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TIER IV to showcase integrated AI, data, and computing solution for SDVs at Automotive World 2026

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TOKYO, Aug. 26, 2026 /PRNewswire/ — TIER IV, the pioneering force behind open-source software for autonomous driving, will showcase a solution for software-defined vehicles (SDVs) that integrates AI, data, and computing at Automotive World 2026, to be held at Makuhari Messe from September 9 to 11, 2026. As part of its exhibition, TIER IV will introduce the autolabeling function of its Co-MLOps platform, a data-sharing platform, as well as its reference E2E AI model, an end-to-end (E2E) autonomous driving AI model developed using data processed through the platform. The demonstration will run the reference E2E AI model on an automotive computer, showcasing an integrated SDV solution that covers the entire process, from data collection and processing to the development of the E2E autonomous driving AI model and its deployment on an automotive computing platform.

Toward the development of autonomous driving systems for passenger vehicles

As the use of AI in autonomous driving technology continues to advance rapidly, high-quality and diverse datasets with accurate labeling are becoming increasingly important for enabling AI to correctly interpret its surroundings. Equally important is an efficient framework for developing autonomous driving AI models using these datasets. To deploy autonomous driving AI models in mass-produced vehicles, including passenger vehicles, it is also essential to run these models efficiently on automotive computing platforms.

To accelerate the development of autonomous driving AI, TIER IV launched the Co-MLOps platform in January 2024 and has been working with partners to collect and share driving data. TIER IV is working toward an integrated SDV solution that combines AI, data, and computing by automatically labeling driving data collected through the platform, efficiently developing the E2E autonomous driving AI model using the labeled data, and establishing an environment for deploying the model on an automotive computing platform.

Key features of the autolabeling function

Using driving data as training data for autonomous driving AI models requires the collection of large volumes of driving data and accurate labeling to enable AI to correctly interpret the data. The autolabeling function automatically labels a wide range of objects and background elements in driving data, including vehicles, pedestrians, road surfaces and structures, so that they can be accurately recognized by AI.

The function can generate millions of labels instantly and with consistent quality, enabling efficient data processing even when new regions or sensors are added or the volume of data increases. By automating the enormous amount of labeling work that has traditionally been performed manually, the function is expected to reduce development costs and accelerate the development of autonomous driving AI models.

To improve the accuracy of autonomous driving AI models, TIER IV supplements difficult-to-collect driving data, such as rare scenarios directly associated with collision risks and data from adverse weather conditions, with synthetic data generated using NVIDIA Cosmos. The autolabeling function is also used to label this generated data.

For more details on the autolabeling function and the use of NVIDIA Cosmos to supplement driving data, please see TIER IV’s tech blog, Building a dataset foundation for autonomous driving with NVIDIA Cosmos.

Key features of the reference E2E AI model

The reference E2E AI model does not rely on high-definition maps and uses only images captured by automotive cameras to perform a range of functions, from a bird’s-eye-view understanding of the surrounding environment to trajectory generation, using a single neural network. The model supports 3D road and object recognition, the generation of occupancy maps that determine whether obstacles are present in each cell when the environment captured by camera images is divided into a grid, and vehicle trajectory prediction. Its architecture is also well suited to automotive computing, making it easier to deploy on actual system-on-chips.

The model is developed through an agentic AI-driven development process. Humans specify what to build, while an AI agent takes the lead in developing the E2E autonomous driving AI model, incorporating automatically labeled driving data, data transformation and cleansing, implementation optimization, and model management. The agent autonomously runs the cycle of training, evaluation, and improvement. By having agentic AI lead the development process, the model is designed to improve development efficiency and enable low-cost, rapid prototyping of autonomous driving AI models.

TIER IV is continuing to develop the reference E2E AI model and plans to make it available to partners participating in the Co-MLOps project.

Demonstration at Automotive World 2026

TIER IV will demonstrate technology that automatically labels various objects and background elements in driving data using the autolabeling function of the Co-MLOps platform. The demonstration will also run the reference E2E AI model, developed using the labeled driving data, on an NVIDIA Jetson Orin, where the model will use only images from automotive cameras to perform the entire process from a bird’s-eye-view understanding of the surrounding environment to trajectory generation.

By integrating large-scale driving data collection and processing through the platform with the continuous development and improvement of the E2E autonomous driving AI model and its deployment on the automotive computing platform, TIER IV is advancing the development of an SDV solution designed to support automakers and suppliers in the development of autonomous driving systems for mass production in passenger vehicles.

About TIER IV

TIER IV stands at the forefront of deep tech innovation, pioneering Autoware, open-source software for autonomous driving. With a comprehensive suite of platforms and services built around Autoware, TIER IV provides everything from software development and vehicle procurement to operational support. Through the Autoware ecosystem, TIER IV works with partners worldwide to shape the future of intelligent vehicles with open-source software, aiming to create mobility that is safer, more sustainable, and accessible to all.

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pr@tier4.jp 

The word marks and logos of TIER IV are trademarks or registered trademarks of TIER IV, Inc. in Japan and other countries. All other company names, product names, service names, and logos referenced herein are trademarks or registered trademarks of their respective owners.

Autoware is a registered trademark of the Autoware Foundation.

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SOURCE TIER IV, Inc.

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Consilient Expands Access to Federated AI-Powered Financial Crime Solutions in AWS Marketplace, Including for Use in AWS GovCloud (US)

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Consilient’s Federated AML and fraud detection, synthetic financial-crime data, SAR analysis, and open-source intelligence are now available through AWS Marketplace

WASHINGTON, Nov. 9, 2026 /PRNewswire/ — Consilient, the leading provider of federated AI-powered financial-crime discovery and detection technology, today announced that its solutions are now available in Amazon Web Services (AWS) Marketplace, including for use in AWS GovCloud (US). The offering provides financial institutions, fintechs, and U.S. government organizations with a streamlined way to discover, procure, and deploy Consilient’s capabilities through AWS Marketplace.

Customers now have access to Consilient’s Federated AI ecosystem and four complementary products:

Federated Learning Models and Exchange: Behavioral machine-learning models, deployed and shared through a secure federated network that continuously improve by learning across institutions and data sets, without any data moving or leaving the institution’s environment. Covering core anti-money laundering (AML) typologies and specific high-risk financial criminal and fraud activities, the Consilient models also surface hidden risks and emerging typologies that no single institution could detect alone.Federated Synthetic Data: Realistic, labeled examples of rare, emerging, and underrepresented financial-crime risks to support model development, evaluation, and improvement when historical cases and data are limited.SAR Analyzer: AI-assisted analysis of Suspicious Activity Report (SAR) narratives to connect related entities and cases, uncover recurring risk patterns, and turn investigative findings into reusable detection opportunities.OSINT Agent: Open-source and external intelligence on individuals, businesses, ownership, and relationships to help investigators assess risk with fuller context.

Customers can now deploy Consilient flexibly within their AWS environment, taking advantage of shared insights through Consilient’s federated exchange and capabilities while ensuring data remains local, secure, and private.

“Financial-crime teams need more effective and dynamic ways to find emerging risks without compromising sensitive data or adding unnecessary friction to procurement. In proven deployments at Tier-1 financial institutions, Consilient has improved efficiency by 75% and increased detection effectiveness by 4x, uncovering hidden risks that existing systems simply cannot see. Availability in AWS Marketplace makes it easier for financial institutions and government agencies to access these capabilities on a continuous basis, including our newer SAR Analyzer and Federated Synthetic Data products, within the secure, compliant infrastructure they require,”  Ajit Tharaken, Chief Executive Officer, Consilient.

Consilient’s availability in AWS GovCloud (US) reflects growing demand from U.S. government agencies and regulated institutions for financial-crime detection capabilities that meet the highest standards of security and compliance, areas where federated learning’s data-local architecture is a natural fit for cloud infrastructure.  Consilient allows for more dynamic public-private insight sharing and feedback without having to share or move data.

Consilient’s federated learning approach allows approved model updates and insights to strengthen detection across participating institutions without transferring the underlying customer data. Industry estimates suggest existing rules-based systems generate false positive rates of up to 98%, creating enormous operational overhead for compliance teams.  Consilient’s federated capabilities enable more efficient and effective risk discovery.

Consilient’s wider portfolio combines its federated approach with AI-assisted investigation, external intelligence, and synthetic data to address structural inefficiencies of current approaches and support the detection of complex, emerging financial-crime risks dynamically. Consilient’s solutions are now deployable within AWS infrastructure.

To learn more about Consilient’s offerings, visit Consilient.com or view its listing in AWS Marketplace at https://aws.amazon.com/marketplace/pp/prodview-3goaqbwjfiffo.

About Consilient
Consilient is the first company to apply federated AI for the detection and prevention of financial crime and fraud risk.  Consilient’s mission is to transform how the world prevents financial crime. 

Consilient enables financial institutions and regulators to transform financial crime detection by learning from patterns of behavior across institutions and borders, without ever sharing or moving data. Using federated learning, Consilient generates collective and constantly improving insights across data sets, making dynamic industry-wide collaboration to detect financial-crime risk possible for the first time. It reveals complex and emerging threats that cannot be detected within the boundaries of any single institution, improving risk discovery, increasing precision, and enabling more effective prioritization while maintaining strict data privacy and governance standards.

Co-founded and chaired by Juan Zarate, the first-ever U.S. Treasury Assistant Secretary for Terrorist Financing and former Deputy National Security Advisor for Combating Terrorism, Consilient was built to address the structural limitations of siloed detection systems and offer a more effective, collaborative, and systemic approach to preventing financial-crime and fraud while strengthening data privacy.

Learn more at Consilient.com.

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SOURCE Consilient Inc

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InventHelp Inventor Develops New Finger Blood Pressure, Pulse, Oximetry Device (CLR-357)

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PITTSBURGH, Nov. 9, 2026 /PRNewswire/ — “I’m a registered nurse, and I thought there could be a way to obtained three vital signs in one easy step,” said an inventor, from Romeoville, Ill., “so I invented the FINGER BLOOD PRESSURE, PULSE, OXIMETRY DEVICE. My design offers a simple and accurate way to frequently monitor blood pressure, pulse rate, and oxygen saturation.”

The invention provides an improved means to monitor vital signs in medical settings, at home, as well as when on the go. In doing so, it can be used to monitor the pulse, oxygen saturation, as well as blood pressure. As a result, it saves time and effort, and it eliminates the need to employ multiple devices. The invention features a practical design that is easy to use so it is ideal for the medical facilities, households, on-the-go individuals, and the general population.

The original design was submitted to the Chicago sales office of InventHelp. It is currently available for licensing or sale to manufacturers or marketers. For more information, write Dept. 25-CLR-357, InventHelp, 100 Beecham Drive, Suite 110, Pittsburgh, PA 15205-9801, or call (412) 288-1300 ext. 1368. Learn more about InventHelp’s Invention Submission Services at http://www.InventHelp.com.

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SOURCE InventHelp

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DongA Science turns 40 years of science journalism into AI tutor AiR NOVA, a CES 2027 honoree

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AiR NOVA answers K-12 students’ science questions using more than 100,000 articles written by DongA Science’s own journalists, showing the source article behind each answer.Launching in January 2027 on web, iOS and Android in Korean, English, Vietnamese and Spanish.

AiR NOVA’s Tutor answers a question about a newly named Korean dinosaur and shows the source article behind the answer. Background imagery is AI-generated.

SEOUL, South Korea, Nov. 9, 2026 /PRNewswire/ — DongA Science, a South Korean science media company that has published science magazines since 1986, has built an AI tutor on its own journalism. AiR NOVA, which answers students’ science questions from the company’s archive and shows the source article behind each answer, has been named a CES Innovation Awards® 2027 Honoree in the EdTech category, the company announced today.

As news publishers around the world weigh how their reporting should be used by AI, DongA Science took a different route by turning its archive into an exclusive learning product. Rather than drawing on the open web, AiR NOVA sources its answers from more than 100,000 articles reported and verified by the company’s science journalists over the past 40 years. This archive spans its magazine archive and daily science news, allowing students to verify where each answer originated. Furthermore, students using AiR NOVA in English, Vietnamese or Spanish receive answers in their selected language, alongside the translated source article from the Korean original.

To learn more about AiR NOVA’s CES 2027 recognition and explore its AI-driven educational features, visit nova.dongascience.com/intro or watch the introductory video at www.youtube.com/watch?v=03EsRqmuASQ.

Three Ways to Keep Students Asking

AiR NOVA is designed for K-12 students and integrates three core AI functions into a single app:

Tutor answers questions with verified sources. For instance, if a student asks, “Are new dinosaurs still being discovered?” Tutor explains at their grade level how the Doolysaurus was named in 2026 as Korea’s third new dinosaur species, and then displays the reference article.Socrates is a patent-pending Socratic-dialogue mode that replies with guiding questions instead of direct answers, encouraging students to reason their way to an explanation in their own words. Students can also upload their inquiry reports, prompting Socrates to ask questions that walk them back through their conclusion process.Coach sustains the inquiry process beyond the initial answer. Students work through missions tied to specific articles, which involve predicting, asking questions, checking sources, explaining and reflecting.

In the Classroom

Teachers can utilize Coach to structure lessons around articles that match their curriculum, build worksheets and missions, and track each student’s participation and results via comprehensive reports. This significantly reduces the time required to prepare inquiry-based lessons.

At launch, AiR NOVA’s science and math content will align with South Korea’s national curriculum, the U.S. Next Generation Science Standards (NGSS), the Common Core State Standards for Mathematics (CCSSM), Cambridge International and the International Baccalaureate (IB). AiR NOVA will be available in January 2027 on web, iOS and Android platforms, requiring no dedicated device. Pricing details will be announced at a later date.

Built on a Proven Service in South Korean Schools

AiR NOVA is the global edition of DongA Science AiR, the company’s established AI science inquiry service in South Korea. The school edition, DongA Science AiR edu, is currently utilized by more than 20,000 students across 170 schools, who collectively complete an average of 5,000 inquiry activities per month. DongA Science developed AiR NOVA based on this extensive operational experience and direct feedback from educators, including practicing teachers collaborating through a classroom problem-solving project run by the Korea Education and Research Information Service (KERIS), a South Korean public agency.

The Korean service was honored with the Minister of Science and ICT Award at the 2024 Digital Service Frontier Awards, while its school edition received the Minister of Education Award at the 2026 K-EduTech Contest.

Showcasing at CES 2027

AiR NOVA will be featured in the Korea Pavilion at CES 2027, taking place Jan. 6-9, 2027, in Las Vegas. During the event, DongA Science plans to connect with global education institutions and edtech companies.

“This CES Innovation Awards honor reflects our long-standing effort to combine the science content we have built up over many years with AI technology to solve real problems in education,” said Kyung-ae Jang, CEO of DongA Science. “We want students around the world to start from a small spark of curiosity and discover the joy of inquiry with AiR NOVA, and we want teachers to be able to design inquiry lessons without the extra burden.”

The CES Innovation Awards program, produced by the Consumer Technology Association (CTA), honors outstanding design and engineering in consumer technology products.

About DongA Science

DongA Science is a leading South Korean science media company that connects science journalism with AI technology to broaden how people learn. Starting with its flagship magazine, Science DongA, launched in 1986, it publishes science and math magazines for children and teens and, together with its daily science news, has built an archive of more than 100,000 science articles over 40 years. Content reported and verified by its science journalists is the foundation for building trustworthy AI education products. On that foundation, the company operates the AI science inquiry service DongA Science AiR in South Korea and will launch its global edition, AiR NOVA, in January 2027.

Website: www.dongascience.com/en
About AiR NOVA: nova.dongascience.com/intro
Video: www.youtube.com/watch?v=03EsRqmuASQ

CES® is a registered trademark of the Consumer Technology Association (CTA)®.

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SOURCE DongA Science

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