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- A single card A100 can achieve millions of token inferences, which is 10 times faster. This is Microsoft's official large model inference acceleration.
- This Microsoft research allows developers to process more than 1M of input text on a single-card machine at 10 times the speed. Large language models (LLM) have entered the era of long context processing, and the context window they support has soared from the previous 128K to the 10Mtoken level. However, due to the quadratic complexity of the attention mechanism, it can take several minutes for the model to process the input cues (i.e., the pre-population stage) and start generating the first token. As a result, the first token generation time is too long, which seriously affects the user experience, which also greatly limits the widespread application of long context LLM. For example (as shown in Figure 2a), when serving LLaMA-3-8B on a single machine equipped with A100, if it prompts that there are 300,000
- AI 825 2024-07-12 17:14:05
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- DAMO Academy releases one-stop AI video creation platform 'Xunguang' to create a new AI workflow
- This year is the first year of the explosion of AI video generation, and algorithm models and product applications represented by Sora are constantly emerging. In just a few months, we have witnessed the emergence of dozens of video generation tools, and AI-based video creation methods have begun to become popular. However, new technologies have also caused more challenges and doubts. In addition to the well-known "blind box opening" phenomenon, video content generated by AI has also been frequently criticized for its poor controllability and cumbersome processing workflow. OpenAI once invited a professional video production team to test Sora. Among them, the ShyKids team from Toronto used Sora to produce a short film with a balloon man theme. It perfectly combined creativity and AI technology, which was impressive. The entire short film is actually not
- AI 974 2024-07-12 16:24:20
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- ICLR 2024 Spotlight | No need to worry about intermediate steps, MUSTARD can generate high-quality mathematical inference data
- 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. In recent years, large language models (LLM) have made great progress in tasks such as mathematical application problems and mathematical theorem proving. Mathematical reasoning requires a rigorous, formalized multi-step reasoning process and is therefore a key milestone in the advancement of LLMs' reasoning ability, but it still faces
- AI 1103 2024-07-12 16:07:14
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- HANDS@ECCV24 Hand Symposium and Challenge, we sincerely invite submissions and participation in the competition
- Introduction The 8th HANDS will be held at ECCV24 (afternoon, September 30, Milan), including workshops and challenges. HANDS will provide a platform for related hand researchers and practitioners to share their work and discuss potential collaborations. The past seven editions of HANDS have also achieved great success. This document is a translation, please refer to the official website for information. HANDS@ECCV24 homepage: https://hands-workshop.org/ Hand seminar and submission: The seminar focuses on hand-related directions, and experts in hand-related fields will be invited to give cutting-edge reports. In particular, we sincerely invite submissions of relevant long articles. Hand Challenge: The challenge is based on the latest hand big data sets AssemblyHands and ARC
- AI 1038 2024-07-12 14:12:10
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- DALL-E 3 Now Has Integrated Editing Tools, But They Need Work
- Ever wanted to edit your DALL-E 3 creation immediately but did not know how to make the changes? OpenAI hears you and has added inline editing tools to DALL-E 3 in ChatGPT, allowing you to make tweaks to your creations without leaving the app. The
- AI 769 2024-07-12 14:10:52
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- The open source 3D medical large model SAT supports 497 organoids and has performance exceeding 72 nnU-Nets. It was released by the Shanghai Jiao Tong University team.
- Author | Shanghai Jiao Tong University, Shanghai Artificial Intelligence Laboratory Editor | ScienceAI Recently, the joint team of Shanghai Jiao Tong University and Shanghai Artificial Intelligence Laboratory released a large 3D medical image segmentation model SAT (SegmentAnything in radiology scans, driven by Textprompts), which can be used in 3D medical images (CT, MR, PET), based on text prompts, universal segmentation of 497 types of organs/lesions in the human body is achieved. All data, codes, and models are open source. Paper link: https://arxiv.org/abs/2312.17183 Code link: https://github.com/zhao
- AI 623 2024-07-12 10:52:01
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- Generate four-dimensional content in a few minutes and control motion effects: Peking University and Michigan propose DG4D
- 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, Dr. Pan Liang, is currently a Research Scientist at the Shanghai Artificial Intelligence Laboratory. Previously, from 2020 to 2023, he served as a Research Fellow at the S-Lab of Nanyang Technological University in Singapore.
- AI 1161 2024-07-12 09:30:21
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- Terence Tao supports it! AI Mathematical Olympiad Progress Award Announced, with Prizes of More than US$1 Million
- How can a large model do math problems? You might as well let it participate in this level of competition. "The preliminary results of the AI Mathematical Olympiad (AIMO Progress Award) have been announced. According to the leaderboard data, it currently appears that the winning program correctly answered 29/50 questions in the private test, which is a higher than expected result "Just now, Tao Zhexuan announced the news on his personal blog. AIMO originated from XTXMarkets, a non-bank financial institution that specializes in machine learning quantitative trading. It mainly allows participants to use AI models to solve international mathematical problems. The goal of this progress award is to create algorithms and models that can solve complex mathematical problems written in LaTeX format. This helps to promote the mathematical reasoning capabilities of artificial intelligence models and promote the development of cutting-edge knowledge.
- AI 832 2024-07-12 08:22:13
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- Revealed: Step Star trillion MoE+ multi-modal large model matrix unveiled
- At the 2024 World Artificial Intelligence Conference, many people lined up in front of a booth just to let the big AI model "arrange" an errand for them in heaven. Process: Provide personal photos to generate fairyland image photos (referring to the style of "Havoc in Heaven") Interactive plot selection and conversation sessions evaluate MBTI personality types based on choices and answers. "Arrange" heavenly errands based on personality types. Experience method: on-site queuing online experience ( Scan the QR code below) The large model startup company Step Star announced its big move. The AI interactive experience "AI + Havoc in Heaven" in cooperation with Shanghai Film Studio is just an appetizer for Step Star to showcase the charm of large models. During WAIC, they grandly launched the following big move: Trillion parameter MoE large model: Step-2 official version
- AI 1167 2024-07-12 05:52:58
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- ACL 2024 | Leading academic audiovisual research, Shanghai Jiao Tong University, Tsinghua University, Cambridge University, and Shanghai AILAB jointly released the academic audiovisual data set M3AV
- 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 article are from Shanghai Jiao Tong University, Tsinghua University, Cambridge University and Shanghai Artificial Intelligence Laboratory. The first author, Chen Zhe, is a PhD student at Shanghai Jiao Tong University, studying under Professor Wang Yu from the School of Artificial Intelligence of Shanghai Jiao Tong University. The corresponding author is Professor Wang Yu (homepage: https:/
- AI 1200 2024-07-12 04:11:47
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- Da Hongliang's research group at Shanghai Jiao Tong University & Shanghai AI Laboratory team released FSFP, a small sample prediction method for protein function based on language model, which was published in the Nature sub-journal
- Editor | ScienceAI Recently, the research group of Professor Hong Liang from the Institute of Natural Sciences/School of Physics and Astronomy/Zhangjiang Advanced Research Institute/School of Pharmacy of Shanghai Jiao Tong University, and Tan Pan, a young researcher from the Shanghai Artificial Intelligence Laboratory, achieved important breakthroughs in protein mutation-property prediction. . This work adopts a new training strategy, which greatly improves the performance of traditional protein pre-trained large models in mutation-property prediction using very little wet experimental data. The research results are titled "Enhancing the efficiency of protein language models with minimal wet-labdata throughfew-shot learning" and were published in
- AI 1049 2024-07-11 20:10:28
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- Zhijia Technology's paper DualBEV was selected into the top computer vision conference ECCV
- Recently, the paper "DualBEV: UnifyingDualVeiwTransformationwithProbabilisticCorrespondences" by the Zhijia Technology team was selected into the European International Conference on Computer Vision (ECCV, European Conference on Computer Vision). ECCV is one of the most influential and authoritative international conferences in the field of computer vision, and is closely related to the International Conference on Computer Vision (ICCV). It is as famous as the Conference on Computer Vision and Pattern Recognition (CVPR) and is known as one of the "three top conferences" in the field of computer vision. ECCV is held every two years, bringing together the world’s top
- AI 614 2024-07-11 18:12:18
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- The self-organizing neural network that 'grows' like a biological network and has 'structural plasticity' is here
- An important feature of biological neural networks is a high degree of plasticity, which allows natural organisms to have remarkable adaptability, and this ability affects the synaptic strength and topology of the nervous system. However, artificial neural networks are mainly designed as static, fully connected structures that can be very fragile in the face of changing environments and new inputs. Although researchers have conducted extensive research into online learning and meta-learning, current state-of-the-art neural network systems still use offline learning because this is simpler when combined with backpropagation. So, can artificial neural networks also have properties similar to high plasticity? A research team from the University of Information Technology in Copenhagen proposed a self-organizing neural network-LNDP, which can
- AI 1240 2024-07-11 17:19:10
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- The molecule is 100% effective, ligands are designed from scratch, and Hunan University proposes a fragment-based molecular characterization framework
- Editor | Applications and Challenges of KX Molecular Descriptors Molecular descriptors are widely used in molecular modeling. However, in the field of AI-assisted molecular discovery, there is a lack of naturally applicable, complete and original molecular representations, affecting model performance and interpretability. The t-SMILES framework is proposed. The fragment-based multi-scale molecular characterization framework t-SMILES solves the problem of molecular characterization. The framework uses SMILES type strings to describe molecules and supports sequence models as generative models. Code algorithm of t-SMILES t-SMILES has three code algorithms: TSSA, TSDY and TSID. Experimental results show that the molecules generated by the t-SMILES model have 100% theoretical validity and high novelty, which is better than those based on SOTASM.
- AI 646 2024-07-11 16:12:59
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- The first in the country! SenseTime releases 'Ririxin 5o', real-time multi-modal streaming interaction benchmarking GPT-4o
- July 5, 2024, Shanghai - SenseTime, a strategic partner of the 2024 World Artificial Intelligence Conference and High-Level Conference on Artificial Intelligence Global Governance (WAIC2024), held the "Love Without Boundaries·Xiang Xinli" Artificial Intelligence Forum and released the first domestic artificial intelligence The WYSIWYG model is "new every day 5o", and the interactive experience is benchmarked against GPT-4o, realizing a new AI interaction model. By integrating cross-modal information, based on various forms such as sound, text, image and video, the country's first WYSIWYG model "Ririxin 5o" brings a new AI interaction model, that is, real-time streaming multi- Modal interaction. This was also shown to everyone at the scene
- AI 1129 2024-07-11 15:52:55
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