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- The first GPU high-level language, massive parallelism is like writing Python, has received 8500 stars
- After nearly 10 years of unremitting efforts and in-depth research on the core of computer science, people have finally realized a dream: running high-level languages on GPUs. Last weekend, a programming language called Bend sparked heated discussions in the open source community, and the number of stars on GitHub has exceeded 8,500. GitHub: https://github.com/HigherOrderCO/Bend As a massively parallel high-level programming language, it is still in the research stage, but the ideas proposed have already surprised people. With Bend you can write parallel code for multi-core CPU/GPU without having to be a C/CUDA expert with 10 years of experience, it feels like Python
- AI 1134 2024-06-07 12:03:58
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- Deploy Elasticsearch based on memory storage - 100 million+ pieces of data, full-text search 100ms response
- 1. Mount the memory storage directory on the host. Create a directory for mounting mkdir/mnt/memory_storage. Mount the tmpfs file system mount-ttmpfs-osize=800Gtmpfs/mnt/memory_storage. The storage space will be used on demand, that is, when using 100G storage. It will occupy 100G of memory. There is 2T memory on the host node, and 800G memory is allocated here to store Elasticsearch data. Create the directory mkdir/mnt/memory_storage/elasticsearch-data-es-jfs-prod-es-defaul in advance
- AI 540 2024-06-07 11:11:48
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- Karpathy's new tutorial goes viral, and netizens rush to give him H100: Recreate GPT-2 training from scratch
- The master Karpathy is no longer satisfied with using C language to create Llama! The latest challenge he gave himself: to reproduce the classic results of OpenAI, starting with the basic version of GPT-2. The success of the challenge itself is not unexpected, but it only cost 20 US dollars and 90 minutes to complete the training, and the loss and evaluation exceeded the original version, just! have! point! Pass! point! Got it! . Not only that, he wrote a complete tutorial on the reproduction process, and sure enough, it became popular again. Since Karpathy rented the A100 cloud service himself, training the 124M version cost US$20. However, someone followed the tutorial and ran with H100. Not only did the training time become shorter, but it also saved money: it was completed in 43 minutes and only cost 14 US dollars. In addition, Karpathy also paid 2 out of his own pocket
- AI 504 2024-06-07 10:29:25
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- Seven Cool GenAI & LLM Technical Interview Questions
- 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
- AI 616 2024-06-07 10:06:29
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- Deploy large language models locally in OpenHarmony
- This article will open source the results of "Local Deployment of Large Language Models in OpenHarmony" demonstrated at the 2nd OpenHarmony Technology Conference. Open source address: https://gitee.com/openharmony-sig/tpc_c_cplusplus/blob/master/thirdparty/InferLLM/docs/ hap_integrate.md. The implementation ideas and steps are to transplant the lightweight LLM model inference framework InferLLM to the OpenHarmony standard system, and compile a binary product that can run on OpenHarmony. InferLLM is a simple and efficient L
- AI 942 2024-06-07 10:02:23
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- Focusing on innovation, Intel launches new Xeon® brand strategy
- Brand is a symbol of corporate mission and development, and also carries product characteristics and market recognition. Today, at the launch of the Intel® Xeon® 6 energy-efficient core processor at the Intel GTC Technology Experience Center, Brett Hannath, global vice president and chief marketing officer of Intel Corporation, announced the launch of the new Intel® Xeon® brand. Brett Hannath said that the new Intel® Xeon® brand strategy will focus on innovation, give product brand attributes with more concise naming and deeper meaning, and enhance the recognition of the Xeon brand in the market. Through the integration of innovative technologies, high performance, high efficiency, high quality and high safety features, we create a new experience for industry partners and users. Since its introduction in 1998, the Intel® Xeon® brand
- AI 936 2024-06-07 09:29:48
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- High-gloss reflective terminator? Google NeRF-Casting: Ray tracing can do it!
- NeRF is no longer "afraid" of near specular reflections. Early NeRF variants used multilayer perceptrons (MLPs) to map from 3D coordinates to volumetric density and viewpoint-dependent color, but representing detailed 3D geometry and color required training of large MLPs and evaluation is extremely slow. Recent work has focused on making NeRF more efficient by replacing large MLPs with voxel grid-like data structures or a combination of grids and small MLPs. While scalable to represent detailed large-scale scenes, its advantages are limited to three-dimensional geometry and predominantly diffuse color. Expanding NeRF's ability to model the viewpoint-dependent appearance of reality remains a challenge. The current advanced model for view synthesis of shiny objects has limitations in two aspects: it can only synthesize distant ambient light
- AI 1239 2024-06-07 09:27:53
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- LLM | Yuan 2.0-M32: Expert Mixture Model with Attention Routing
- Picture 1. The conclusion is written above. Yuan+2.0-M32 is an infrastructure, similar to Yuan-2.0+2B, using an expert hybrid architecture containing 32 experts. 2 of these experts are active. An expert hybrid architecture containing 32 experts is proposed and adopted to select experts more efficiently. Compared with the model using the classic routing network, the accuracy rate is improved by 3.8%. Yuan+2.0-M32 is trained from scratch, using 2000B tokens, and its training consumption is only 9.25% of that of a dense ensemble model of the same parameter size. In order to better select experts, the attention router is introduced, which has the ability to sense quickly and thus enable better selection of experts. Yuan2.0-
- AI 632 2024-06-07 09:06:30
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- Constructing Scaling Law from 80 models: a new work by a Chinese doctoral student, highly recommended by the author of the thinking chain
- In the field of AI, scaling laws (Scalinglaws) are a powerful tool for understanding LM scaling trends. They provide a guideline for researchers. This law provides an important guide for understanding how the performance of language models changes with scale. But unfortunately, scaling analysis is not common in many benchmarking and post-training studies because most researchers do not have the computational resources to build scaling laws from scratch, and open models are trained on too few scales to make reliable scaling predictions. . Researchers from Stanford University, University of Toronto and other institutions have proposed an alternative observation method: Observational Scaling Laws, which combines the functions of language models (LM) with cross-multiple models.
- AI 434 2024-06-06 20:40:36
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- Reshaping the cloud 'build” experience in the era of generative AI
- In the era of generative AI, the changes in the cloud computing industry are accelerating across the board. The time to build a new cloud has arrived. As a developer, how can we adapt to technological innovations with ease? How to quickly seize new technology opportunities to get started and grow quickly? Join the 2024 Amazon Cloud Technology China Summit, a must-go event for developers, which can help you answer your questions and get rewards! Amazon Cloud Technology is reshaping the one-stack construction experience of development, operation and maintenance, and optimization in the generative AI era on the cloud. At this summit, we will bring you a new developer generative AI exploration journey, including immersive star products Experience, hands-on special training and peak challenges, skills certification and free learning, technology forward-looking sharing, global community leader dialogue, developer creative market, etc., help developers enjoy unlimited
- AI 848 2024-06-06 18:48:01
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- Human preference is the ruler! SPPO alignment technology allows large language models to compete with each other and compete with themselves
- 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 Richard Sutton made this evaluation in "TheBitterLesson": "The most important lesson that can be drawn from 70 years of artificial intelligence research is that those general methods that use computing will eventually is the most effective and has the advantage
- AI 475 2024-06-06 18:32:31
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- The visual representation model vHeat inspired by physical heat transfer is here. It attempts to break through the attention mechanism and has both low complexity and global receptive field.
- 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 the original members of VMamba. The first author Wang Zhaozhi is a 2022 jointly trained doctoral student between the University of Chinese Academy of Sciences and Pengcheng Laboratory, and the co-author Liu Yuesi Direct PhD candidate from the University of Chinese Academy of Sciences in 2021. Their main research direction is visual
- AI 549 2024-06-06 17:28:46
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- DenserRadar: 4D millimeter wave radar point cloud detector based on dense LiDAR point cloud
- Original title: DenserRadar: A4Dmillimeter-waveradarpointclouddetectorbasedondenseLiDARpointclouds Paper link: https://arxiv.org/pdf/2405.05131 Author affiliation: Tsinghua University Paper idea: 4D millimeter wave (mmWave) radar is known for its robustness in extreme environments and broad Detection range and the ability to measure speed and altitude have shown significant potential to enhance perception when autonomous driving systems face corner-cases. However, the inherent sparsity and noise limitations of 4D millimeter wave radar point clouds
- AI 786 2024-06-06 14:10:54
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- The evaluation results of the bean bag large model are revealed, which is 19% higher than the previous generation 'Skylark'
- Recently, the large bean bag model was officially released at the Volcano Engine Power Conference. While the price reduction trend of large models is promoted at ultra-low prices, Doubao’s model capabilities have also attracted industry attention. In a product information of Volcano Engine, the Doubao Model team released some of the internal test results of the first phase: on the public evaluation sets of 11 mainstream industries such as MMLU, BBH, GSM8K, HumanEval, etc., the total score of Doubao-pro-4k It scored 76.8 points, which is a 19% increase compared to the 64.5 points of the previous generation model Skylark 2. This is also better than other domestic models tested during the same period. This evaluation was completed in May this year and mainly included nine domestic large language models including Universal Model Pro, Skylark2, and
- AI 367 2024-06-06 13:45:41
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- Yann LeCun: ViT is slow and inefficient. Real-time image processing still depends on convolution.
- In the era of unification of Transformers, is it still necessary to study the CNN direction of computer vision? At the beginning of this year, OpenAI’s large video model Sora made the VisionTransformer (ViT) architecture popular. Since then, there has been an ongoing debate about who is more powerful, ViT or traditional convolutional neural network (CNN). Recently, Turing Award winner and Meta chief scientist Yann LeCun, who has been active on social media, also joined the discussion on the dispute between ViT and CNN. The cause of this incident was that Harald Schäfer, CTO of Comma.ai, was demonstrating his latest research. He (like many recent AI scholars) cue Yann LeCun's expression, although
- AI 1060 2024-06-06 13:25:02
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