Generative AI Associate

Innodata has opened a motion-capture laboratory in New Jersey designed to generate training data for humanoid robots and validate their performance. The facility features Vicon optical tracking cameras that measure movement with sub-millimetre accuracy, capturing 3D motion directly rather than inferring it from 2D video. The lab addresses the shortage of high-quality training data for physical AI systems. It can produce custom motion-capture data packages and evaluate robots sent by customers, providing independent verification of their movements and responses. According to CEO Rahul Singhal, physical AI is the fastest-growing segment in artificial intelligence, but development teams face constraints due to limited real-world interaction data. The facility offers end-to-end capabilities from data collection through model evaluation. Customers can purchase off-the-shelf data packages or commission bespoke projects, with the lab able to retarget motion data across different robotic platforms.

Innodata opens motion-capture AI lab to help humanoids move like humans. * 3 hrs ago Lab features Vicon optical motion capture cameras to measure subtle movements with sub-millimeter accuracy NEW YORK, NY / ACCESS Newswire / September 30, 2026 / Innodata Inc. (Nasdaq:INOD) today announced the opening of a new R&D laboratory that is designed to generate the data needed to train the next generation of human-like robots and independently validate the performance data that robots generate internally. Innodata developed the lab in collaboration with Vicon, a leader in motion capture who consulted on the lab design and continues to provide technical consulting. The New Jersey-based lab is equipped with high-precision, low-latency infrared optical tracking cameras that measure movement down to the sub-millimeter level-a degree of accuracy that methods such as wearable inertial measurement unit (IMU) sensors and single-camera (monocular) video analysis typically cannot match. The lab addresses an urgent need for high-quality training data for humanoids, industrial robots, and other forms of physical AI. While many other data providers infer 3D motion by analyzing 2D video, Innodata captures 3D data directly, from the bodies themselves-whether those bodies are human or mechanical. "There's just no substitute for direct 3D motion capture," said Frank Tanner, vice president of robotics and physical AI at Innodata. "When a computer vision model tries to make sense of a 2D grid of pixels, mistakes inevitably creep in. Our sensors are designed to register the tiniest motion of every joint, which makes training more accurate and efficient. When you're training a humanoid that weighs almost 200 pounds, your readings can't be in the ballpark. They need to be precise. And with this lab, they are." "Plenty of motion capture companies have discovered humanoid robotics lately. But the teams building the most capable robots keep reaching the same conclusion: if the training data is approximate, the robot will be too," said Andrew Knox, managing director of Vicon. "Vicon sets the standard that motion data is measured against. Our systems capture people, robots and the objects they handle in the same space, with sub-millimeter accuracy and millisecond latency. That gives you independent ground truth, not an estimate. It's why the leading humanoid developers, frontier AI labs and research universities keep choosing Vicon, and why Innodata's lab is well placed to become a reference point for the whole physical AI industry." Innodata customers will be able to purchase motion-capture data as off-the-shelf packages, or commission custom projects. Innodata can produce training data for a wide range of physical AI platforms and retarget motion data from one platform to another as needed. Customers can also send in robots for evaluation, to confirm they perform to customer specifications. Innodata's lab experts can measure a robot's movements and responses in a variety of scripted scenarios, including those in which robots and people interact. Because the lab's calibrated cameras observe each robot from the outside, they provide an external ("exocentric") check on the robot's internal ("egocentric") telemetry, which is often noisy. The resulting measurements can be used to validate a developer's internal data reports or performance claims or to provide independent, third-party benchmarks for trust and safety. The motion-capture lab is an important addition to Innodata's physical AI practice, which supports robotics programs across the full data lifecycle. Its work includes end-to-end real-world data capture and training data production spanning humanoids, human-operated hardware, wearable systems, sensor rigs, Universal Manipulator Interface (UMI) grippers, and other multimodal capture set-ups, as well as evaluation and safety-assurance services that validate robot performance. Innodata's physical AI experts apply the same rigorous, multi-stage quality processes the company has honed over decades of delivering premium data for mission-critical use cases in finance, government and healthcare and, more recently, for frontier AI labs. "Physical AI is growing faster than any other segment in AI, but every robotics team hits the same wall: there isn't enough real-world interaction data, and what exists is expensive and slow to produce," said Innodata CEO Rahul Singhal. "This facility removes that wall. We now offer physical AI companies a complete end-to-end capability - from data collection through model evaluation - that compresses development cycles and gets more capable, safer robots into the world sooner." About Innodata Innodata (Nasdaq:INOD) is a global data engineering company. Mycarrollcountynews believe that data and Artificial Intelligence (AI) are inextricably linked. Its mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. Mycarrollcountynews provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, Mycarrollcountynews honor its 36+ year legacy delivering the highest quality data and outstanding outcomes for its customers. Forward-Looking Statements This press release may contain certain forward-looking statements within the meaning of Section 21E of the Securities Exchange Act of 1934, as amended, and Section 27A of the Securities Act of 1933, as amended. These forward-looking statements include, without limitation, statements concerning its operations, economic performance, financial condition, developmental program expansion, and position in the AI services market. Words such as "project," "forecast," "believe," "expect," "can," "continue," "could," "intend," "may," "should," "will," "anticipate," "indicate," "guide," "predict," "likely," "estimate," "plan," "potential," "possible," "promises," or the negatives thereof, and other similar expressions generally identify forward-looking statements. These forward-looking statements are based on management's current expectations, assumptions and estimates and are subject to a number of risks and uncertainties, including, without limitation, impacts resulting from ongoing geopolitical conflicts; anticipated and actual use cases and outcomes; investments in large language models; that contracts may be terminated by customers; projected or committed volumes of work may not materialize; pipeline opportunities and customer discussions which may not materialize into work or expected volumes of work; the likelihood of continued development of the AI markets, particularly new and emerging markets, that its services support; the ability and willingness of its customers and prospective customers to execute business plans that give rise to requirements for its services; continuing reliance on project-based work and the primarily at-will nature of such contracts and the ability of these customers to reduce, delay or cancel projects; potential inability to replace projects that are completed, canceled or reduced; revenue concentration among a limited number of customers; its dependency on third-party providers and partners; its ability to achieve revenue and growth targets; difficulty in integrating and deriving synergies from acquisitions, joint ventures and strategic investments; potential undiscovered liabilities of companies and businesses that Mycarrollcountynews may acquire; potential impairment of the carrying value of goodwill and other acquired intangible assets of companies and businesses that Mycarrollcountynews acquire; a continued downturn in or depressed market conditions; changes in external market factors; the potential effects of U.S. global trade and monetary policy, including the interest rate policies of the Federal Reserve; changes in its business or growth strategy; the emergence of new, or growth in existing competitors; various other competitive and technological factors; its use of and reliance on information technology systems, including potential security breaches, cyber-attacks, privacy breaches or data breaches that result in the unauthorized disclosure of consumer, customer, employee or company information, or service interruptions; and other risks and uncertainties indicated from time to time in its filings with the Securities and Exchange Commission ("SEC"). Its actual results could differ materially from the results referred to in any forward-looking statements. Factors that could cause or contribute to such differences include, but are not limited to, the risks discussed in Part I, Item 1A. "Risk Factors," Part II, Item 7. "Management's Discussion and Analysis of Financial Condition and Results of Operations," and other parts of its Annual Report on Form 10-K, filed with the SEC on February 26, 2026, and in the other filings that Mycarrollcountynews may make with the SEC. In light of these risks and uncertainties, there can be no assurance that the results referred to in any forward-looking statements will occur, and you should not place undue reliance on these forward-looking statements. These forward-looking statements speak only as of the date hereof. Mycarrollcountynews undertake no obligation to update or review any guidance or other forward-looking statements, whether as a result of new information, future developments or otherwise, except as may be required by the U.S. federal securities laws. Company Contact Aneesh Pendharkar (201) 371-8000 Media Contact Maura Lafferty Firebrand Communications for Innodata (415) 848-9175 View the original on ACCESS Newswire Media gallery

Innodata opens motion-capture AI lab that aims to help humanoids move like humans. Features Vicon optical motion-capture cameras to measure subtle movements with sub-millimeter accuracy. By Robotics 24/7 Staff September 30, 2026 Innodata's new motion-capture AI lab in New Jersey features Vicon optical motion-capture cameras to measure subtle movements with sub-millimeter accuracy to generate data that will train the next generation of humanoid robots. Stay up-to-date with news and resources you need to do your job. Research industry trends, compare companies and get weekly market intelligence with Robotics 24/7. Global data engineering company Innodata announced the opening of a new R&D laboratory designed to generate the data needed to train the next generation of human-like robots and independently validate the performance data that robots generate internally. Innodata said that it developed the lab in collaboration with Vicon, a provider of motion capture technology, which consulted on the lab design and continues to provide technical consulting. Generating data to help humanoids perform more human-like movement. Innodata said that the New Jersey-based lab is equipped with high-precision, low-latency infrared optical tracking cameras that measure movement down to the sub-millimeter level, a degree of accuracy that methods such as wearable inertial measurement unit (IMU) sensors and single-camera (monocular) video analysis typically cannot match. "There's just no substitute for direct 3D motion capture," said Frank Tanner, vice president of robotics and physical AI at Innodata. "When a computer vision model tries to make sense of a 2D grid of pixels, mistakes inevitably creep in. Our sensors are designed to register the tiniest motion of every joint, which makes training more accurate and efficient. When you're training a humanoid that weighs almost 200 pounds, your readings can't be in the ballpark. They need to be precise. And with this lab, they are." The company said that the lab addresses an urgent need for high-quality training data for humanoids, industrial robots and other forms of physical AI. While many other data providers infer 3D motion by analyzing 2D video, Innodata said it captures 3D data directly, from the bodies themselves, whether those bodies are human or mechanical. "Plenty of motion capture companies have discovered humanoid robotics lately. But the teams building the most capable robots keep reaching the same conclusion: if the training data is approximate, the robot will be too," said Andrew Knox, managing director of Vicon. "Vicon sets the standard that motion data is measured against. Our systems capture people, robots and the objects they handle in the same space, with sub-millimeter accuracy and millisecond latency. That gives you independent ground truth, not an estimate. It's why the leading humanoid developers, frontier AI labs and research universities keep choosing Vicon, and why Innodata's lab is well placed to become a reference point for the whole physical AI industry." Innodata customers can utilize the new R&D lab. Innodata said that its customers can purchase motion-capture data as off-the-shelf packages, or commission custom projects. Innodata added that it can produce training data for a wide range of physical AI platforms and retarget motion data from one platform to another as needed. "Physical AI is growing faster than any other segment in AI, but every robotics team hits the same wall: there isn't enough real-world interaction data, and what exists is expensive and slow to produce," said Rahul Singhal, CEO of Innodata. "This facility removes that wall. We now offer physical AI companies a complete end-to-end capability - from data collection through model evaluation - that compresses development cycles and gets more capable, safer robots into the world sooner." The company said that customers can also send in robots for evaluation to confirm they perform to customer specifications. Innodata said that its lab experts can measure a robot's movements and responses in a variety of scripted scenarios, including those in which robots and people interact. Because the lab's calibrated cameras observe each robot from the outside, the company said that it can provide an external ("exocentric") check on the robot's internal ("egocentric") telemetry, which is often noisy. Innodata said that the resulting measurements can be used to validate a developer's internal data reports or performance claims or to provide independent, third-party benchmarks for trust and safety. Latest in camera. Latest in artificial intelligence. Latest robotics news.