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JIDU Auto unveils its new V2.0 software: China’s exclusive and global’s unique pure vision intelligent driving

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CHENGDU, China, Aug. 30, 2024 /PRNewswire/ — On August 28, JIDU Auto unveiled its all-new V2.0 software at an AI driving conference themed “Evolution: AI Reshaping Intelligent Driving” in Chengdu. The newly launched software will debut on the JIDU 07 model. Powered by Baidu Apollo’s Level 4 autonomous driving atomic capabilities and safety framework, JIDU Auto has achieved the milestone to offer pure vision technology for advanced intelligent driving, which is China’s exclusive and one of only two such offerings worldwide, maintaining the company’s leading position in the industry.

The V2.0 software is the most significant update for all JIDU Auto models, encompassing over a dozen key modules for up to 947 new features including end-to-end large-scale model smart driving, a large-scale model smart cockpit, and intelligent vehicle connectivity. Following the upgrade from PPA intelligent driving to ASD (Apollo Self Driving), JIDU Auto has taken a major step towards the era of end-to-end large-scale models on its pure vision technology for advanced intelligent driving, positioning the company as the first global smart EV brand to adopt Baidu Apollo ADFM—the Level 4 autonomous driving large-scale model.

“This marks a significant achievement as Level 4 autonomous driving technology is integrated into consumer cars for the first time. Thanks to the deep integration between Baidu’s ADFM and JIDU Auto, this is the world’s first large-scale autonomous driving model supporting fully unmanned driving applications,” said Joe Xia, CEO of JIDU Auto. “Baidu’s 10+ years of continuous R&D in AI and autonomous driving, coupled with investments exceeding RMB150 billion, has been instrumental in maintaining JIDU Auto’s leadership position.”

JIDU Auto’s fully-upgraded ASD: A giant leap in pure vision end-to-end technology

2024 is poised to be a breakthrough year for intelligent driving technology, as it increasingly becomes a key factor for consumers when choosing cars. End-to-end large models utilize two distinct data processing and transmission methods: one-stage and two-stage. Tesla’s one-stage approach prioritizes lossless transmission and direct information processing. However, this method presents challenges like unpredictable outputs, high debugging costs, and difficulties in guaranteeing a consistent minimum performance level. While the two-stage end-to-end model simplifies system design and implementation by processing data in phases, separating perception and decision-making. Each component performs its specific function, making test and maintenance more straightforward. By processing data in segments, it also allows for optimization at each stage, contributing to the overall system’s stability.

Considering safety, user experience, and other factors, JIDU Auto has opted for a two-stage end-to-end approach. While both JIDU Auto’s ASD and Tesla’s FSD are intelligent driving assistance systems based on pure vision technology, ASD is developed in China and has a deeper understanding of Chinese road conditions, which makes ASD a more suitable intelligent driving assistance system for the country’s specific traffic environment.

“Businesses will make their decisions between one-stage and two-stage models based on specific needs, recognizing the tangible benefits that end-to-end models offer. For us, the potential of intelligent driving technology is full of surprises,” said Wang Liang, Chair of Baidu Intelligent Driving Group Technical Committee. “Theoretically, using one-stage model to address the lower bound challenges is more difficult, requiring us to collect an exceptionally large amount of data with fast growth at an exponential rate compared to the two-stage model, as well as manage a large scale model and handle large amount of data.”

With the newly launched V2.0 software, JIDU Auto’s ASD has achieved a breakthrough by combining pure vision with an end-to-end large-scale model, which places ASD a generation ahead of the industry. Leveraging the Level 4 autonomous driving model Apollo ADFM, ASD strikes a balance between safety and generalizability, offering more safety to human drivers and encompasses the entire range of high-speed and complex urban scenarios.

Baidu is a global leader in AI large-scale models and autonomous driving technology, with over a decade of experience in AI and autonomous driving. Its technological capabilities are among the best in the world. Currently, Apollo’s Level 4 autonomous driving has surpassed 100 million kilometers in mileage and has established a high-performance training cluster with over 5.5 EFLOPS of computing power. Based on Joe Xia’s introduction, JIDU Auto will utilize a high-performance computing cluster exceeding 5.5 EFLOPS to enable efficient model training and rapid iteration. Meanwhile, through its “monthly evolution” approach, JIDU Auto will deliver increasingly advanced, intelligent, and safe intelligent driving experiences.

JIDU Auto’s pure vision technology for advanced intelligent driving surpasses mainstream LiDAR technology in perception capabilities. It achieves centimeter-level 3D precision, offering a perception range of up to 250 meters. Remarkably, it can even identify a mineral water bottle at a distance of 200 meters and maintains a recognition accuracy of moving obstacle speeds within 0.1 meters per second. JIDU Auto’s ASD introduces 106 new features and upgrades, including pilot assistance, valet parking, advanced lane keeping, and active safety, enhancing driving, safety, and parking capabilities.

Large-scale model smart cockpit evolves again: industry’s first lip movement recognition

At the press conference, JIDU Auto also unveiled the industry’s first native AI large-scale model cockpit. Built on an all-new native AI architecture, this cockpit redefines core functionalities by incorporating an innovative end-cloud AI agent system. Perception, comprehension, and execution are now model-driven, enabling both rapid local responses and leveraging the cloud’s powerful understanding and decision-making capabilities.

As early as October 2023, SIMO led the way by integrating Baidu’s ERNIE Bot, becoming the world’s first voice assistant powered by AI large-scale model. This enabled control of nearly all vehicle functions, delivering a more human-like and natural interaction. The newly upgraded SIMO 2.0 is even smarter and more human-like, revolutionizing the traditional command-based interaction of voice assistants. SIMO 2.0 boasts capabilities such as exploration, role-playing, and scene modes. It can assume the role of a family tutor, a car expert, or a travel guide, and it supports over 10,000 user-defined scene settings. Integrated with a multi-modal large-scale model, SIMO 2.0 achieved the industry’s first lip movement recognition function. By recognizing the user’s lip movement trajectory, speech recognition accuracy in noisy environments is increased to 90%. With the addition of features such as simultaneous recognition of multiple commands, multi-zone group chats, and voice commands inside and outside the car, it creates a truly immersive and futuristic intelligent cockpit experience.

As a premium intelligent automotive robot brand, JIDU Auto is always at the forefront of AI advancements, setting new standards for the future of AI mobility.

About JIDU Auto

JIDU is a joint-venture between Geely and Baidu. We stand at the forefront of the AI-driven mobility revolution, crafting premium intelligent robocars that integrate Baidu’s advanced AI capabilities, Apollo’s Level 4 autonomous driving technologies, and Geely’s SEA Platform.

With a commitment to innovation, JIDU’s robocars feature leading-edge autonomous driving, smart cabin technology, and digital services designed to redefine the future of mobility.

Our mission is to create revolutionary Robocars, making safer and more efficient mobility experience, so people have more time and space to go further.

 

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Earth’s pulse monitored: a review highlights remote sensing time series progress

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As urbanization accelerates and environmental dynamics shift, the need for accurate and timely terrestrial monitoring has never been more urgent. A review has introduced a novel approach to remote sensing time series analysis, integrating multi-source data to enable near real-time monitoring. This innovative methodology promises to transform environmental conservation and urban planning by providing unprecedented insights into terrestrial changes and offering a more precise understanding of environmental dynamics.

GUANGZHOU, China, Dec. 22, 2024 /PRNewswire-PRWeb/ — An international team of researchers from South China Normal University, the University of Connecticut, and the Chinese Academy of Sciences has made a significant breakthrough in remote sensing. Their review, published (DOI: 10.34133/remotesensing.0285) in the Journal of Remote Sensing on December 11, 2024, addresses key challenges in remote sensing, such as incomplete data and noise interference. The team’s new time series analysis technique leverages advanced data reconstruction and fusion methods, significantly enhancing the precision and efficiency of remote sensing for monitoring environmental changes.

The research team has developed an advanced time series analysis technique that combines deep learning algorithms with traditional remote sensing methods to integrate data from various remote sensing sources. This innovative approach allows for the extraction of subtle patterns from large, complex datasets, which is crucial for monitoring critical environmental parameters such as land use and vegetation health. Unlike conventional techniques that struggle with incomplete or noisy data, this new methodology offers enhanced accuracy and more reliable insights into terrestrial dynamics, paving the way for more effective environmental monitoring.

Central to the study’s success is the integration of Long Short-Term Memory (LSTM) networks and Generative Adversarial Networks (GANs) to address the challenges posed by missing or noisy data. The LSTM networks capture temporal trends over time, while the GANs generate synthetic data that mimics real-world observations to fill gaps and correct for atmospheric distortions. This dual approach has resulted in a cleaner, more accurate time series dataset, which was validated against independent ground truth measurements. The researchers demonstrated significant improvements in key vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), setting a new benchmark in the field of remote sensing.

Experts in the field have lauded the study’s potential to revolutionize remote sensing applications. They see the method as a transformative tool for enhancing high-resolution monitoring and extending its coverage, particularly in agricultural surveillance, urban planning, and environmental management. “This method represents a crucial advancement in our ability to monitor environmental changes,” says Professor Fu. “As it evolves, it could play a key role in addressing climate change and other global challenges.”

The methodology’s future applications are vast, especially in global environmental monitoring and supporting sustainable development goals. By integrating multi-temporal data from Landsat and Sentinel-2 satellites, the team has created a framework for accurate and continuous terrestrial analysis. As computational power advances and algorithms improve, this technology is expected to become a vital tool for natural resource management, disaster response, and climate change mitigation. In the years to come, it could provide critical data to help policymakers address pressing environmental issues on a global scale.

References

DOI

10.34133/remotesensing.0285

Oiginal Source URL

https://doi.org/10.34133/remotesensing.0285

Funding information

This work was supported by the National Nature Science Foundation of China (grant numbers 42425001 and 42071399).

About Journal of Remote Sensing

The Journal of Remote Sensing, an online-only Open Access journal published in association with AIR-CAS, promotes the theory, science, and technology of remote sensing, as well as interdisciplinary research within earth and information science.

Media Contact

George Hua, Chuanlink Innovations, 1 8656606278, TranSpread1@gmail.com, http://chuanlink-innovations.com/

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ZINZINO AB (PUBL.): ENTERS INTO AGREEMENT TO PROVIDE DIP FINANCING TO ZURVITA INITIATING CHAPTER 11 PROCESS

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GOTHENBURG, Sweden, Dec. 22, 2024 /PRNewswire/ — Zinzino has in a press release dated 20240617 announced that a letter of intent to acquire 100% of the shares in the North American direct selling company Zurvita Inc. “Zurvita or the Company” was signed. Since then, Zinzino has negotiated with the owners of Zurvita Inc. and instead concluded that the purchase of Zurvita’s assets in a Chapter 11 proceeding for the Company is in Zinzino’s best interest.

Zinzino is providing a debtor-in-possession (DIP) financing to Zurvita, which filed for Chapter 11 bankruptcy proceedings on the 20th December 2024. By entering as a financier in Zurvita’s Chapter 11 with loans totaling USD 4.5 million, Zinzino simultaneously makes an offer to acquire the company’s assets via a so-called stalking horse bid. If the bid is accepted, the DIP loan will be converted into part of a debt-settled purchase price, which will be determined after Zurvita has completed the sale process that is subject to higher and better offers in accordance with the applicable terms of Chapter 11. Other bidders have the right to submit bids for Zurvita during the process and if another bid is accepted, Zinzino’s loan will be repaid and certain of its costs associated with the process will be reimbursed. 

Zurvita is a direct selling health company with operations in the United States, Canada and Mexico. The brand portfolio offers a range of innovative health and wellness products. The business has total annual sales of approximately USD 30 million with good gross margins. A potential transaction with Zinzino is expected to add growth through the synergies arising from the joint networks, combined with Zinzino’s test-based product concept. The profitability of the Company will thus be able to develop well by utilizing Zinzino’s existing technical platform and organization.

A visionary mindset, tech first perspective, test-based nutrition at the cellular level and a strong position to capitalize on current trends will form the basis of the new partnership. Following the acquisitions of VMA Life in 2020, Enhanzz in 2022, the strategic partnership with ACN and the recently completed asset acquisition of Xelliss, Zinzino has been looking for further strong investments to maintain its sustainable, profitable growth, strengthen its distribution power, expand into new markets and leverage the product portfolio in new consumer areas.

– “Individualized advice and tailored solutions are the future, and not just in health and wellness,” says Dag Bergheim Pettersen, CEO of Zinzino. “Together, we have years of combined industry experience and everything it takes to drive the modern, personalized shopping experience through direct sales”. Jay Shafer, CEO and co-founder of Zurvita, states “After considering multiple options for the company and under the guidance of our attorneys and third-party advisors, we feel this presents the best opportunity to continue Zurvita’s mission, deliver the highest quality products, and provide continuity for our staff and consultants. We are excited to see what the future holds for Zurvita.” 

For more information:
Dag Bergheim Pettersen CEO Zinzino +47 (0) 932 25 700, www.zinzino.com

Pictures for publication free of charge:
marketing@zinzino.com

Certified Adviser:
Carnegie Investment Bank AB (publ.)

Zinzino AB (publ.) is obliged to publish this information in compliance with current EU regulations governing market abuse. The information was provided by the above contact person for publication at 20.00 on the 21st of December 2024.

This information was brought to you by Cision http://news.cision.com

https://news.cision.com/zinzino/r/zinzino-ab–publ–enters-into-agreement-to-provide-dip-financing-to-zurvita-initiating-chapter-11-pr,c4086040

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Meet With Culture: Exquisite Craftsmanship of Traditional Chinese Architecture

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BEIJING, Dec. 22, 2024 /PRNewswire/ — The Temple of Agriculture in Beijing played a significant role during the Ming (1368-1644) and Qing (1644-1911) dynasties. Over nearly 600 years, 25 emperors personally visited or sent ministers to perform spring farming ceremonies and offer sacrifices to Shennong, the god of agriculture.

 

Built in 1420 during the Yongle reign, the temple’s predecessor was the Temple of Mountains and Rivers in Nanjing. When Emperor Zhu Di moved the Ming capital to Beijing, he constructed a larger temple inspired by the Nanjing temple, which gradually evolved into the Temple of Agriculture.

The Taisui Hall, the largest building complex in the temple, now serves as a major exhibition hall of the Beijing Ancient Architecture Museum, showcasing models of classical Chinese buildings and demonstrating the solemnity of royal architecture.

Ancient Chinese architecture is predominantly wooden-structured, chosen for its availability, versatility, and earthquake resistance. Artisans developed sophisticated techniques in material selection and construction. The wooden framework consists of columns, beams, girders, and purlins, with innovative structural forms like lifting-beam and piercing-bracket structures.

A unique architectural element is the dougong (bracket sets), which supports weight and connects beam frames with column walls. Mortise-tenon joints were invented to create elastic frameworks by connecting different components.

While discussing the Temple of Agriculture, it’s worth noting another remarkable example of architectural hierarchy which could be found in the Temple of Heaven. The hierarchy of architectural designs reflected social stratification, with eave structures like the triple-layered eaves of the Hall of Prayer for Good Harvest representing the highest-level architectural design.

Over centuries, the Temple of Agriculture has transformed from an imperial garden to a public park and a museum for historical architecture, now standing as a significant cultural landmark that symbolizes China’s agricultural civilization and architectural heritage along Beijing’s Central Axis.

Quickly join Alexandre to study and explore the traditional Chinese architecture.
https://youtu.be/YpA03WiZ9Wc

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SOURCE China International Communications Group

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