How can AI make robots more autonomous and adaptable?
In the field of industrial automation technology, there are two recent hot spots that are difficult to ignore: artificial intelligence (AI) and Nvidia.
Don’t change the meaning of the original content, fine-tune the content, rewrite the content, don’t continue: “Not only that, the two are closely related, because NVIDIA is not limited to its most open The original graphics processing unit (GPU) is extending its GPU technology into the field of digital twins while closely connecting with emerging AI technologies. ”
Recently, NVIDIA has reached cooperation with many industrial companies, including leading industrial automation companies such as Aveva, Rockwell Automation, Siemens and Schneider Electric, as well as Teradyne Robotics and its MiR and Universal Robots Robotics Inc. Recently, Nvidia has collaborated with numerous industrial enterprises, including leading industrial automation companies such as Aveva, Rockwell Automation, Siemens, and Schneider Electric, as well as Teradyne's robotics division and its subsidiaries MiR and Universal Robots.
dealing with differences As a leader in an advanced robotics company with one of the largest installed bases of collaborative and autonomous mobile robots, Ujjwal Kumar, president of Teradyne Robotics, said the industrial sector still faces many issues. Teradyne is working with NVIDIA to help customers solve these problems. He illustrates this point with the example of autonomous pallet trucks.
There are many types of pallets used in industry. They had paint and stickers on them, and in some places had scuffed or broken wood. However, testing of automated pallet trucks is typically performed on new, nearly perfect pallets, which does not reflect the reality on most factory floors. Kumar said the industry has largely accepted this and opted to use humans to handle pallets that automated pallet trucks cannot handle.
“But what we don’t want to launch is just another autonomous pallet truck.” Kumar said, “We want to provide customers with a fully autonomous solution. But to do this, the robot needs advanced cognitive capabilities Capabilities – That’s why we partnered with NVIDIA to deliver a high level of pallet detection and security based on how it detects, responds and moves.
Kumar explained that before Nvidia’s AI capabilities were introduced into pallet inspection applications, the industry’s autonomous pallet truck capabilities were “asterisked”, meaning that they were only autonomous if the robot’s working conditions were perfect. . But now, in our new system we can say that it is an autonomous system suitable for the real world. We understand that pallets come from all over the world and they can be broken, scratched and have many defects. But our robots will no longer be looking for the perfect scenario. They will work in imperfect scenarios and poorly structured environments, with more variability than typical robotic solutions can handle. Picture: The Jetson Edge AI module is used with the UR5e collaborative robot and vision system for quality inspection.
Software Stack
這個拐點可能會比在製造業20年中看到的所有技術採用速度都快。原因在於，過去任何新技術都需要在工廠中分出一部分——風險最小的部分——來嘗試新技術，同時小心不要破壞任何東西。現在，我們的大多數客戶在試行這些AI演算法時，都在雲端中的數位孿生中進行，以便在數百萬種不同的場景中進行各種測試，這將極大地加速技術的採用。因此，在Kumar看來，這個轉折點會比工業界習慣的速度快得多。
他舉出了美國北卡羅來納州和密蘇裡州的一些小型製造商與泰瑞達和英偉達合作開發應用的最新例子，這些應用現已在多個國家使用。 「在過去，只有大公司才能如此迅速地擴大規模。現在，這種擴展正是我們正在實現的。」
AI技術的融合，使機器人能夠在非結構化和不斷變化的環境中更精確地運行，並在各種規模的公司中迅速推廣新的機器人應用。
The above is the detailed content of How can AI make robots more autonomous and adaptable?. 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
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
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
