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- WAIC 2024 Embodied Intelligence Collection｜Gathering of top celebrities, exhibition of all categories of achievements: Innovation in embodied intelligence technology opens a new era of AI robots
- Embodied Intelligence: The new era of intelligent robots The embodied intelligence industry represents the in-depth integration and development of two cutting-edge technologies, artificial intelligence and robotics, allowing robots to achieve natural interaction with the environment through the collaboration of perception, cognition and action. The rise of embodiment means that artificial intelligence is moving from single information processing to more complex and multi-dimensional scene fields, opening a new era of deep integration of intelligent systems and human society. Key issues, application scenarios and cutting-edge results of embodied intelligence The 2024 World Artificial Intelligence Conference and High-Level Conference on Global Governance of Artificial Intelligence (hereinafter referred to as "WAIC2024") will focus in depth on the development trends of embodied intelligence, with major forums and rich intelligent robots Exhibits of innovative achievements provide a glimpse into the huge development potential of the embodied intelligence industry and jointly chart the era of intelligent robots.
- AI 951 2024-07-18 00:17:51
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- These Features Make the ChatGPT Desktop App Better Than the Website
- Thanks to the ChatGPT app for macOS, you can now launch ChatGPT from any window on your Mac and use Voice Mode. OpenAI also added a few media attachment options to the app that aren't available on the website, such as screenshots and access t
- AI 1297 2024-07-17 22:50:21
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- Topping the list of open source AI software engineers, UIUC's agent-less solution easily solves SWE-bench real programming problems
- 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 The authors of this paper are all from the team of teacher Zhang Lingming at the University of Illinois at Urbana-Champaign (UIUC), including: Steven Code repair; Deng Yinlin, fourth-year doctoral student, researcher
- AI 1239 2024-07-17 22:02:05
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- SOTA performance, Xiamen multi-modal protein-ligand affinity prediction AI method, combines molecular surface information for the first time
- 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
- AI 1321 2024-07-17 18:37:10
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- Exploration and practice of multi-modal remote sensing large models, Wang Jian, head of remote sensing large models of Ant Group, brings in-depth interpretation
- On July 5, under the guidance of the World Artificial Intelligence Conference Organizing Committee Office and the People's Government of Xuhui District, Shanghai, the 2024 WAIC Yunfan Award and Artificial Intelligence Youth were hosted by the Shanghai Artificial Intelligence Laboratory, this site, and the Global University Artificial Intelligence Academic Alliance. The forum was successfully held. The forum brought together more than 30 past and new Yunfan graduates from universities, research institutions and enterprises at home and abroad, including Stanford University, Oxford University, UCLA, University of California, ETH Zurich, University of Hong Kong, Tsinghua University, Peking University, Shanghai Jiao Tong University, etc. Award winners attended the conference offline, gathering the wisdom of international young AI scientists, actively exploring the boundaries of AI capabilities, and contributing new energy to China's AI development blueprint. Wang Jianzuo, the person in charge of remote sensing large-scale models of Ant Group, serves as the 2024 WAIC Yunfan
- AI 751 2024-07-17 18:03:14
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- Quark upgrades 'Super Search Box” and launches one-stop AI service centered on AI search
- In the era of large models, how does generative AI revolutionize search products? Quark, a subsidiary of Alibaba Intelligent Information Business Group, "raised your hand to answer the question." On July 10, Quark upgraded the "Super Search Box" and launched a one-stop AI service centered on AI search, providing users with integrated information service value from retrieval, creation, summary, to editing, storage, and sharing. The new AI search box enables answering, creating, and summarizing the past. The search engine provides sorting of website lists based on keywords. Repeated selection, clicking, reading, and a large number of irrelevant results have become obstacles for users to obtain information efficiently, and it is difficult to get satisfactory answers to complex questions. The leap in AI technology has ignited a new value in search. User opens Quark version 7.0 search
- AI 625 2024-07-17 17:43:33
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- Essential AI Tools and Tips for Every Student
- Students can use AI in several smart ways to improve their learning and work more efficiently. At this point, there are heaps of AI tools students can use, covering note-taking, tutoring, and much more. But which AI tools are the best for students?
- AI 1314 2024-07-17 16:49:04
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- Completely change the language model: the new architecture TTT surpasses the Transformer, and the ML model replaces the RNN hidden state
- From 125M to 1.3B large models, the performance has been improved. It's unbelievable that this finally happened. A new large language model (LLM) architecture is expected to replace Transformer, which has been popular in the AI field so far, and its performance is better than Mamba. On Monday this week, the paper on Test-TimeTraining (TTT) became a hot topic in the artificial intelligence community. Paper link: https://arxiv.org/abs/2407.04620 The authors of this study are from Stanford University, University of California, Berkeley, University of California, San Diego, and Meta. They designed a new architecture, TTT, to replace the hidden state of RNN with a machine learning model. The module
- AI 852 2024-07-17 16:08:17
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- Single-author paper, Google proposes millions of expert Mixture, surpassing dense feedforward and sparse MoE
- Unleashing the potential to further extend the Transformer while maintaining computational efficiency. Feedforward (FFW) layers in standard Transformer architectures result in a linear increase in computational cost and activation memory as the hidden layer width increases. As the size of large language models (LLM) continues to increase, the sparse mixed expert (MoE) architecture has become a feasible method to solve this problem, which separates the model size from the computational cost. Many emerging MoE models can achieve better performance and more powerful performance at the same size. The recently discovered scaling law of fine-grained MoE suggests that higher granularity leads to better performance. However, existing MoE models are limited to a low number of experts due to computational and optimization challenges.
- AI 660 2024-07-17 14:34:17
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- Axiomatic training allows LLM to learn causal reasoning: the 67 million parameter model is comparable to the trillion parameter level GPT-4
- Show the causal chain to LLM and it learns the axioms. AI is already helping mathematicians and scientists conduct research. For example, the famous mathematician Terence Tao has repeatedly shared his research and exploration experience with the help of AI tools such as GPT. For AI to compete in these fields, strong and reliable causal reasoning capabilities are essential. The research to be introduced in this article found that a Transformer model trained on the demonstration of the causal transitivity axiom on small graphs can generalize to the transitive axiom on large graphs. In other words, if the Transformer learns to perform simple causal reasoning, it may be used for more complex causal reasoning. The axiomatic training framework proposed by the team is a new paradigm for learning causal reasoning based on passive data, with only demonstrations
- AI 1478 2024-07-17 10:14:38
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- If you want to engage in AI, don't study data science in high school: Altman and Musk finally agree now
- Whether studying data science in high school can replace mathematics? The discussion on this topic has extended to the AI circle. For the development of AI, it will be too late if we don’t strengthen basic education. While large model technology is developing rapidly and companies are competing fiercely, some people have come forward to express concerns about future talents, focusing on mathematics. Recently, the University of California (UC) system has caused an uproar with the news that it has set basic mathematics standards for incoming freshmen. With math scores declining nationwide, some educators believe standard algebra-intensive math education needs reform, both to attract more students and to help them develop relevant skills for an increasingly data-reliant future. According to some organizations, at least 17 states have now included “data science” as a possible component of high school mathematics education.
- AI 1029 2024-07-17 09:11:51
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- Xiaomi hackathon ended, and the large model 'smart helmet' won the first prize
- On July 9, 2024, the award ceremony for the Xiaomi 2024 Fifth Hackathon "Boundless Creation, Endless Creation" competition hosted by the Xiaomi Group Technical Committee was held in Beijing. Xiaomi's annual innovation competition came to a successful conclusion. This competition takes the form of 48 hours of offline concentrated coding, with the main venue in Beijing and four regional sub-venues in Wuhan, Nanjing, Shanghai and Shenzhen. 319 Xiaomi engineers from 11 major departments jointly produced 63 creative projects. New technology works, and 31 patent applications submitted. The number of applicants and the number of cross-regional teams reached a record high. At the award ceremony, Qu Heng, vice president of Xiaomi Group and chairman of the group’s technical committee, said: This hackathon is the largest in its five years.
- AI 1319 2024-07-17 09:07:55
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- Video generation new company! Cao Yue, winner of the Maar Prize and Tsinghua Special Prize, started a business, and the 'Queen of Venture Capital' bet on it
- After Dark Side of the Moon, Xu Xin, the “Queen of Venture Capital” with a vicious vision, invested in another AIGC startup company. Recently, rumors that Capital Today has laid off its primary market team have attracted attention in the industry. On the evening of July 10, Xu Xin, president of Capital Today Group, personally refuted the rumors in WeChat Moments and revealed an investment news: In May 2024, Capital Today led the early financing round of SandAI. According to IT Orange data, Beijing SandAI was founded in 2023 and is an AI startup company that aims to "do influential things in the world." Currently, SandAI mainly focuses on video generation technology similar to OpenAISora, providing users with efficient and convenient video generation services. The company’s founder and CEO Cao Yue was a former employee of Wang Hui Wen Chuang
- AI 694 2024-07-17 07:02:39
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- Gemini 1.5 Pro is installed into the robot, and it can provide concierge and guidance after visiting the company.
- Long-context large models help robots understand the world. Recently, Google DeepMind suddenly started showing off its robots. This robot can easily follow human instructions, conduct visual navigation, and use common sense reasoning to find paths in three-dimensional space. It uses the Gemini 1.5 Pro, a large model recently released by Google. When using traditional AI models, robots often have difficulty recalling environmental details due to context length limitations, but Gemini1.5Pro's million-level token context length provides robots with powerful environmental memory capabilities. In a real office scenario, engineers guided the robot around specific areas and marked key places to recall, such as "Lewis' desk" or the "temporary desk area." Transfer completed
- AI 1085 2024-07-17 05:58:40
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- ICLR2024 | Harvard FairSeg: The first large-scale medical segmentation dataset to study the fairness of segmentation algorithms
- Author | Editor Tian Yu | Baicai Ye In recent years, the issue of fairness of artificial intelligence models has received more and more attention, especially in the medical field, because the fairness of medical models is crucial to people's health and lives. High-quality medical equity datasets are necessary to advance equitable learning research. The existing medical fairness data sets are all aimed at classification tasks, and there is no fairness data set that can be used for medical segmentation. However, medical segmentation is a very important medical AI task like classification. In some scenes, segmentation is even better than Classification because of its ability to provide detailed spatial information on organ abnormalities to be evaluated by the clinician. In the latest study, Harvard-Ophthalmology at Harvard University
- AI 1305 2024-07-17 05:46:46
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