Dublin, March 08, 2024 (GLOBE NEWSWIRE) -- The "Automotive AI Foundation Model Technology and Application Trends Report, 2023-2024" report has been added to ResearchAndMarkets.com's offering.
The comprehensive analysis of the current and future landscape of Automotive AI Foundation Model Technology investigates the rapid advancements and adoption of these models, particularly highlighting the significant progress made in end-to-end autonomous driving models by industry leaders like Tesla with their Full Self-Driving (FSD) version 12 and the introduction of advanced AI capabilities in vehicles for enhanced driving experience.
The publication delves into the evolving phases of AI foundation model development in autonomous driving, spotlighting current industry benchmarks and the transition to more sophisticated AI applications that emulate human-like understanding of the physical world through vision. Major OEMs and Tier 1 suppliers' progress in integrating and implementing these technologies foreshadows a future led by Artificial General Intelligence (AGI) and versatile AI applications within the automotive industry.
This document contrasts the strategies employed by companies operating at the frontier of autonomous driving technology, such as Xpeng Motor, NIO, Li Auto, and how they shape the competitive landscape through innovative breakthroughs like generative end-to-end models. The role of AI video generation technologies like OpenAI's SORA is also discussed in the context of their potential to expand the capabilities of autonomous driving systems and the broader AI technology ecosystem.
AI Foundation Models: Transformative Potential and Industry Disruption
- An analysis of the phases in AI foundation models' development, from perception-level models to advanced AGI's world models, is thoroughly presented.
- Details on Tesla's FSD version 12 pioneering the end-to-end autonomous driving approach, with an AI algorithm replacing extensive coding for decision-making processes.
- Exploration of state-of-the-art AI-driven autonomous driving benchmarks and tests, such as Horizon Robotics' VADv2 model, which demonstrates exceptional performance utilizing camera-based sensor inputs.
- Recent trends in visual language models (VLMs), as seen in the new DriveVLM technology, which offers hybrid autonomous driving solutions combing traditional methodologies with cutting-edge AI components for enhanced functionality.
In-depth analysis of computing power, algorithm developments, and data management, the report spotlights AI and cloud companies that are becoming increasingly critical to the success of AI foundation model initiatives.
Pioneering solutions are discussed, such as SenseTime's SenseChat-Vision and autonomous driving foundation model DriveMLM, which offer new perspectives on vehicle automation. Collaboration highlights between AI companies and OEMs include Tencent's Intelligent Vehicle Cloud services and Haomo.ai's foundation model-based scenario generation efforts for autonomous driving development.
Emerging Regional and Sectoral Trends in Automotive AI
- Insight into how regional markets and sectors within the automotive industry are integrating AI foundation models.
- Advances in the Asia-Pacific market, particularly from Chinese companies like Xpeng Motor and Li Auto, pioneering significant advancements in autonomous driving technologies.
- Consideration of North America's Silicon Valley as a hotbed for AI technological advancements, with companies like Tesla setting industry standards.
With a spotlight on innovation, transformation, and the future trajectory of automotive AI, this report serves as a key resource for industry stakeholders, technologists, strategists, and policymakers interested in the profound impact AI foundation models have on the automotive sector.
Key Topics Covered:
1 Classification of Autonomous Driving (AD) Algorithms and Common Algorithm Models
1.1 AD System Classification and Software 2.0
1.2 Baidu AD Algorithm Development History
1.3 Tesla AD Algorithm Development History
1.4 Neural Network Model
1.5 Traditional AD AI Algorithms (Small Model)
1.6 Transformer and BEV (Foundation Model)
1.7 End-to-end Foundation Model Cases
2 Overview of AI Foundation Model and Intelligent Computing Center
2.1 AI Foundation Model
2.2 Application of AI Foundation Model in Automotive
2.3 Autonomous Driving (AD) Multimodal Basic Foundation Model
2.4 Intelligent Computing Center
3 Tesla Algorithm and Foundation Model Analysis
3.1 Algorithm Fusion of CNN and Transformer
3.2 Transformer Turns 2D into 3D
3.3 Occupancy Network, Semantic Segmentation and Time-space Sequence
3.4 LaneGCN and Search Tree
3.5 Data Closed Loop and Data Engine
4 AI Algorithms and Foundation Model Providers
4.1 Haomo.ai
4.2 QCraft
4.3 Baidu
4.4 Inspur
4.5 SenseTime
4.6 Huawei
4.7 Unisound
4.8 iFLYTEK
4.9 AISpeech
4.10 Megvii Technology
4.11 Volcengine
4.12 Tencent Cloud
4.13 Other Companies
4.13.1 Banma Zhixing
4.13.2 ThunderSoft
4.13.3 Horizon Robotics' End-side Deployment of Foundation Model
5 Foundation Model of OEMs
5.1 Xpeng Motor
5.2 Li Auto
5.3 Geely
5.4 BYD
5.5 GM
5.6 Changan Automobile
5.7 Other Auto Enterprises
5.7.1 GWM: All-round Layout of AI Foundation Model
5.7.2 Chery: EXEED STERRA ES Equipped with Cognitive Foundation Model
5.7.3 GAC
5.7.4 SAIC-GM-Wuling
5.7.5 Mercedes-Benz
5.7.6 Volkswagen
5.7.7 Stellantis
5.7.8 PSA
6 Application Trends of Sora and AI Foundation Model in Automotive
6.1 Analysis of Sora Text-to-Video Foundation Model
6.2 Explanation of Sora's Underlying Algorithm Architecture
6.3 Generative World Model and Intelligent Vehicle Industry
6.4 Application Trends of AI Foundation Model in Automotive
6.5 AI Foundation Model Requirements for Chips
Companies Profiled
- Haomo.ai
- QCraft
- Baidu
- Inspur
- SenseTime
- Huawei
- Unisound
- iFLYTEK
- AISpeech
- Megvii Technology
- Volcengine
- Tencent Cloud
- Banma Zhixing
- ThunderSoft
- Horizon Robotics
- Xpeng Motor
- Li Auto
- Geely
- BYD
- GM
- Deepal GPT
- GWM
- Chery
- GAC
- SAIC-GM-Wuling
- Mercedes-Benz
- Volkswagen
- Stellantis
- PSA
For more information about this report visit https://www.researchandmarkets.com/r/72rlwm
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