Technology peripherals
AI
This 'treasure of the hall' at this artificial intelligence conference comes from Changning Enterprise Xijing Technology!
This 'treasure of the hall' at this artificial intelligence conference comes from Changning Enterprise Xijing Technology!
The 2023 World Artificial Intelligence Conference is here as scheduled. At the conference, Xijing Technology, a Changning company that has participated in the conference for six consecutive years, exhibited the world's first intelligent power-swapping driverless commercial vehicle Q-Truck, the world's first new energy driverless tractor Q-Tractor, and a large-scale model based on TerminalGPT, an expert in new intelligent robots for container logistics. Among them, Q-Truck was also selected as one of the "Nine Treasures of the Museum" of this conference, attracting the attention of many participants.
The 2023 World Artificial Intelligence Conference selected the "Nine Treasures of the Museum" based on indicators such as technological content, business prospects, versatility and socio-economic benefits, and Q-Truck, a product of Xijing Technology, was selected.
At 10:30 in the morning, I arrived at the H1-C121 booth of the World Expo Exhibition and Convention Center. Before I could see the "full picture" of Q-Truck, I could see the charm of the "treasure of the museum" surrounded by visitors. It can be seen.
The world’s first intelligent power-swap driverless commercial vehicle launched by Xijing Technology is called Q-Truck. It adopts a new generation of fused perception architecture, equipped with industrial-grade ultra-long-viewing range high-precision binocular AI cameras, lidar and other sensors, and integrates intelligent algorithms to have powerful human-like perception and decision-making, and can be ready in 5 minutes. Can complete unmanned battery replenishment.
The reporter learned that Q-Truck was independently developed by Xijing Technology. Since its launch in September 2018, it has set a new benchmark in the field of autonomous driving. In 2019, Q-Truck achieved engineering mass production; in 2020, Q-Truck mass-produced vehicles went to overseas markets and were commercially launched in Thailand, the United Arab Emirates, the United Kingdom, Malaysia, Mexico and other countries; in January 2022, Q-Truck -The battery-swapping version of the Truck was announced for mass production and became the world's first mass-produced autonomous driving commercial project.
Today, Q-Truck has served more and more countries, helping users achieve the world's earliest mixed operation of driverless and manual driving, and for the first time realized the normal operation of "cab-less" new energy driverless trucks. . It is worth mentioning that in June this year, Xijing Technology completed a contract with the Port of Felixstowe, a subsidiary of Hutchison Ports and the largest port in the UK, to add 100 new energy intelligent driverless trucks Q-Truck to the port. , and will join forces to build the largest "cab-less" new energy driverless commercial fleet in the UK to date.
In addition to the "treasure of the town" Q-Truck, Xijing Technology has also continued to innovate in recent years and launched multiple types of new energy intelligent commercial vehicles to adapt to the needs of global users in different scenarios. At this World Artificial Intelligence Conference, Xijing Technology launched the world's first new energy driverless tractor Q-Tractor, which further enriched Xijing Qomolo's product matrix.
According to reports, Q-Tractor can be adapted to multiple scenarios such as airports, factories, and logistics centers, bringing deeper scene interconnection, a more humane driving experience, and high derivatives to the logistics and transportation fields such as small cargo transportation and luggage towing. application scenarios and higher-level autonomous driving.
At the same time, the Q-Tractor has a maximum load capacity of 40 tons and can achieve 24x7 all-weather transportation, which is more stable, smooth and convenient, with "zero pollution and no emissions". Its digital and intelligent interconnection capabilities can help users efficiently manage vehicle transportation tasks and perform full life cycle maintenance of vehicles to achieve all-weather, full-process unmanned cargo transportation.
In addition to new members of the intelligent driving family, Xijing Technology also launched the world's first TerminalGPT (a new intelligent robot expert in container logistics) based on a large model technology base at this World Artificial Intelligence Conference.
The reporter learned that in the container logistics industry, optimizing the supply chain and improving efficiency are particularly important. Since various emergencies can greatly affect operational efficiency, products are needed to help users build complete digital capabilities and achieve more efficient allocation of production factors at lower costs in production and logistics. In this context, TerminalGPT came into being.
According to the on-site staff, TerminalGPT combines the experience knowledge and operating habits of large logistics scenarios. It can independently learn and use "big data" to predict, "intelligent recommendation" and "overall planning". Through the analysis of various intelligent and information systems, Links empower each system to make it more “intelligent”. Therefore, it can effectively break through the multi-dimensional operational barriers of vehicles, personnel, space and energy in production scenarios such as ports and factories, and make container logistics scenarios more efficient, safe and low-carbon.
According to reports, Xijing Technology’s products and services have successfully entered 18 countries and regions around the world, providing support and services to more than 160 customers in these places. Next, Xijing Technology will continue to focus on digital intelligence and green transformation in multiple scenarios such as sea, land, air, and rail, and demonstrate the charm of China's technological innovation with new forces, new scenarios, and new values.
Source: Shanghai Changning
The above is the detailed content of This 'treasure of the hall' at this artificial intelligence conference comes from Changning Enterprise Xijing Technology!. For more information, please follow other related articles on the PHP Chinese website!
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
Bytedance Cutting launches SVIP super membership: 499 yuan for continuous annual subscription, providing a variety of AI functions
Jun 28, 2024 am 03:51 AM
This site reported on June 27 that Jianying is a video editing software developed by FaceMeng Technology, a subsidiary of ByteDance. It relies on the Douyin platform and basically produces short video content for users of the platform. It is compatible with iOS, Android, and Windows. , MacOS and other operating systems. Jianying officially announced the upgrade of its membership system and launched a new SVIP, which includes a variety of AI black technologies, such as intelligent translation, intelligent highlighting, intelligent packaging, digital human synthesis, etc. In terms of price, the monthly fee for clipping SVIP is 79 yuan, the annual fee is 599 yuan (note on this site: equivalent to 49.9 yuan per month), the continuous monthly subscription is 59 yuan per month, and the continuous annual subscription is 499 yuan per year (equivalent to 41.6 yuan per month) . In addition, the cut official also stated that in order to improve the user experience, those who have subscribed to the original VIP
Context-augmented AI coding assistant using Rag and Sem-Rag
Jun 10, 2024 am 11:08 AM
Improve developer productivity, efficiency, and accuracy by incorporating retrieval-enhanced generation and semantic memory into AI coding assistants. Translated from EnhancingAICodingAssistantswithContextUsingRAGandSEM-RAG, author JanakiramMSV. While basic AI programming assistants are naturally helpful, they often fail to provide the most relevant and correct code suggestions because they rely on a general understanding of the software language and the most common patterns of writing software. The code generated by these coding assistants is suitable for solving the problems they are responsible for solving, but often does not conform to the coding standards, conventions and styles of the individual teams. This often results in suggestions that need to be modified or refined in order for the code to be accepted into the application
Seven Cool GenAI & LLM Technical Interview Questions
Jun 07, 2024 am 10:06 AM
To learn more about AIGC, please visit: 51CTOAI.x Community https://www.51cto.com/aigc/Translator|Jingyan Reviewer|Chonglou is different from the traditional question bank that can be seen everywhere on the Internet. These questions It requires thinking outside the box. Large Language Models (LLMs) are increasingly important in the fields of data science, generative artificial intelligence (GenAI), and artificial intelligence. These complex algorithms enhance human skills and drive efficiency and innovation in many industries, becoming the key for companies to remain competitive. LLM has a wide range of applications. It can be used in fields such as natural language processing, text generation, speech recognition and recommendation systems. By learning from large amounts of data, LLM is able to generate text
Can fine-tuning really allow LLM to learn new things: introducing new knowledge may make the model produce more hallucinations
Jun 11, 2024 pm 03:57 PM
Large Language Models (LLMs) are trained on huge text databases, where they acquire large amounts of real-world knowledge. This knowledge is embedded into their parameters and can then be used when needed. The knowledge of these models is "reified" at the end of training. At the end of pre-training, the model actually stops learning. Align or fine-tune the model to learn how to leverage this knowledge and respond more naturally to user questions. But sometimes model knowledge is not enough, and although the model can access external content through RAG, it is considered beneficial to adapt the model to new domains through fine-tuning. This fine-tuning is performed using input from human annotators or other LLM creations, where the model encounters additional real-world knowledge and integrates it
Five schools of machine learning you don't know about
Jun 05, 2024 pm 08:51 PM
Machine learning is an important branch of artificial intelligence that gives computers the ability to learn from data and improve their capabilities without being explicitly programmed. Machine learning has a wide range of applications in various fields, from image recognition and natural language processing to recommendation systems and fraud detection, and it is changing the way we live. There are many different methods and theories in the field of machine learning, among which the five most influential methods are called the "Five Schools of Machine Learning". The five major schools are the symbolic school, the connectionist school, the evolutionary school, the Bayesian school and the analogy school. 1. Symbolism, also known as symbolism, emphasizes the use of symbols for logical reasoning and expression of knowledge. This school of thought believes that learning is a process of reverse deduction, through existing
To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework
Jul 25, 2024 am 06:42 AM
Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A
SOTA performance, Xiamen multi-modal protein-ligand affinity prediction AI method, combines molecular surface information for the first time
Jul 17, 2024 pm 06:37 PM
Editor | KX In the field of drug research and development, accurately and effectively predicting the binding affinity of proteins and ligands is crucial for drug screening and optimization. However, current studies do not take into account the important role of molecular surface information in protein-ligand interactions. Based on this, researchers from Xiamen University proposed a novel multi-modal feature extraction (MFE) framework, which for the first time combines information on protein surface, 3D structure and sequence, and uses a cross-attention mechanism to compare different modalities. feature alignment. Experimental results demonstrate that this method achieves state-of-the-art performance in predicting protein-ligand binding affinities. Furthermore, ablation studies demonstrate the effectiveness and necessity of protein surface information and multimodal feature alignment within this framework. Related research begins with "S
SK Hynix will display new AI-related products on August 6: 12-layer HBM3E, 321-high NAND, etc.
Aug 01, 2024 pm 09:40 PM
According to news from this site on August 1, SK Hynix released a blog post today (August 1), announcing that it will attend the Global Semiconductor Memory Summit FMS2024 to be held in Santa Clara, California, USA from August 6 to 8, showcasing many new technologies. generation product. Introduction to the Future Memory and Storage Summit (FutureMemoryandStorage), formerly the Flash Memory Summit (FlashMemorySummit) mainly for NAND suppliers, in the context of increasing attention to artificial intelligence technology, this year was renamed the Future Memory and Storage Summit (FutureMemoryandStorage) to invite DRAM and storage vendors and many more players. New product SK hynix launched last year
