Table of Contents
2023 Artificial Intelligence Annual Leading Enterprise TOP50
2023 Artificial Intelligence Annual Influencer TOP30
Home Technology peripherals AI Huang Wei and Yunzhisheng were successfully selected for the '2023 Artificial Intelligence Annual Selection' and won two honors

Huang Wei and Yunzhisheng were successfully selected for the '2023 Artificial Intelligence Annual Selection' and won two honors

Jan 12, 2024 pm 07:24 PM
AI Yun Zhisheng Keywords: Huang Wei

On December 14, at the MEET2024 Intelligent Future Conference hosted by Qubit, the results of the "2023 Artificial Intelligence Annual Selection" were officially announced. With its outstanding artificial intelligence technology innovation and practical application capabilities, Yunzhisheng was successfully selected into the "2023 Artificial Intelligence Annual Leading Enterprises TOP50" list. At the same time, Huang Wei, the founder and CEO of Yunzhisheng, was also included in the "2023 Artificial Intelligence Annual TOP30 Influential People" list

due to his outstanding insight, creativity and leadership.

Huang Wei and Yunzhisheng were successfully selected for the 2023 Artificial Intelligence Annual Selection and won two honors

Huang Wei and Yunzhisheng were successfully selected for the 2023 Artificial Intelligence Annual Selection and won two honors

As a well-known new media in the field of artificial intelligence and cutting-edge technology in China, the list released by Qubit has important guiding significance in the industry. This time, the "2023 Artificial Intelligence Annual Selection" is divided into three dimensions: enterprise, individual and product/solution. In the past three months, Qubits has finally selected 50 leading companies and 20 leading companies based on real data, combined with in-depth research on hundreds of artificial intelligence companies, and the opinions of dozens of well-known industry experts. The most valuable startups, 30 leaders, 10 outstanding products and 10 outstanding solutions

2023 Artificial Intelligence Annual Leading Enterprise TOP50

In the "2023 Artificial Intelligence Annual Leading Companies TOP50" list, 50 companies with hard-core technology, promising capital, customer trust, and commercial success are gathered. They are the backbone of China's AI field - technically, leading companies The latest trends such as basic large models, AI computing, embodied intelligence, spatial computing, and multi-modal interaction; in terms of scenarios, it covers current mainstream AI applications such as AIGC, autonomous driving, intelligent terminals, finance, e-commerce, logistics, security, and content communities. field. The list includes industry giants who entered the industry early and have profound influence, as well as leading representative companies with eye-catching performance in the vertical track. Yun Zhisheng is one of them.

As a pioneer in China's artificial intelligence industry, Yunzhisheng adheres to technology-driven as its core, continues to dig deep into the industry's pain points, understands industry needs, continues to rationally apply artificial intelligence technology in actual scenarios, and is committed to making artificial intelligence serve all walks of life. Bring real benefits to all industries. It is out of this original intention that Yunzhisheng released the large model of mountains and seas in May this year, opening a new chapter in the field of large models

Yunzhisheng uses the Shanhai model to provide industry solutions for the field of smart IoT, covering segmented scenarios such as knowledge management, education, vehicle and transportation. In terms of knowledge management, Yunzhisheng's KMS system can manage, share and apply proprietary knowledge, promoting the enterprise's model upgrade from "knowledge cost" to "knowledge capital". For educational scenarios, Yunzhisheng uses the Shanhai large model to implement three-level corrections including pronunciation guidance, grammar correction, and dialogue generation to help English learners improve their speaking skills. In the smart vehicle scenario, Yunzhisheng relies on the Shanhai model to deeply understand user needs and provide a one-stop voice interaction solution to achieve an ideal human-vehicle interaction experience. In smart transportation scenarios, Yunzhisheng uses large models of mountains and seas to create more humane smart customer service, providing passengers with a faster and more convenient travel experience

Targeting the smart medical field, Yunzhisheng combines past data and experience accumulation, and based on the Shanhai model, launched three medical product applications: outpatient medical record generation system, surgical record writing assistant and commercial insurance intelligent claims system, continuing to lead Smart medical innovation and development

2023 Artificial Intelligence Annual Influencer TOP30

Technological trends are changing drastically, and their essence cannot be separated from the promotion of "people". In this special year, there are many rookies and veterans in the industry, which have a profound impact on China's AI commercialization process and also add excitement to the list of AI heroes "TOP30 Influential People of the Year in Artificial Intelligence in 2023". Among them, some are well-known in academia and have brought hard-core technical experience to impact China's AI business landscape; some are dominant in the business market and lead their teams to continuously deepen the foundation of competitiveness with precise insights.

As the leader of Yunzhisheng, Huang Wei graduated from the University of Science and Technology of China and is one of the earliest researchers in China engaged in research on artificial intelligence speech and semantic related technologies. He served as a senior researcher at Motorola China Research Center and as the dean of the Voice Branch of Shanda Innovation Institute. During this period, he led the team to participate in the speaker recognition evaluation of the National Institute of Standards and Technology for three consecutive years and achieved the first place in the world

In the boom of large models, Huang Wei led the team to start a new wave of technology with his keen strategic vision. In May this year, they officially released the Shanhai model, focusing on the two fields of smart IoT and smart medical care, and constantly exploring new paths in commercialization. Up to now, Yunzhisheng's large model of mountains and seas has been successfully used in scenarios such as smart medical care, smart government affairs, smart rail transit, and smart vehicles, and the scenario applications based on this large model are constantly being enriched and expanded, and its commercial value has also been Recognized by more people, it fully demonstrates Huang Wei’s excellent judgment, creativity and leadership

While Huang Wei and his team have been recognized for their achievements in the field of artificial intelligence, Yunzhisheng has been selected for the 2023 annual selection. This is not only recognition of them, but also expectations for their future development potential. In the future, Yunzhisheng will continue to promote the development of artificial intelligence technology and take root in the industry. Work with other peers to create a more exciting blueprint for commercialization of artificial intelligence in China

The above is the detailed content of Huang Wei and Yunzhisheng were successfully selected for the '2023 Artificial Intelligence Annual Selection' and won two honors. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

Repo: How To Revive Teammates
1 months ago By 尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Energy Crystals Explained and What They Do (Yellow Crystal)
2 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
Hello Kitty Island Adventure: How To Get Giant Seeds
1 months ago By 尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Bytedance Cutting launches SVIP super membership: 499 yuan for continuous annual subscription, providing a variety of AI functions Bytedance Cutting launches SVIP super membership: 499 yuan for continuous annual subscription, providing a variety of AI functions Jun 28, 2024 am 03:51 AM

This site reported on June 27 that Jianying is a video editing software developed by FaceMeng Technology, a subsidiary of ByteDance. It relies on the Douyin platform and basically produces short video content for users of the platform. It is compatible with iOS, Android, and Windows. , MacOS and other operating systems. Jianying officially announced the upgrade of its membership system and launched a new SVIP, which includes a variety of AI black technologies, such as intelligent translation, intelligent highlighting, intelligent packaging, digital human synthesis, etc. In terms of price, the monthly fee for clipping SVIP is 79 yuan, the annual fee is 599 yuan (note on this site: equivalent to 49.9 yuan per month), the continuous monthly subscription is 59 yuan per month, and the continuous annual subscription is 499 yuan per year (equivalent to 41.6 yuan per month) . In addition, the cut official also stated that in order to improve the user experience, those who have subscribed to the original VIP

Context-augmented AI coding assistant using Rag and Sem-Rag Context-augmented AI coding assistant using Rag and Sem-Rag Jun 10, 2024 am 11:08 AM

Improve developer productivity, efficiency, and accuracy by incorporating retrieval-enhanced generation and semantic memory into AI coding assistants. Translated from EnhancingAICodingAssistantswithContextUsingRAGandSEM-RAG, author JanakiramMSV. While basic AI programming assistants are naturally helpful, they often fail to provide the most relevant and correct code suggestions because they rely on a general understanding of the software language and the most common patterns of writing software. The code generated by these coding assistants is suitable for solving the problems they are responsible for solving, but often does not conform to the coding standards, conventions and styles of the individual teams. This often results in suggestions that need to be modified or refined in order for the code to be accepted into the application

Seven Cool GenAI & LLM Technical Interview Questions Seven Cool GenAI & LLM Technical Interview Questions Jun 07, 2024 am 10:06 AM

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

Can fine-tuning really allow LLM to learn new things: introducing new knowledge may make the model produce more hallucinations Can fine-tuning really allow LLM to learn new things: introducing new knowledge may make the model produce more hallucinations Jun 11, 2024 pm 03:57 PM

Large Language Models (LLMs) are trained on huge text databases, where they acquire large amounts of real-world knowledge. This knowledge is embedded into their parameters and can then be used when needed. The knowledge of these models is "reified" at the end of training. At the end of pre-training, the model actually stops learning. Align or fine-tune the model to learn how to leverage this knowledge and respond more naturally to user questions. But sometimes model knowledge is not enough, and although the model can access external content through RAG, it is considered beneficial to adapt the model to new domains through fine-tuning. This fine-tuning is performed using input from human annotators or other LLM creations, where the model encounters additional real-world knowledge and integrates it

To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework Jul 25, 2024 am 06:42 AM

Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A

SOTA performance, Xiamen multi-modal protein-ligand affinity prediction AI method, combines molecular surface information for the first time SOTA performance, Xiamen multi-modal protein-ligand affinity prediction AI method, combines molecular surface information for the first time Jul 17, 2024 pm 06:37 PM

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

Five schools of machine learning you don't know about Five schools of machine learning you don't know about Jun 05, 2024 pm 08:51 PM

Machine learning is an important branch of artificial intelligence that gives computers the ability to learn from data and improve their capabilities without being explicitly programmed. Machine learning has a wide range of applications in various fields, from image recognition and natural language processing to recommendation systems and fraud detection, and it is changing the way we live. There are many different methods and theories in the field of machine learning, among which the five most influential methods are called the "Five Schools of Machine Learning". The five major schools are the symbolic school, the connectionist school, the evolutionary school, the Bayesian school and the analogy school. 1. Symbolism, also known as symbolism, emphasizes the use of symbols for logical reasoning and expression of knowledge. This school of thought believes that learning is a process of reverse deduction, through existing

Laying out markets such as AI, GlobalFoundries acquires Tagore Technology's gallium nitride technology and related teams Laying out markets such as AI, GlobalFoundries acquires Tagore Technology's gallium nitride technology and related teams Jul 15, 2024 pm 12:21 PM

According to news from this website on July 5, GlobalFoundries issued a press release on July 1 this year, announcing the acquisition of Tagore Technology’s power gallium nitride (GaN) technology and intellectual property portfolio, hoping to expand its market share in automobiles and the Internet of Things. and artificial intelligence data center application areas to explore higher efficiency and better performance. As technologies such as generative AI continue to develop in the digital world, gallium nitride (GaN) has become a key solution for sustainable and efficient power management, especially in data centers. This website quoted the official announcement that during this acquisition, Tagore Technology’s engineering team will join GLOBALFOUNDRIES to further develop gallium nitride technology. G

See all articles