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- Shanshu Technology releases new intelligent modeling and computing products, opening a new chapter in artificial intelligence applications
- On July 3, the "Intelligent Computing and Decision Technology Forum" co-organized by the Global Digital Economy Conference Organizing Committee, Beijing Municipal Bureau of Economy and Information Technology, Beijing Chaoyang District People's Government, and Shanshu Technology came to a successful conclusion in Beijing. With the theme of "Innovative Intelligent Computing Engine to Create Enterprise Intelligent Productivity", the forum invited relevant government leaders, internationally renowned scholars, university professors, corporate technical experts, investment institutions and other academic and industrial elites to gather together to discuss intelligent computing and Decision-making technology frontiers and industrial innovation, exploring how to use artificial intelligence technology to accelerate the construction of a modern industrial system, promote the deep integration of the digital economy and the real economy, and contribute to the high-quality development of our country's economy. Forward-looking guidance at the conference to inspire the future
- AI 669 2024-07-17 02:36:41
- CVPR'24 Highlight | One framework to generate character movements, down to hand movements
- 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 author of this article, Jiang Nan, is a second-year doctoral student in the School of Intelligence at Peking University. The instructor is Professor Zhu Yixin. He is jointly conducting research work with Dr. Huang Siyuan from the Beijing Institute of General Artificial Intelligence. His research focuses on human-object interaction understanding and digital human action generation, and he was awarded the title of ICCV
- AI 912 2024-07-17 02:09:30
- Moka CTO Liu Hongze: In the era of large models, organizations and talent structures will usher in new changes
- AI technology empowers the HR industry: MokaAscend2024 Product Launch With the rapid development of AI technology, especially the emergence of large models, AI is bringing profound changes to various industries, and the HR industry is no exception. MokaAscend2024 Product Launch Conference Recently, HRSaaS company Moka officially held the MokaAscend2024 product launch conference. At the meeting, Moka partner and CTO Liu Hongze shared Moka’s technological innovation and application practices in the field of AI. AI native as the concept, empowering business scenarios With AI native as the concept, in-depth business scenarios, MokaEva's capabilities continue to evolve, not only completing the upgrade from smart interviews to smart recruitment solutions, but also empowering
- AI 700 2024-07-17 02:01:11
- The author of ControlNet has another hit! The whole process of generating a painting from a picture, earning 1.4k stars in two days
- It is also a Tusheng video, but PaintsUndo has taken a different route. ControlNet author LvminZhang started to live again! This time I aim at the field of painting. The new project PaintsUndo has received 1.4kstar (still rising crazily) not long after it was launched. Project address: https://github.com/lllyasviel/Paints-UNDO Through this project, the user inputs a static image, and PaintsUndo can automatically help you generate a video of the entire painting process, from line draft to finished product. follow. During the drawing process, the line changes are amazing. The final video result is very similar to the original image: Let’s take a look at a complete drawing.
- AI 230 2024-07-17 01:56:08
- How to Spot Fake ChatGPT Apps on the Apple App Store
- Have you ever searched for ChatGPT on the App Store and found multiple apps claiming to be the official ones? Unfortunately, most of them are dangerous for your iPhone. But how do you spot a fake ChatGPT app on the App Store? Let's find out.
- AI 249 2024-07-17 01:30:50
- Predicting discrete-time bifurcations through deep learning
- Editor | Cabbage Leaf Many natural and man-made systems are susceptible to critical transitions—sudden and potentially disruptive changes in dynamics. Deep learning classifiers can provide early warning signals for critical transitions by learning common features of bifurcations from large simulated training data sets. So far, classifiers have only been trained to predict continuous-time bifurcations, ignoring the rich dynamics that characterize discrete-time bifurcations. Here, Thomas M. Bury's research team at McGill University trained a deep learning classifier to provide early warning signals for five local discrete-time bifurcations of codimension one. They used simulated data from discrete-time models used in physiology, economics and ecology as well as spontaneous
- AI 623 2024-07-16 21:27:51
- SIGGRAPH2024｜Shanghai University of Science and Technology and Yingmu jointly proposed DressCode: generating 3D clothing patterns from text
- 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 3D generation is one of the most eye-catching topics in the fields of generative artificial intelligence and computer graphics. 3D generation that meets film, television, and game standards is particularly concerned by the industry. In the production process, 3D assets of general categories are often produced through manual modeling or scanning.
- AI 331 2024-07-16 21:04:28
- Li Feifei's team's new work: brain-controlled robots do housework, giving brain-computer interfaces the ability to learn with few samples
- Those who can use their brains never use their hands. In the future, you may be able to ask a robot to do your housework for you with just a thought. The NOIR system recently proposed by the team of Wu Jiajun and Li Feifei of Stanford University allows users to control robots to complete daily tasks through non-invasive electroencephalography devices. NOIR decodes your EEG signals into a library of robotic skills. It can now complete tasks such as cooking sukiyaki, ironing clothes, grating cheese, playing tic-tac-toe, and even petting a robot dog. This modular system has powerful learning capabilities and can handle complex and varied tasks in daily life. The Brain-Robot Interface (BRI) is a masterpiece of human art, science, and engineering. We’ve seen it in countless works of science fiction and creative art, such as The Matrix
- AI 992 2024-07-16 20:38:02
- The first AI Mathematical Olympiad competition plan was announced: the four winning teams all chose the domestic model DeepSeekMath
- The winning AI Mathematical Olympiad model is released! A few days ago, with the announcement of the list, there was a lot of discussion about the progress award of the world's first AI Mathematics Olympiad (AIMO). A total of 5 teams won this competition. The Numina team won the first place, CMU_MATH ranked second, afterexams temporarily ranked third, and the codeinter and Conor#2 teams ranked fourth and fifth respectively. Image source: https://www.kaggle.com/c/ai-mathematical-olympiad-prize/leaderboard This result once surprised Tao Zhexuan. At that time, only the official list of winners was announced.
- AI 847 2024-07-16 18:14:57
- Hot GPTs experience report: Create exclusive GPT, spring is coming for people who don't understand code
- Getting closer to AI agents. If OpenAI’s developer conference is like a stone hitting the water, when it’s over, ripples are spreading in all directions. Not only does GPT go a step further in integration, eliminating the need to call it step by step, it will also become a powerful tool that everyone can develop. Even if you don’t know coding or have basic computer-related knowledge, you can easily build it. Official blog: https://openai.com/blog/introducing-gpts It seems that we are not far away from the ultimate imagination of AI-"AI intelligent agent". The definition of this word is still vague, but it roughly refers to an autonomous AI program that can independently achieve a goal after being given one. In the past few months, there have been
- AI 374 2024-07-16 17:23:42
- DeepMind develops neural network variational Monte Carlo for quantum chemical calculations
- Editor | However, quantum chemical calculations of the ground state properties of positron-molecule complexes are challenging. Here, researchers from DeepMind and Imperial College London tackle this problem using a recently developed Fermionic Neural Network (FermiNet) wave function that does not rely on a basis set. FermiNet was found to produce highly precise, and in some cases state-of-the-art, ground state energies in a range of atoms and small molecules with a variety of qualitative positron binding properties. Researchers calculated the binding energy of the challenging nonpolar benzene molecule and found that it was in high agreement with experimental values.
- AI 407 2024-07-16 15:26:30
- Llama molecule embedding is better than GPT, can LLM understand molecules? Meta defeated OpenAI in this round
- Editor | Radish Skin Large language models (LLMs) such as OpenAI's GPT and MetaAI's Llama are increasingly recognized for their potential in the field of cheminformatics, particularly in understanding the Simplified Molecular Input Line Input System (SMILES). These LLMs are also able to decode SMILES strings into vector representations. Researchers at the University of Windsor in Canada compared the performance of GPT and Llama with pretrained models on SMILES for embedding SMILES strings in downstream tasks, focusing on two key applications: molecular property prediction and drug-drug interaction prediction. The study uses "Canlargelanguagemod"
- AI 504 2024-07-16 13:33:18
- For the first time, neural activation of language has been localized to the cellular level
- The highest-resolution map of neurons encoding word meaning to date is here. 1. Humans can access rich and subtle meanings through language, which is crucial to human communication. Despite increasing understanding of the brain regions that support language and semantic processing, much remains unknown about neurosemantic derivations at the cellular level. Recently, a research paper published in the journal Nature discovered the fine cortical representation of semantic information by single neurons by tracking the activity of neurons during natural speech processing. The paper is titled "Semantic encoding for language understanding at single-cell resolution." 1. Paper address: https://www.nature.com/articles/s41586-024-07643-
- AI 749 2024-07-16 12:12:59
- Academician E Weinan leads the new work: Large models not only have RAG and parameter storage, but also a third kind of memory
- The 2.4B Memory3 achieves better performance than the larger LLM and RAG models. In recent years, large language models (LLMs) have received unprecedented attention due to their extraordinary performance. However, the training and inference costs of LLM are high, and people have been trying to reduce the cost through various optimization methods. In this article, researchers from Shanghai Algorithm Innovation Research Institute, Peking University and other institutions were inspired by the memory hierarchy of the human brain. They reduced this problem by equipping LLM with explicit memory (a cheaper memory format than model parameters and RAG). cost. Conceptually, LLM can enjoy smaller parameter sizes, training costs, and inference costs since most of its knowledge is externalized into explicit memory. Paper address: https:
- AI 429 2024-07-16 11:57:51
- Peking University's embodied intelligence team proposes demand-driven navigation to align human needs and make robots more efficient
- Imagine if a robot could understand your needs and work hard to meet them, wouldn't it be great? If you want a robot to help you, you usually need to give a more precise command, but the actual implementation of the command may not be ideal. If we consider the real environment, when the robot is asked to find a specific item, the item may not actually exist in the current environment, and the robot cannot find it anyway; but is it possible that there is another item in the environment, which is related to the user? Does the requested item have similar functions and can also meet the user's needs? This is the benefit of using "requirements" as task instructions. Recently, Peking University Dong Hao’s team proposed a new navigation task—demand-driven navigation (
- AI 948 2024-07-16 11:27:39
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