of millions of unique, high-quality 3D digital humans. This announcement came just months after the launch of the FaceAPI synthetic data-as-a-service product, which has delivered over 10M labeled facial images for leading smartphone, teleconferencing, automobile, and technology companies.

Most recently, Synthesis AI announced enhanced capabilities to support the development of advanced digital humans, with new functionalities for pose estimation, action recognition, and high-density landmarks. The new capabilities enable advanced applications in the metaverse, Augmented Reality (AR), Virtual Reality (VR), and others in generated media, home & enterprise security, and AI fitness. The company plans to launch several new APIs in 2022 to address new use-cases in robotics and autonomy.

About Fast Company

“The world’s most innovative companies play an essential role in addressing the most pressing issues facing society, whether they’re fighting climate change by spurring decarbonization efforts, ameliorating the strain on supply chains, or helping us reconnect with one another over shared passions,” said Fast Company Deputy Editor David Lidsky.

For the second year in a row, to coincide with the issue launch, Fast Company will host its Most Innovative Companies Summit on April 26–27. The virtual, multi-day summit celebrates the Most Innovative Companies in business, and provides an early look at major business trends and an inside look at what it takes to innovate in 2022. Fast Company’s Most Innovative Companies issue (March/April 2022) is available online here, as well as in-app form via iTunes, and on newsstands beginning March 15. The hashtag is #FCMostInnovative.

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About Synthesis AI 

Synthesis AI, a San Francisco-based technology company, is pioneering the use of synthetic data to build more capable and ethical computer vision models. Through a proprietary combination of generative neural networks and cinematic CGI pipelines, Synthesis’ platform can programmatically create vast amounts of perfectly-labeled image data at orders of magnitude increased speed and reduced cost compared to current approaches. 

Media Contact

Laura Kubitz, Merritt Group

850.865.1038

synthesis.ai@merrittgrp.com

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Synthesis AI Launches HumanAPI to Create Millions of Photorealistic Digital Humans, On-Demand

The ability to create vast amounts of high-quality, labeled human images will enable more capable AI models needed to power the next generation of computer vision and metaverse applications.

SAN FRANCISCO, Nov. 9, 2021 /PRNewswire/ — Synthesis AI, a pioneer in synthetic data technologies, today released HumanAPI, a significant expansion of the company’s synthetic data capabilities enabling the programmatic generation of millions of unique, high-quality 3D digital humans. This announcement comes months after the launch of the FaceAPI synthetic data-as-a-service product, which has delivered over 10M labeled facial images for leading smartphone, teleconferencing, automobile, and technology companies. HumanAPI is the next step in the company’s journey to support advanced computer vision Artificial Intelligence (AI) applications.

“The ability to obtain accurate 3D labeled human data on-demand will fundamentally change the development of more sophisticated human AI models,” said Andrew Rabinovich, PhD and Headroom co-founder and CTO and former Head of AI for Magic Leap. “This is an important development in expanding the use of synthetic data across multiple use-cases and into new emerging technologies.” 

“HumanAPI is a natural evolution in our synthetic data roadmap. Now it is possible to produce photoreal 3D digital humans on-demand with programmatic control of facial appearance, body type, clothing, pose, and actions at an unprecedented scale. This functionality unlocks the ability to build new models for our existing smartphone, teleconferencing, and automobile customers,” said Yashar Behzadi, CEO and founder of Synthesis AI. “HumanAPI also enables all kinds of new opportunities for our customers, including smart AI assistants, virtual fitness coaches, and of course, the world of metaverse applications.”

By creating a digital double of the real world, the metaverse will enable new applications ranging from reimagined social networks, entertainment experiences, teleconferencing, gaming, and more. Computer vision AI will be fundamental to how the real world is captured and recreated with high-fidelity in the digital realm. Photorealistic, expressive, and behaviorally accurate humans will be an essential component of the metaverse. HumanAPI will be the first product to enable companies to create vast amounts of perfectly labeled whole-body data on-demand to build more capable AI models including pose estimation, emotion recognition, activity and behavior characterization, facial reconstruction, and more. 

The HumanAPI furthers Synthesis AI’s mission to create a new synthetic data paradigm to power the future of computer vision. A recent report commissioned by Synthesis AI and Vanson Bourne found that 89 percent of tech executives see synthetic data as a key to transforming their industry. In fact, 59 percent of industry leaders believe that their industry will utilize synthetic data in five years, either independently or in combination with ‘real-world’ data.

HumanAPI is available immediately. 

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Survey of Industry Leaders Shows Synthetic Data is Essential to Building More Capable AI Models

Executives believe that synthetic data is key to more efficiently and cost-effectively creating labeled training data.

SAN FRANCISCO, Sept. 15, 2021 /PRNewswire/ — Synthesis AI, a pioneer in synthetic data technologies, today released a new report in conjunction with Vanson Bourne, a global technology market research firm, highlighting how 89% of technology executives view synthetic data as a key emerging technology to creating more capable models, cutting the cost of data labeling, improving access to data, and reducing the time it takes to build AI models.

Industry leaders believe that, on average, 59% of their industry will utilize synthetic data in five years, either independently or in combination with ‘real-world’ data. This suggests that synthetic data will play an important role in the development of next-generation AI models.

The survey report, Adapt or Be Left Behind: 89 Percent of Tech Execs See Synthetic Data As a Key to Transforming Their Industry, is based on a survey of 100 senior technology executives on their perceptions of synthetic data, potential benefits and barriers of implementation, and what industry leaders think it will take to continue driving the adoption of synthetic data.

Synthetic data refers to computer-generated images and simulations used to train computer vision models. Synthetic data is emerging to be an essential element in building accurate and capable AI models, as it provides developers with vast amounts of perfectly labeled data on-demand.

“AI is driven by the amount, quality, and speed of training data. Synthetic training data is already making waves in several industries including autonomous vehicles and robotics. There is a critical need for more education on the underlying technology and benefits to drive broader industry adoption,” said Yashar Behzadi, CEO and founder of Synthesis AI. “Building core synthetic data capability will be the key to whether or not some companies adapt or fall behind in the future. Synthetic data has the potential to deliver perfectly labeled data on-demand, potentially cutting millions of dollars and months of work related to the current process of collecting, preparing, and manually labeling training data.”

Andy Thurai, Vice President and Principal Analyst at Constellation Research, said, “Today’s AI models are limited by real-world data for a couple of reasons – collecting real-world data is very expensive, and most companies don’t have the time and resources to collect the volume of data that is required to train models that the tech giants do. The survey results indicate synthetic data is a new market where there is a knowledge gap that needs to be addressed. A blend of the real world and synthetic data will provide the best combination that is impossible to match just by raw data collection. If a model can handle all possible scenarios based on assumptions, then it is ready for real-world scenarios.”

Synthetic data adoption is increasing, but a key to further adoption is enhanced understanding of this emerging technology across the board, all the way from the C-suite to machine learning engineers. Only half (51%) of the respondents were knowledgeable, state-of-the-art synthetic data approaches indicating a critical gap.

Respondents who were aware of recent advances in synthetic data expressed confidence in the technology’s ability to address key issues with current “real-world” data approaches. This indicates that if the knowledge gap is reduced, many more will likely see and understand synthetic data’s benefits.

Prominent barriers to synthetic data adoption are organizational knowledge and a slow buy-in from colleagues.

Other barriers to adoption included:

Concerns that models built with synthetic data are not as good as ‘real-world’ data (46%);Difficulty in creating high-quality synthetic data for complex systems (45%);The costs of integration and implementation (42%).

Recent advances in synthetic data are addressing the key identified barriers and the technology is predicted to be a significant enabler of the next generation of AI models.

Click here to download the report. To learn more about the company, visit https://synthesisaistg.wpengine.com.

About Synthesis AISynthesis AI, a San Francisco-based technology company, is pioneering the use of synthetic data to build more capable computer vision models. Through a proprietary combination of generative neural networks and cinematic CGI pipelines, Synthesis’ platform can programmatically create vast amounts of perfectly-labeled image data at orders of magnitude increased speed and reduced cost compared to current approaches.

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Synthesis AI’s Head of Artificial Intelligence Publishes The First Book on Synthetic Data for Deep Learning

Sergey Nikolenko explores fundamental computer vision problems, key synthetic data technologies, and future directions and applications 

SAN FRANCISCO, CA, August 10, 2021 – Synthesis AI, a pioneer in synthetic data technologies, today announced Springer has published the book Synthetic Data for Deep Learning written by Head of Artificial Intelligence (AI), Sergey Nikolenko. The book is available for purchase on Amazon and Springer.

Synthetic data refers to computer-generated images and simulations used to train computer vision models. Sergey Nikolenko is a computer scientist specializing in machine learning and the analysis of algorithms. In addition to his role at Synthesis AI, Nikolenko serves as the Head of the Artificial Intelligence Lab at the Steklov Mathematical Institute at St. Petersburg, Russia. His previous research includes works on cryptography, theoretical computer science, and algebra.

Synthetic Data for Deep Learning discusses fundamental computer vision problems, both low-level and high-level, synthetic environments and datasets for outdoor and urban scenes (i.e. autonomous driving), indoor scenes (i.e. indoor navigation), aerial navigation, and simulation environments for robotics. Additionally, it touches upon applications of synthetic data outside computer vision. Springer Publisher states, “This is the first book on synthetic data for deep learning, and its breadth of coverage may render this book as the default reference on synthetic data for years to come.” 

Serge Belongie, Professor, Department of Computer Science at the University of Copenhagen (DIKU) and Director, Pioneer Centre for Artificial Intelligence, said, “As deep learning finds its way into a rapidly growing array of real-world applications ranging from autonomous vehicles to telemedicine, the need for data to train ever-higher capacity models shows no signs of stopping. To meet that need, our field must tap into rich sources of synthetic and real data. Sergey’s book lucidly surveys the state of the art in the former, and I consider it required reading for any researcher using deep learning based methods.”

“The sheer pace — not to mention complexity — of machine learning and deep learning development is exponential in the world around us. I felt strongly that we needed a comprehensive text to look at the rise of synthetic data needed to prolong the exponential growth of machine learning in supervised learning problems, especially computer vision, and more,“ said Nikolenko. “Simply put, synthetic data is a way to prolong the march of progress in these fields. I hope this text can help educate, serve as a comprehensive reference for all aspects of synthetic data, and facilitate discussion and future research.” 

Coming out of stealth with $4.5M in funding in April 2021, Synthesis AI’s platform addresses industry needs by letting customers programmatically create vast amounts of perfectly labeled, unbiased image data enabling the development of more capable models. The company has since achieved the largest synthetic data set in the industry with 40K unique identities and delivered 10M labeled images from its FaceAPI product. Synthesis AI’s customers include top handset manufacturers, global technology companies, teleconferencing companies, and leading chipset and camera manufacturers. The company also recently announced enhanced capabilities to enable the development of driver safety monitoring systems and is already working with leading automobile manufacturers.

To learn more about the company, visit https://synthesisaistg.wpengine.com

About Synthesis AI 

Synthesis AI, a San Francisco-based technology company, is pioneering the use of synthetic data to build more capable computer vision models. Through a proprietary combination of generative neural networks and cinematic CGI pipelines, Synthesis’ platform can programmatically create vast amounts of perfectly-labeled image data at orders of magnitude increased speed and reduced cost compared to current approaches. 

Media Contact

Laura Kubitz, Merritt Group

850.865.1038

synthesis.ai@merrittgrp.com 

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Synthesis AI Announces Enhanced Synthetic Data Capabilities to Enable the Development of Driver Safety Monitoring Systems

The company’s labeled training data will enable automobile manufacturers to build computer vision systems to meet new driver safety regulatory requirements.

SAN FRANCISCO, July 27, 2021 /PRNewswire/ — Synthesis AI, a pioneer in synthetic data technologies, today announced enhanced capabilities to simulate driver behavior in the car cabin environment to ensure Automobile and Autonomous Vehicle (AV) manufacturers have access to high-quality, perfectly labeled training data to build driver safety systems. Through the company’s synthetic data-as-a-service FaceAPI solution, manufacturers can now test intelligent sensing configurations and driver safety monitoring systems across a broader set of environments and solutions without compromising customer privacy.

“For safe and general deployment of automobiles, especially AVs, Artificial Intelligence (AI) systems need to perceive the world reliably and make proper decisions across a wide range of situations,” said Yashar Behzadi, CEO of Synthesis AI. “With recent attention directed to driver monitoring systems to improve road safety, it’s inevitable that the demand for synthetic data and its simulation capabilities will only increase, as the technology is uniquely positioned to accelerate the development of driver safety and autonomous systems.”

Beginning in 2022, all new cars entering the EU market must be equipped with advanced safety systems. Among the mandatory safety measures is distraction recognition and alert systems on trucks and buses to warn when vulnerable road users, such as pedestrians or cyclists, are in close proximity.

To meet the new requirements, automobile companies will be faced with spending vast amounts of resources building and deploying cars to collect diverse datasets to train AI models. However, it is both costly and impractical to capture sufficient examples of diverse sets of drivers across a wide variety of situations. Synthetic data will play an increasingly important role in overcoming these bottlenecks.

Manufacturers will have the ability to mimic driver behavior in virtual car environments to test and iterate their models across a broader set of settings and situations without building and deploying fleets of vehicles. To meet the data demands of the in-cabin driver safety monitoring systems, Synthesis AI’s FaceAPI enables the on-demand generation of thousands of unique identities with granular control of emotion, gaze angle, head pose, accessories, environments, camera systems (e.g., RGB, NIR, TOF), and more. Since the data is generated, the image data comes with an expanded set of pixel-perfect labels, including facial landmarks, gaze, angle, depth maps, segmentation, surface normals, and facial meshes. As a result, automotive manufacturers will be able to build more robust training models in a fraction of the time and cost of traditional human-annotated real-world data approaches.

“The new EU regulations demonstrate the growing expectation for car manufacturers to have a comprehensive understanding of all the human variables that can impact road safety. Synthetic data will play an instrumental role in meeting this need,” said Dr. Rana el Kaliouby, Deputy CEO of Smart Eye, and former Co-Founder and CEO of Affectiva. “Our collaboration with Synthesis AI has allowed us to test our computer vision models with large sets of diverse data that are indicative of real-world use-cases. As a result, we’re able to deliver advanced driver monitoring and Interior Sensing systems that meet the requirements of automakers today and in the future.”

Synthesis AI, which works with automobile and autonomous vehicle manufacturers and tier-1 suppliers, is continually building capability to meet the future demands of manufacturers.

To learn more about the use of synthetic data to improve state-of-the-art facial models, download the white paper, Synthetic Data Case Studies: It Just Works.

About Synthesis AISynthesis AI, a San Francisco-based technology company, is pioneering the use of synthetic data to build more capable computer vision models. Through a proprietary combination of generative neural network and cinematic CGI pipelines, Synthesis’ platform can programmatically create vast amounts of perfectly-labeled image data at orders of magnitude increased speed and reduced cost compared to current approaches.

SOURCE Synthesis AI

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Synthesis AI Delivers 10 Millionth Labeled Image from its FaceAPI Product as Demand for Synthetic Data Surges

The milestone highlights the rapidly emerging role of synthetic data in AI

SAN FRANCISCO, CA, July 13, 2021 – Synthesis AI, a pioneer in synthetic data technologies, today announced their 10 millionth generated labeled image, a testament to the increasing demand for synthetic data to drive new AI models. The company’s first product, FaceAPI, is being leveraged by leading companies to build more capable facial models for smartphone facial verification, teleconferencing, driver monitoring and smart assistants. 

Synthesis AI’s unique API approach for synthetic data generation enables customers to create massive amounts of labeled data on-demand. The API empowers machine learning engineers to directly and effortlessly create data with an expanded set of pixel-perfect labels including dense facial landmarks, depth maps, surface normals, gaze, and sub-segmentation masks. As demonstrated by the milestone, Synthesis AI’s scalable cloud infrastructure can support production-level data generation. This announcement signals continued momentum as Synthesis AI recently announced a $4.5M funding round to add to its world-class R&D teams and continue leading the industry in the development of synthetic data technologies. Synthesis AI also recently released 40,000 unique high-resolution 3D facial models.

“Synthetic data solves fundamental cost, efficiency, and accuracy issues with today’s human-labeled data approaches,” said Yashar Behzadi, CEO and founder of Synthesis AI. “Traditionally, obtaining labeled facial images would cost about $3 an image for standard 2D landmarks. Instead, we are now able to produce images with never before labels such as depth maps, surface normals, dense 3D landmarks, gaze vectors, emotion, and more at a fraction of the cost and time. Once ML developers can generate labeled data on-demand through our simple FaceAPI, the ability to iterate and optimize model performance changes by orders of magnitude.” 

Synthetic data is a disruptive technology that will democratize access to high-quality training data, allowing companies of all sizes to create best-in-class models. Synthesis AI will be introducing new APIs in the coming months to service broader use-cases and industries. 

“This accomplishment is truly a testament to how Synthesis AI is setting the pace for synthetic data technology,” said Rob May, Partner at PJC. “We are excited to be supporting a true trailblazer putting a game-changing technology on the map.”

About Synthesis AI 

Synthesis AI, a San Francisco-based technology company, is pioneering the use of synthetic data to build more capable computer vision models. Through a proprietary combination of generative neural network and cinematic CGI pipelines, Synthesis’ platform can programmatically create vast amounts of perfectly-labeled image data at orders of magnitude increased speed and reduced cost compared to current approaches. 

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Synthesis AI Achieves Largest Synthetic Data Set in the Industry with 40,000 Unique Identities

The highly diverse computer vision training set reduces bias concerns by spanning genders, BMI, and ethnicities.

SAN FRANCISCO, June 9, 2021 /PRNewswire/ —Synthesis AI, a pioneer in synthetic data technologies, today announced they have released 40,000 unique high-resolution 3D facial models.  Through the company’s synthetic data-as-a-service FaceAPI solution, users can now programmatically create perfectly labeled image training data spanning 40,000 unique identities. Demonstrating Synthesis AI’s commitment to addressing ethical AI issues related to bias and privacy, this data set not only represents the largest collection of 3D facial models available anywhere, but also is the most diverse, spanning gender, ethnicity, age, and BMI.

“On the heels of our recent funding announcement, we are excited to continue this type of growth and momentum as a company,” said Yashar Behzadi, CEO of Synthesis AI. “Our goal is to address bias and privacy in AI and to democratize access to high-quality data. Making 40,000 unique identities available further strengthens this mission, while also addressing the technical, economic, and ethical issues with current approaches.”

The new capability will allow companies of any size to create high-performing and unbiased facial models with access to more robust data. Early customers include three of the top five handset manufacturers, leading teleconferencing companies, and global technology companies building the next generation of smart assistants.

By bringing together cinematic VFX pipelines and novel generative AI models, Synthesis AI is uniquely able to produce high-quality and diverse 3D models of faces. Each identity can be modified by near-infinite variability through the combination of emotion, head pose, hair, facial hair, accessories, environments, and camera attributes. Each image comes with associated pixel-perfect labels such as segmentation, facial landmarks, depth maps, surface normals, and more. The ability to create large diverse datasets has recently enabled leading handset manufacturers to develop improved facial verification systems that work with user mask wear across environments and camera angles.  Companies across industries and use-cases will be able to build more capable and less biased models, further solidifying Synthesis AI as a leader in synthetic data by providing more capabilities than competitors.

“Releasing a data set of this breadth and depth reflects Synthesis AI’s commitment to pushing the boundaries of computer vision,” said Dr. Rana el Kaliouby, Co-Founder and CEO of Affectiva. “Brands have a unique opportunity to address ethical AI issues related to bias and privacy and build better, more capable models. We’re proud to be working with Synthesis AI to pioneer synthetic data technologies that will strengthen and facilitate that trust.”About Synthesis AISynthesis AI, a San Francisco-based technology company, is pioneering the use of synthetic data to build more capable computer vision models. Through a proprietary combination of generative neural network and cinematic CGI pipelines, Synthesis’ platform can programmatically create vast amounts of perfectly-labeled image data at orders of magnitude increased speed and reduced cost compared to current approaches.

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Synthesis AI speaking at the MetaBeat conference on Oct 4th

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