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Hon Hai Research Institute unveils AI-enabled ModeSeQ that can read pedestrian and vehicle movements in a flash

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23 hours ago

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Multimodal Trajectory Prediction Model Competitively Recognized Internationally

Hon Hai Research Institute (HHRI), an R&D powerhouse of Hon Hai Technology Group (Foxconn) (TWSE: 2317), the world’s largest electronics manufacturer and technology service provider, has been recognized for its competitive work in trajectory prediction in autonomous driving technology.

The landmark achievements in ModeSeq, taking top spot in the Waymo Open Dataset Challenge and presenting at CVPR 2025, among the world’s most influential AI and computer vision conferences, gathering top-tier tech firms, research institutions, and academic leaders, highlight HHRI’s growing leadership and technical excellence on the international stage.

“ModeSeq empowers autonomous vehicles with more accurate and diverse predictions of traffic participant behaviors,” said Yung-Hui Li, Director of the Artificial Intelligence Research Center at HHRI. “It directly enhances decision-making safety, reduces computational cost, and introduces unique mode-extrapolation capabilities to dynamically adjust the number of predicted behavior modes based on scenario uncertainty.”

Figure 1: Illustrates the ModeSeq workflow, showing how the model anticipates multiple possible future trajectories (highlighted by red vehicle icons and arrows). It progressively analyzes the scenario and assigns confidence scores (e.g., 0.2) to each potential path.

HHRI’s Artificial Intelligence Research Center, in collaboration with City University of Hong Kong, on June 13, presented “ModeSeq: Taming Sparse Multimodal Motion Prediction with Sequential Mode Modeling” at CVPR 2025(IEEE/CVF Conference on Computer Vision and Pattern Recognition), where its paper was among only the 22% that were accepted.

The multimodal trajectory-prediction technology overcomes the limitations of prior methods by both preserving high performance and delivering diverse potential outcome paths. ModeSeq introduces sequential pattern modeling and employs an Early-Match-Take-All (EMTA) loss function to reinforce multimodal predictions. It encodes scenes using Factorized Transformers and decodes them with a hybrid architecture combining Memory Transformers and dedicated ModeSeq layers.

The research team further refined it into Parallel ModeSeq, which claimed victory in the prestigious Waymo Open Dataset (WOD) Challenge – Interaction Prediction Track at the CVPR WAD Workshop. The team’s winning entry surpassed strong competitors from the National University of Singapore, University of British Columbia, Vector Institute for AI, University of Waterloo and Georgia Institute of Technology.

Building on their success from last year – where ModeSeq placed second globally in the 2024 CVPR Waymo Motion Prediction Challenge – this year’s Parallel ModeSeq emerged triumphant in the 2025 Interaction Prediction track.

Led by Director Li of HHRI’s AI Research Lab, in collaboration with Professor Jianping Wang’s group at City University of Hong Kong and researchers from Carnegie Mellon University, ModeSeq outperforms previous approaches on the Motion Prediction Benchmark—achieving superior mAP and soft-mAP scores while maintaining comparable minADE and minFDE metrics.

SOURCE: Foxconn



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AI Research

RRC getting real with artificial intelligence – Winnipeg Free Press

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51 minutes ago

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July 11, 2025

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Red River College Polytechnic is offering crash courses in generative artificial intelligence to help classroom teachers get more comfortable with the technology.

Foundations of Generative AI in Education, a microcredential that takes 15 hours to complete, gives participants guidance to explore AI tools and encourage ethical and effective use of them in schools.

Tyler Steiner was tasked with creating the program in 2023, shortly after the release of ChatGPT — a chatbot that generates human-like replies to prompts within seconds — and numerous copycat programs that have come online since.



MIKE DEAL / FREE PRESS

Lauren Phillips, a RRC Polytech associate dean, said it’s important students know when they can use AI.

“There’s no putting that genie back in the bottle,” said Steiner, a curriculum developer at the post-secondary institute in Winnipeg.

While noting teachers can “lock and block” via pen-and-paper tests and essays, the reality is students are using GenAI outside school and authentic experiential learning should reflect the real world, he said.

Steiner’s advice?

Introduce it with the caveat students should withhold personal information from prompts to protect their privacy, analyze answers for bias and “hallucinations” (false or misleading information) and be wary of over-reliance on technology.

RRC Polytech piloted its first GenAI microcredential little more than a year ago. A total of 109 completion badges have been issued to date.

The majority of early participants in the training program are faculty members at RRC Polytech. The Winnipeg School Division has also covered the tab for about 20 teachers who’ve expressed interest in upskilling.

“There was a lot of fear when GenAI first launched, but we also saw that it had a ton of power and possibility in education,” said Lauren Phillips, associate dean of RRC Polytech’s school of education, arts and sciences.

Phillips called a microcredential “the perfect tool” to familiarize teachers with GenAI in short order, as it is already rapidly changing the kindergarten to Grade 12 and post-secondary education sectors.

Manitoba teachers have told the Free Press they are using chatbots to plan lessons and brainstorm report card comments, among other tasks.

Students are using them to help with everything from breaking down a complex math equation to creating schedules to manage their time. Others have been caught cutting corners.

Submitted assignments should always disclose when an author has used ChatGPT, Copilot or another tool “as a partner,” Phillips said.

She and Steiner said in separate interviews the key to success is providing students with clear instructions about when they can and cannot use this type of technology.

Business administration instructor Nora Sobel plans to spend much of the summer refreshing course content to incorporate their tips; Sobel recently completed all three GenAI microcredentials available on her campus.

Two new ones — Application of Generative AI in Education and Integration of Generative AI in Education — were added to the roster this spring.

Sobel said it is “overwhelming” to navigate this transformative technology, but it’s important to do so because employers will expect graduates to have the know-how to use them properly.

It’s often obvious when a student has used GenAI because their answers are abstract and generic, she said, adding her goal is to release rubrics in 2025-26 with explicit direction surrounding the active rather than passive use of these tools.