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- Why does the database need to be integrated + AI? Oracle Oracle 23ai gave the answer
- In 2017, a paper called "AttentionisAllYouNeed" proposed a new neural network architecture: Transformer. Seven years later, Transformer has become the core of generated AI and is leading today's technology wave. According to Wu Chengyang, Vice President of Yiguwen Company and Managing Director of China, the most important thing about the emergence of a new technology is not the technology itself, but the value that the technology can bring to users. In the field of data, data as a new type of asset has become a consensus in the industry. How to closely integrate with AI at the data level and maximize the value of data is the core issue to be solved at the moment. Oracle's recently released OracleDatabase23ai is precisely for this purpose
- AI 313 2024-06-04 12:25:07
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- Spring Boot3.x connects with Alibaba Cloud face recognition service to implement face recognition
- This topic is dedicated to an in-depth discussion of how to implement efficient face detection and face recognition systems through the SpringBoot3.x framework and OpenCV library. Through 10 systematic articles, from basic concepts to advanced applications, combined with code examples and practical cases, we will gradually guide you to master the entire process of building a complete face detection and recognition system from scratch. Alibaba Cloud face recognition service is an artificial intelligence service based on deep learning, which can provide functions such as face detection, face attribute analysis, and face comparison. Compared with other services, Alibaba Cloud has become the first choice of many enterprises in China due to its ultra-high accuracy, low latency, strong technical support and compliance. Its advantages include: High accuracy: Relying on Alibaba’s strong artificial intelligence research capabilities, Alibaba
- AI 309 2024-06-04 11:53:12
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- Driven by generative AI, global public cloud spending will grow to $675.4 billion in 2024
- According to Gartner's recent forecast, driven by production artificial intelligence (GenAI) and application modernization, global users' spending on public cloud services will increase by US$6.754 billion this year. This figure represents an increase of 20.4% compared with last year's US$5.61 billion. Global public cloud spending is expected to reach $825 billion by 2025 (see Figure 1), and this ongoing growth trend shows no signs of abating. This number marks a new milestone in the field of public cloud services. Public cloud services are becoming increasingly popular among enterprises for many reasons. First, it provides elasticity and flexibility, allowing enterprises to scale up or down their computing and storage resources based on actual needs. Secondly, public cloud services can provide more
- AI 772 2024-06-04 10:26:39
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- OpenAI, Microsoft, Zhipu AI and other 16 companies around the world signed the Frontier Artificial Intelligence Security Commitment
- The security issues of artificial intelligence (AI) are being discussed globally with unprecedented attention. Before OpenAI founder and chief scientist Ilya Sutskever and OpenAI Super Alignment team co-leader Jan Leike left OpenAI one after another, Leike even published a series of posts on X, saying that OpenAI and its leadership ignored security in favor of shiny products. This has attracted widespread attention in the industry, highlighting the seriousness of current AI security issues to a certain extent. On May 21, an article published in Science magazine called on world leaders to take stronger action against the risks of artificial intelligence (AI). The article points out that authoritative scientists and
- AI 383 2024-06-03 22:24:44
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- Explainable AI: Explaining complex AI/ML models
- Translator | Reviewed by Li Rui | Chonglou Artificial intelligence (AI) and machine learning (ML) models are becoming increasingly complex today, and the output produced by these models is a black box – unable to be explained to stakeholders. Explainable AI (XAI) aims to solve this problem by enabling stakeholders to understand how these models work, ensuring they understand how these models actually make decisions, and ensuring transparency in AI systems, Trust and accountability to address this issue. This article explores various explainable artificial intelligence (XAI) techniques to illustrate their underlying principles. Several reasons why explainable AI is crucial Trust and transparency: For AI systems to be widely accepted and trusted, users need to understand how decisions are made
- AI 800 2024-06-03 22:08:09
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- CVPR 2024 | Is there only single-person data in the synthetic video data set? M3Act solves the problem of crowd behavior labeling
- 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 Paper link: https://arxiv.org/abs/2306.16772 Project link: https://cjerry1243.github.io/M3Act/ Paper title: M3Act:
- AI 581 2024-06-03 22:02:59
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- How can AI make robots more autonomous and adaptable?
- In the field of industrial automation technology, there are two recent hot spots that are difficult to ignore: artificial intelligence (AI) and Nvidia. Don’t change the meaning of the original content, fine-tune the content, rewrite the content, don’t continue: “Not only that, the two are closely related, because Nvidia is expanding beyond just its original graphics processing units (GPUs). The technology extends to the field of digital twins and is closely connected to emerging AI technologies. "Recently, NVIDIA has reached cooperation with many industrial companies, including leading industrial automation companies such as Aveva, Rockwell Automation, Siemens and Schneider Electric, as well as Teradyne Robotics and its MiR and Universal Robots companies. Recently,Nvidiahascoll
- AI 1063 2024-06-03 19:18:05
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- Hype and reality of AI agents: Even GPT-4 cannot support it, and the success rate of real-life tasks is less than 15%
- According to the continuous evolution and self-innovation of large language models, performance, accuracy, and stability have been greatly improved, which has been verified by various benchmark problem sets. However, for existing versions of LLM, their comprehensive capabilities do not seem to be able to fully support AI agents. Multi-modal, multi-task, and multi-domain inference have become necessary requirements for AI agents in the public media space, but the actual effects displayed in specific functional practices vary greatly. This seems to once again remind all AI robot startups and large technology giants to recognize the reality: be more down-to-earth, don’t spread your business too big, and start with AI enhancement functions. Recently, a blog about the gap between the propaganda and real performance of AI agents emphasized a point:
- AI 1005 2024-06-03 18:38:42
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- Read this article to understand several common LangChain alternatives
- Hellofolks, I am Luga. Today we will talk about technologies related to the artificial intelligence (AI) ecological field - the LLM development framework. In the field of LLM (large-scale language model) application development, open source frameworks play a vital role and provide powerful tool support for developers. As a leader in this field, LangChain has won widespread praise for its innovative design and comprehensive functionality. But at the same time, some alternative frameworks have also emerged, providing better choices for needs in different scenarios. After all, any framework inevitably has certain limitations. For example, the speed abstraction of LangChain in some cases may make it more difficult to get started, the debugging experience needs to be improved, and the quality of some codes also deserves improvement.
- AI 1399 2024-06-03 18:25:26
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- 2024 Future Automobile Pioneer Conference丨Gu Weihao: AI large model is the only path to realize autonomous driving
- On June 1st, Hao Mo Zhixing CEO Gu Weihao was invited to attend the 2024 (Second) Future Automobile Pioneers Conference and delivered a keynote speech "In the Autonomous Driving 3.0 Era, Large Models Reshape the Intelligent Automobile Route". Gu Weihao said: "AI large models are the only way to truly realize autonomous driving, and end-to-end will be a very important technical direction in the future. End-to-end is not only the optimization of the model end, but also requires the supply of data and the support of computing power. "Haimo DriveGPT has been exploring end-to-end solutions since 2022, and once applied, it will bring very amazing results." (Gu Weihao, CEO of Haimou Zhixing, was invited to attend the 2024 Future Automobile Pioneer Conference). With the theme of "Struggle for Current", in 6
- AI 866 2024-06-03 17:18:53
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- OpenAI and Google have made big moves in two consecutive days, both of which want to make AI assistants 'smart'
- After seeing the spring release of OpenAI yesterday, it is not difficult to guess that at today’s Google I/O conference, there will definitely be an introduction to AI assistants. After all, Altman, who released GPT-4o before the Google I/O conference, has shown full pertinence. With Altman's methods, he is naturally confident to achieve precise strikes and put this "red-blue confrontation" Carry on to the end. Sure enough, at the conference, Google CEO Pichai invited DeepMind founder Demis. Google's new AI assistant ProjectAstra was unveiled by Demis, who made his debut at the Google I/O conference. What is ProjectAstra? ProjectAstr
- AI 300 2024-06-03 15:23:07
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- Essential Skills and Traits of a Chief Artificial Intelligence Officer
- Chief Artificial Intelligence Officers (CAIOs) require multidimensional skills to drive innovation, build and lead an AI-ready culture, and leverage complex and rapidly evolving technologies to achieve tangible organizational results. In addition, CAIOs should also have strong leadership capabilities and be able to drive strategic planning and implementation of AI in an ever-changing environment. CAIOs require deep business knowledge and technical background to understand the rapid rise of reconciliation AI, especially generative AI, has prompted many organizations to hire or promote chief artificial intelligence officers (CAIOs). So far, many positions have been concentrated at technology vendors, and similar positions are emerging in government entities following the recent enactment of several AI bills. But in the next few years, the number of CAIO positions in corporate organizations is expected to continue to increase.
- AI 812 2024-06-03 12:32:13
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- Talking to the Machine: Ten Secrets of Prompt Engineering Revealed
- To learn more about AIGC, please visit: 51CTOAI.x community https://www.51cto.com/aigc/ The power of prompts is amazing. We only need to throw out a few words that approximate human language to get a Well-formatted and structured answers. No topic is obscure and no fact is out of reach. At least as long as it is part of the training corpus and approved by the model's shadow controller (ShadowyController), we can get the answer with a simple prompt. However, some people have begun to notice that the magic of prompts is not absolute. Our cues don’t always produce the results we want. Some prompt languages are even better than others
- AI 378 2024-06-03 10:53:11
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- Microsoft unveils a $3.3 billion AI infrastructure investment plan to expand data center capacity in the United States
- Microsoft will launch a four-part investment strategy by the end of 2026. The tech company will build a data center campus and plans to upskill more than 10 million people across the state in GenAI by 2030. AWS, Google, and Microsoft are developing comprehensive infrastructure plans to support growing demand for computing power and investing in states across the United States. Earlier this year, AWS announced a $210 million investment in data centers in Indonesia and Mississippi. This is the largest capital investment in either state. Google said last month it planned to invest $3 billion to build and expand data center campuses in Virginia and Indiana. A report released by SynergyResearchGroup in October
- AI 1120 2024-06-03 10:52:37
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- An American professor used his 2-year-old daughter to train an AI model to appear in Science! Human cubs use head-mounted cameras to train new AI
- Unbelievably, in order to train an AI model, a professor from the State University of New York strapped a GoPro-like camera to his daughter’s head! Although it sounds incredible, this professor's behavior is actually well-founded. To train the complex neural network behind LLM, massive data is required. Is our current LLM training process necessarily the simplest and most efficient way? Certainly not! Scientists have discovered that in human toddlers, the brain absorbs water like a sponge, quickly forming a coherent worldview. Although LLM performs amazingly at times, over time, human children become smarter and more creative than the model! The secret of children mastering language. How to train LLM in a better way? When scientists are puzzled by the solution,
- AI 700 2024-06-03 10:08:09
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