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- Huawei Software Elite Challenge has been successfully held for ten times, and more than 2,000 software elites have joined Huawei
- On April 28, 2024, the 10th Huawei Software Elite Challenge 2024-"Planck Project" global finals and awards ceremony concluded successfully. Lasting two months, nearly 30,000 players and more than 5,700 teams from more than 800 universities around the world competed fiercely in the regional preliminaries, regional semi-finals, and global finals of the eight major competition areas. In the end, the Beijing-Tianjin Northeast Division came from Harbin Institute of Technology. The "Yuanmeng Star" team won the global championship in one fell swoop and won a prize of 200,000 yuan. A group photo of the finalists of the 2023 Huawei Software Elite Challenge. The global champion of the 2024 Huawei Software Elite Challenge. The Huawei Software Elite Challenge is a large-scale software programming competition organized by Huawei for college students around the world. With the theme of "Planck Plan", it aims to Looking for
- AI 668 2024-04-29 19:22:29
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- The vitality of super intelligence awakens! But with the arrival of self-updating AI, mothers no longer have to worry about data bottlenecks
- I cry to death. The world is madly building big models. The data on the Internet is not enough. It is not enough at all. The training model looks like "The Hunger Games", and AI researchers around the world are worrying about how to feed these data voracious eaters. This problem is particularly prominent in multi-modal tasks. At a time when nothing could be done, a start-up team from the Department of Renmin University of China used its own new model to become the first in China to make "model-generated data feed itself" a reality. Moreover, it is a two-pronged approach on the understanding side and the generation side. Both sides can generate high-quality, multi-modal new data and provide data feedback to the model itself. What is a model? Awaker 1.0, a large multi-modal model that just appeared on the Zhongguancun Forum. Who is the team? Sophon engine. Founded by Gao Yizhao, a doctoral student at Renmin University’s Hillhouse School of Artificial Intelligence.
- AI 1368 2024-04-29 18:55:14
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- Identify overfitting and underfitting through learning curves
- This article will introduce how to effectively identify overfitting and underfitting in machine learning models through learning curves. Underfitting and overfitting 1. Overfitting If a model is overtrained on the data so that it learns noise from it, then the model is said to be overfitting. An overfitted model learns every example so perfectly that it will misclassify an unseen/new example. For an overfitted model, we will get a perfect/near-perfect training set score and a terrible validation set/test score. Slightly modified: "Cause of overfitting: Use a complex model to solve a simple problem and extract noise from the data. Because a small data set as a training set may not represent the correct representation of all data." 2. Underfitting Heru
- AI 1619 2024-04-29 18:50:15
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- Industry 4.0 Revolution: A Four-Phase Blueprint for Predictive Maintenance Success
- Designing predictive maintenance solutions for Industry 4.0 represents a paradigm shift in the way businesses maintain and operate. Proactive prevention of operational challenges through the use of advanced predictive maintenance technologies is a key aspect of this new industrial era. These solutions not only help generate new revenue streams and save costs, but also play an important role in preventing downtime and production downtime. In the era of Industry 4.0, companies need to use intelligent IoT devices and sensors to collect and analyze large amounts of production data. This data can be used to predict equipment failures and repair needs. By using these predictive maintenance technologies, companies can identify potential problems in advance and take appropriate action, minimizing downtime and production disruptions. This proactive approach to preventive maintenance can greatly
- AI 568 2024-04-29 18:22:23
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- What achievements will generative AI have in the field of video game development?
- Generative AI brings exciting new ways for video game developers to create engaging content, realistic visuals, and immersive gaming experiences. In this article, we’ll explore through a series of practical examples how generative AI can enhance and speed up game development. What can generative AI do? Let’s start by breaking down some of the main elements in game development and see how generative AI can facilitate the creative process: procedural generation. Large, complex, and unpredictable environments are algorithmically created to deliver a unique and dynamic gameplay experience in every game. Terrain generation. Generative AI can help generate realistic terrain and enhance the visual appeal of the game world. Automatic modeling. Generative AI can simplify the creation of 3D models of characters and other elements,
- AI 841 2024-04-29 18:04:26
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- Single card running Llama 70B is faster than dual card, Microsoft forced FP6 into A100 | Open source
- FP8 and lower floating point quantification precision are no longer the "patent" of H100! Lao Huang wanted everyone to use INT8/INT4, and the Microsoft DeepSpeed team started running FP6 on A100 without official support from NVIDIA. Test results show that the new method TC-FPx's FP6 quantization on A100 is close to or occasionally faster than INT4, and has higher accuracy than the latter. On top of this, there is also end-to-end large model support, which has been open sourced and integrated into deep learning inference frameworks such as DeepSpeed. This result also has an immediate effect on accelerating large models - under this framework, using a single card to run Llama, the throughput is 2.65 times higher than that of dual cards. one
- AI 1432 2024-04-29 16:55:12
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- The rise of AI in marketing technology: Transforming digital marketing strategies
- In the ever-evolving world of digital marketing, AI has become a powerful tool for brands looking to navigate their marketing funnels with precision and efficiency. By analyzing patterns and trends in large data sets, AI enables marketers to gain valuable insights into consumer behavior, preferences and purchasing patterns. This data-driven approach enables brands to tailor marketing strategies at every stage of the funnel—from awareness to conversion—with unparalleled accuracy. AI uses machine learning and deep learning technologies to automatically collect, analyze and interpret massive amounts of data, transforming the data into actionable marketing strategies. The advantage of AI is that it can automatically discover patterns and trends hidden in massive data and formulate marketing strategies more accurately than humans. Through the application of AI, marketers can better understand
- AI 875 2024-04-29 16:43:10
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- Xiaohongshu interprets information retrieval from the memory mechanism and proposes a new paradigm to obtain EACL Oral
- Recently, the paper "GenerativeDenseRetrieval: MemoryCanBeaBurden" from the Xiaohongshu search algorithm team was accepted as Oral by EACL2024, an international conference in the field of natural language processing, with an acceptance rate of 11.32% (144/1271). In their paper, they proposed a novel information retrieval paradigm—Generative Dense Retrieval (GDR). This paradigm can well solve the challenges faced by traditional generative retrieval (GR) when dealing with large-scale data sets. It is inspired by the memory mechanism. In past practice
- AI 1357 2024-04-29 16:16:07
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- The evolution of artificial intelligence in space exploration and human settlement engineering
- In the 1950s, artificial intelligence (AI) was born. That's when researchers discovered that machines could perform human-like tasks, such as thinking. Later, in the 1960s, the U.S. Department of Defense funded artificial intelligence and established laboratories for further development. Researchers are finding applications for artificial intelligence in many areas, such as space exploration and survival in extreme environments. Space exploration is the study of the universe, which covers the entire universe beyond the earth. Space is classified as an extreme environment because its conditions are different from those on Earth. To survive in space, many factors must be considered and precautions must be taken. Scientists and researchers believe that exploring space and understanding the current state of everything can help understand how the universe works and prepare for potential environmental crises
- AI 1115 2024-04-29 15:25:01
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- The rise of human-like AI: Changing the job market and the workforce
- The emergence of artificial intelligence is reshaping the global job market and workforce. As AI robots become increasingly sophisticated and capable of performing a wide range of tasks, from manual labor to complex cognitive abilities, they are expected to revolutionize industries and redefine traditional concepts of work. This article explores the rise of artificial intelligence and its transformative impact on the job market and workforce across industries. Automation of routine tasks: AI excels at automating routine and repetitive tasks, allowing human workers to focus on more creative and strategic work. In areas such as manufacturing, logistics, and retail, humanoid robots are deployed to perform tasks such as assembly line operations, warehouse management, and customer service. While this automation increases efficiency and productivity, it also requires human workers to be retrained and
- AI 651 2024-04-29 13:20:01
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- Gaussian-LIC: The first multi-sensor fusion 3DGS-SLAM system (Zhejiang University & TUM)
- The implicit expression of the combination of multi-sensors and 3DGS "required real-time capabilities for computationally intensive SLAM tasks based on sampling in 3D space" requires a NeRF-based+SLAM approach. 3DGS stands out for its fast rendering speed and superior visual quality. As a clear and interpretable representation, 3DGS makes scene editing simple and facilitates the execution of numerous downstream tasks. Existing radiation field-based SLAM systems are mainly tested in small-scale indoor environments with good lighting and obtain satisfactory results using sequential RGB-D or RGB input. Difficulties will be encountered when these methods are extended to challenging large-scale uncontrolled outdoor scenes, such as challenging lighting
- AI 1087 2024-04-29 11:49:20
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- How to integrate GPU cloud servers into AI infrastructure?
- GPU cloud servers are cloud-based computing resources that utilize graphics processing units to handle high-performance tasks. Unlike traditional servers that rely solely on CPUs, GPU cloud servers are designed for parallel processing, making them ideal for compute-intensive applications such as machine learning and artificial intelligence. In the B2B field, integrating GPU cloud servers into AI infrastructure has become a strategic move to improve performance and scalability. Machine learning models often require intense computing power, and GPU cloud servers provide a scalable solution that enables enterprises to process large data sets and run complex algorithms more efficiently. This capability is critical for businesses looking to maintain a competitive advantage in a rapidly evolving technology environment, as AI is driving change across industries.
- AI 912 2024-04-28 17:34:37
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- Some thoughts on the world model for robot operation
- In recent years, the popularity of world models seems to play some vital role in robot operation. For embodied intelligence, manipulation is the most important point to break through at this stage. Especially for the following longhorizon tasks, how to build a robot "cerebellum" to achieve various complex operating requirements is the most urgent problem that needs to be solved at the moment. Is it necessary to split the skill into atomic operations? When using LM to apply to robots, a common approach is to provide various APIs in the context, and then let LLM automatically write planning code according to the task prompt. Please refer to the article: The advantage of this method is that it is very intuitive and can be clearly understood Master the breakdown of tasks
- AI 835 2024-04-28 17:31:10
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- Yuanxiang's first multi-modal large model XVERSE-V is open source, refreshing the list of authoritative large models, and supports any aspect ratio input
- 83% of the information humans obtain comes from vision. Large multi-modal models of graphics and text can perceive richer and more accurate real-world information and build more comprehensive cognitive intelligence, thus taking greater steps towards AGI (Artificial General Intelligence). Yuanxiang today released the multi-modal large model XVERSE-V, which supports image input with any aspect ratio and leads in mainstream evaluations. This model is fully open source and available for unconditional free commercial use, continuing to promote R&D and application innovation for a large number of small and medium-sized enterprises, researchers and developers. XVERSE-V has excellent performance, surpassing open source models such as Yi-VL-34B, wall-facing intelligent OmniLMM-12B and DeepSeek-VL-7B in a number of authoritative multi-modal evaluations, and in the comprehensive ability evaluation MMBen
- AI 780 2024-04-28 16:43:08
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- Let large models no longer be 'big Mac'. This is the latest review of efficient fine-tuning of large model parameters.
- The AIxiv column is a column where this site publishes academic and technical content. In the past few years, the AIxiv column of this site has received more than 2,000 reports, covering top laboratories from major universities and companies around the world, effectively promoting academic exchanges and dissemination. If you have excellent work that you want to share, please feel free to contribute or contact us for reporting. Submission email: liyazhou@jiqizhixin.com; zhaoyunfeng@jiqizhixin.com. Recently, large-scale AI models such as large language models and Vincentian graph models have developed rapidly. Under this situation, how to adapt to rapidly changing needs and quickly adapt large models to various downstream tasks has become an important challenge. Limited by computing resources, traditional full-parameter micro
- AI 1259 2024-04-28 16:04:01
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