


Leading the smart era: iFlytek Spark V2.0 deepens the application of artificial intelligence large models and achieves full implementation
In the era of digital economy, data is the key to productivity. Whether an enterprise can create greater value depends on how to use data more securely and efficiently. On August 15, iFlytek, the national artificial intelligence team, released version 2.0 of the Spark Cognitive Large Model, which not only provides intelligent support for all walks of life, but also accelerates the standardization of the general large model industry. At the same time, the "Interim Measures for the Management of Generative Artificial Intelligence Services" also came into effect on the same day. iFlytek Chairman Liu Qingfeng emphasized that the era of deep empowerment of cognitive large models has arrived. We must not only focus on what technology can do, but also establish a healthy and safe industrial promotion environment and capability guarantee
Generative artificial intelligence, or AIGC, is a technology that generates text, pictures, sounds, videos, codes and other content through algorithms, models and rules. Due to the characteristics of content generated by AIGC, security and controllability become very important. iFlytek Spark adopts a general large model industry-empowered business model, which is the "1 N" symbiotic architecture. This business model cannot be separated from the support of advanced production materials such as data, computing power and algorithms. However, we need to assess and review the security of the data
Based on the National Engineering Technology Center for Speech and Language built by iFlytek, the Spark Cognitive Model can collect scientific knowledge, popular science knowledge and industry content suitable for machine learning on a global scale. Screening and filtering are performed through the language discriminator, quality discriminator, privacy discriminator and security discriminator to clean the data and finally obtain high-quality text data
At the Spark V2.0 press conference, there were slogans surrounding it: "Liberate productivity, unleash imagination." However, how to avoid unfounded rhetoric while keeping large models freeing the imagination?
When it comes to serious content such as financial customer service answering user questions, the intelligent performance of general artificial intelligence may be problematic, although it can easily write advertising copy and write stories through large models
By building an industry knowledge base and using class search capabilities, iFlytek Spark V2.0 provides a better security solution, which can accurately extract the content in the security knowledge base and use large models to understand and summarize
The release of the "Spark All-in-One" attracted the attention of the industry at the press conference. This product integrates the intelligent capabilities of the iFlytek Spark model and the base technology of Huawei AI Ascend, and is fully guaranteed from content to computing power. It enables enterprise users to quickly deploy secure and controllable exclusive large models according to their own needs, thereby improving enterprise operating efficiency and creating business value-added
iFlytek Spark V2.0 takes "imagination" as the driving force and accelerates the standardization of the general large model industry from an industrial macro perspective. With the support of iFlytek Spark, all walks of life will fully embrace artificial intelligence and the digital economy, and jointly welcome a new era of "wisdom emerging"
The above is the detailed content of Leading the smart era: iFlytek Spark V2.0 deepens the application of artificial intelligence large models and achieves full implementation. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



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

On May 30, Tencent announced a comprehensive upgrade of its Hunyuan model. The App "Tencent Yuanbao" based on the Hunyuan model was officially launched and can be downloaded from Apple and Android app stores. Compared with the Hunyuan applet version in the previous testing stage, Tencent Yuanbao provides core capabilities such as AI search, AI summary, and AI writing for work efficiency scenarios; for daily life scenarios, Yuanbao's gameplay is also richer and provides multiple features. AI application, and new gameplay methods such as creating personal agents are added. "Tencent does not strive to be the first to make large models." Liu Yuhong, vice president of Tencent Cloud and head of Tencent Hunyuan large model, said: "In the past year, we continued to promote the capabilities of Tencent Hunyuan large model. In the rich and massive Polish technology in business scenarios while gaining insights into users’ real needs

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

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 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

1. Background Introduction First, let’s introduce the development history of Yunwen Technology. Yunwen Technology Company...2023 is the period when large models are prevalent. Many companies believe that the importance of graphs has been greatly reduced after large models, and the preset information systems studied previously are no longer important. However, with the promotion of RAG and the prevalence of data governance, we have found that more efficient data governance and high-quality data are important prerequisites for improving the effectiveness of privatized large models. Therefore, more and more companies are beginning to pay attention to knowledge construction related content. This also promotes the construction and processing of knowledge to a higher level, where there are many techniques and methods that can be explored. It can be seen that the emergence of a new technology does not necessarily defeat all old technologies. It is also possible that the new technology and the old technology will be integrated with each other.

According to news on June 13, according to Byte's "Volcano Engine" public account, Xiaomi's artificial intelligence assistant "Xiao Ai" has reached a cooperation with Volcano Engine. The two parties will achieve a more intelligent AI interactive experience based on the beanbao large model. It is reported that the large-scale beanbao model created by ByteDance can efficiently process up to 120 billion text tokens and generate 30 million pieces of content every day. Xiaomi used the beanbao large model to improve the learning and reasoning capabilities of its own model and create a new "Xiao Ai Classmate", which not only more accurately grasps user needs, but also provides faster response speed and more comprehensive content services. For example, when a user asks about a complex scientific concept, &ldq

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
