The year 2023 is hailed as the "first year of large models," and the subsequent year 2024 is the golden opportunity for the application of "AIGC" technology.
The concept of AIGC is broad, among which Generative AI technology is particularly noteworthy. It addresses problems that traditional AI finds difficult to tackle through innovative algorithms, achieving a qualitative leap, especially in digital content innovation.
How Does the "AIGC + Scenario" Model Help in Processing Enterprise Data?
The advancement of technology and the expansion of application scenarios have made AIGC technology increasingly prevalent in enterprises, particularly demonstrating significant potential in enhancing work efficiency. By leveraging AIGC technology and AI large models, enterprises continuously refine their AI knowledge bases, enabling self-perpetuating cycles of knowledge circulation and updating.
AI Large Models + Knowledge Base = ？
Building an Enterprise Knowledge Base
As AI large models, such as GPT-3.5, GPT-4-Turbo, Claude-3-Sonnet, ERNIE Bot, and Doubao, continue to mature, they are emerging as invaluable assistants in constructing enterprise knowledge bases. Zero-code platforms designed for building AI knowledge bases, exemplified by the rise of HelpLook, not only support these AI large models but also streamline the process, making it simple and fast to establish a robust AI knowledge base. Additionally, equipped with AI search technology, these platforms function like intelligent navigators, precisely capturing user needs and providing efficient, accurate knowledge retrieval and recommendation services.
Evaluation of Domestic and International AI Large Models in 2024
Recently, the release of the "Chinese Large Model Benchmark Evaluation Report for the First Half of 2024" has showcased the latest advancements in AI large models, both domestically and internationally.
According to the "Chinese Large Model Benchmark Evaluation Report for the First Half of 2024," GPT-4o from OpenAI continues to maintain its leading position, but domestic large models such as Ali's Qwen2-72B and SenseChat5.0 from SenseTime have closely followed suit, narrowing the gap to within 5%. Models like Doubao, Kimi, Tongyi Qianwen, and Wenxin Yiyan also rank prominently with scores around 70 points in the SuperCLUE general capability evaluation.
In the SuperCLUE General Capability Evaluation, open-source models like Qwen2-72B performed exceptionally well, rivaling top closed-source models. Yi-1.5-34B, launched by Zero-One Infinity, also demonstrated remarkable strength in the open-source realm, closely trailing some top closed-source models with a score exceeding 60 points.
So What are Some Common AI Large Models Used to Build AI Knowledge Bases?
Popular Domestic AI Large Models:
1. Ernie Bot
Baidu's Wenxin Yiyan (ERNIE Bot) is a knowledge-enhanced large language model that possesses five core capabilities: literary creation, business copywriting, mathematical and logical reasoning, Chinese understanding, and multimodal generation.
Key Features: It focuses on Chinese language understanding and generation, offering multimodal content generation including images, speech, and videos. It leverages Baidu's robust search and data processing capabilities, as well as a vast amount of annotated Chinese data for optimization.
2. Doubao
Doubao from ByteDance is a large-scale multimodal language model family.
Key Features: It supports high levels of customization and personalization, catering to various industry needs, showcasing the technological vitality and innovation capabilities of the ByteDance ecosystem.
3. Kimi
Kimi, developed by Moon's Dark Side Technology Co., Ltd., is an AI large model renowned for its ultra-long text processing capabilities.
Key Features: It supports lossless input of up to 2 million Chinese characters, boasts powerful memory functions and contextual understanding, offers user-friendly operations, supports uploading of multiple file formats, and is suitable for processing large-scale text data.
4. Tongyi Qianwen
Alibaba's Tongyi Qianwen is a feature-rich natural language processing model.
Key Features: It possesses strong semantic understanding capabilities, accurately captures user intent, and is widely applied across various internal Alibaba applications such as DingTalk and Tmall Genie.
5. Xunfei Spark
iFLYTEK's Xunfei Spark is a natural language processing model specializing in speech recognition and speech synthesis.
Key Features: It excels in speech recognition and speech synthesis, providing precise text-to-speech conversion services.
6. Zhipu Qingyan
Zhipu Qingyan, launched by Zhipu AI, is a large model offering comprehensive natural language processing services.
Key Features: It excels at handling large-scale text data, quickly and accurately completing NLP tasks such as text classification, sentiment analysis, and named entity recognition.
7. Hunyuan
Tencent's Hunyuan Model is a self-developed, high-performance, low-energy-consumption large model.
Key Features: It supports 8k-text input length and incorporates reasoning and summarization capabilities. Technological upgrades and innovations provide robust support for Tencent Cloud in the AI cloud service market.
Foreign Popular AI Large Models
1.ChatGpt
ChatGPT from OpenAI is a chatbot program based on the GPT model. Currently, the series encompasses multiple versions such as GPT-3.0, GPT-4, and GPT-4-Turbo.
Key features: ChatGPT is renowned for its exceptional ability in dialogue generation and question answering, enabling it to engage in fluid and intelligent conversational interactions with users. It stands out as a leader in the field of large AI models.
2. PaLM2
Google's PaLM 2 is a new generation language model.
Key features: It boasts improved multilingual and reasoning capabilities, enhanced computational efficiency, and applicability across a wide range of scenarios.
At the turning point of widespread AI adoption by enterprises, there has been a sharp increase in organizations' willingness to embrace AI and their budgets allocated for it. This not only indicates that AI technology will be applied more broadly and deeply globally but also positively impacts the development of enterprises themselves and the continuous advancement of AI technology.
The Importance of Security and Privacy
However, when AI large models process vast amounts of personal data, privacy and security remain paramount concerns. Consequently, adopting machine learning methods centered on privacy protection and secure data analysis techniques is of utmost importance. HelpLook, for instance, strictly adheres to the ISO/IEC 27001 information security standard and provides TLS-standard security and encryption for data in transit.
The rapid development of AI technology presents new opportunities for enterprises to build knowledge bases. SaaS tools like HelpLook simplify this process by eliminating the need for enterprises to select AI large models, enabling them to apply all popular AI large models in a one-stop manner. Click here to explore the HelpLook AI knowledge base for free now.
