Technology peripherals
AI
NetEase Fuxi launches smart robot beta version to help intelligent upgrade of the industry
NetEase Fuxi launches smart robot beta version to help intelligent upgrade of the industry
According to the seventh national census data, my country's population aged 60 and above exceeds 260 million, accounting for 18.70%. The data shows that the degree of population aging will further deepen. As the demographic dividend disappears, all walks of life will continue to face pressures such as labor shortages and high labor costs. Artificial intelligence (AI) and robots are gradually changing our lives, but the in-depth implementation of the technology is still in its infancy. Letting AI and robots handle more repetitive and high-risk tasks and increase the value of human resources is the key to the intelligent development of today's society. The inevitable trend.
According to the "China Robot Industry Development Report (2022)", it is expected that by the end of 2022, the global robot market will reach US$51.3 billion, of which China will reach approximately US$17.4 billion. However, there is greater demand behind this estimated market size. However, due to the complexity of actual business, AI and robot products often cannot be effectively applied in relevant scenarios.
With the continuous development of the Internet of Things, industrial 5G and virtual-real integration technology, artificial intelligence technology will be integrated and upgraded with them, giving full play to the collaborative advantages of humans and machines, solving problems and integrating AI capabilities and innovative technologies applied in real-life scenarios such as robots, games, and the metaverse. This will improve application development efficiency and reduce enterprise labor costs.
From virtual to real, oriented to intelligent agent programming, to build a new solution for unified task modeling
From the current development stage, artificial intelligence It is already easy to solve local simple problems, but complex scenarios still require a large amount of data or high-quality simulation environment support. How to apply AI's cognitive intelligence and decision-making intelligence to a wider range of physical fields, rely on autonomous learning capabilities to collaborate with humans, and even imitate humans to engage in more intellectual and creative labor is a research topic in the field of artificial intelligence and the robotics industry. important direction. Based on the current situation that the degree of machine intelligence is generally low, by building a "human in the loop" (HITL) method, the concept of human-machine collaboration is used to help enterprises solve the problem of high AI thresholds, long R&D cycles, and application implementation. Difficulty and other practical problems have become a feasible way to solve the pain points of the above-mentioned AI industry.
NetEase Fuxi was founded in 2017 and is the top institution in China focusing on the research and application of AI in games and pan-entertainment. They have rich technical accumulation in AI fields such as digital twins, reinforcement learning, user portraits, and natural language processing. In addition, they are also committed to applying virtual world technology to real economic fields such as intelligent manufacturing, construction machinery and service industries. In this context, Fuxi Youling Robot came into being.
Different from traditional PaaS platforms, the decision-making of "humans" in intelligent robots is crucial. The platform issues tasks through the crowdsourcing model and quickly calls on "human capabilities." Crowdsourcing users complete tasks online through the platform, solving the problem of high costs in collecting and annotating data. The platform will also actively learn and implement closed-loop data, feeding real task manual operation data back to the AI algorithm to realize task preprocessing, which greatly improves the efficiency of task completion; crowdsourcing users can also use the "online order taking and remote work" mode to solve construction problems in high-risk and harsh environment scenarios and achieve delivery without leaving home.
In addition to mining robot operation scenarios, the crowdsourcing platform also supports AI enterprise user demand scenarios such as game AI, AR/VR, and Metaverse. Users with data collection and labeling needs can publish tasks through the crowdsourcing platform. The platform covers 80% of mainstream data labeling scenarios in the AI field, and continues to reduce the number of manual labeling through automatic learning, with automatic labeling accounting for up to 20%.
For business scenarios such as robots, the platform also provides end-side management capabilities, allowing users to write end-side business logic in a platform-based manner, combined with one-click device initialization, continuous integration release, OTA and other functions truly achieve integrated development of cloud, edge and device, allowing users to focus only on business.
Open ecosystem and build a new era of intelligent robots
In the next few decades, human-machine collaboration will be the key to the intelligent development of society The main theme is that machine intelligence requires human support, and human intelligence requires machine assistance. At the root node connecting the intelligent agent to the world, there will certainly be no shortage of humans, but the role may continue to change from task executor to organizer, manager, decision-maker and discoverer. On the basis of providing standardized task modeling tools, NetEase Youling Robot hopes to serve as a bridge between small and medium-sized enterprises and scattered workers in the society at large, providing platform support for task modeling, release and execution.
The implementation of NetEase Fuxi's excavating robot in the construction of key infrastructure projects in southwest China has also verified the strong implementation, sustainability, and replicability of the human-machine collaboration platform. On the one hand, the platform allows traditional excavators to achieve intelligent production through human-machine collaboration. On the other hand, through online distribution of crowdsourcing tasks, traditional excavator masters no longer engage in repetitive, boring and dangerous work, further promoting the digital economy. Deeply integrate with the real economy to promote the quality and efficiency improvement of the real economy. In addition to exploring robot application scenarios, the platform has also been practiced and verified in scenarios such as game character face pinching, image and text recognition detection, smart parks, and art crowdsourcing.
In the future, intelligent robots will explore more scenarios that integrate reality and reality, allowing intelligent agents to better meet people’s needs for production and labor, and fully open up opportunities for cooperation and co-construction, and integrate with the ecosystem. Partners create a new era of human-machine collaboration.
The above is the detailed content of NetEase Fuxi launches smart robot beta version to help intelligent upgrade of the industry. 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
