Innovations in AI Applications: From Twitter Data Analysis to Real Performance Assessment of Large Models

13 January 2025

As AI technology advances rapidly, various industries are continuously innovating new application scenarios. This article uses Twitter data analysis as a starting point and combines the outstanding performance of Zhi Pu GLM-4-9B in evaluations to explore AI's wide-ranging applications in practical scenarios and its significant value. It also delves into current challenges faced by AI technology and potential future directions.

A team of data analysts using the Zhipu GLM-4-9B model to analyze Twitter data, showcasing the practical application of AI technology in real-world scenarios.

Targeted Lead Generation and Smart Marketing: AI Tools Drive Breakthroughs in International Trade

AI applications are transforming traditional methods of acquiring customers in international trade. With AI tools, businesses can attract potential customers more precisely through accurate target identification and personalized communication. Integrating data from diverse sources—LinkedIn client profiles, Google Maps search results, and Twitter interaction data—gives a comprehensive picture of target clients, enabling highly targeted marketing campaigns. Recent actions by Microsoft against hackers bypassing Azure’s OpenAI security highlight the importance of cybersecurity in maintaining AI's benefits. Successful international trade AI software emphasizes encryption and access control to protect user data. Advanced models like Zhi Pu GLM-4-9B, which boast extremely low error rates, ensure secure and reliable data transmission.

Additionally, AI enhances customer relationship management. Smart chatbots can automatically respond to user inquiries, while intelligent recommendation systems provide tailored product suggestions based on purchase history. By 2025, nearly 40% of retailers globally plan to invest in automated services. Thus, AI is revolutionizing the marketing industry, ushering in a new era of innovation.

Developing High-Performance AI Models: Insights from Zhi Pu GLM-4-9B

The evolution of AI applications places great importance on the development of high-performance AI models. One prominent example is Zhi Pu Technology’s GLM-4-9B, a standout achievement among China’s top AI laboratories. GLM-4-9B excelled in international benchmarks, demonstrating exceptional text comprehension and scoring high in niche problem-solving. It has set new standards in the industry, especially in solving long-tail issues.

GLM-4-9B’s success underscores collective efforts across the entire AI ecosystem. Collaborative efforts like SenseTime’s "Daily New Fusion" models contribute to overall advancements. As computing power becomes more accessible and costs drop, more research entities engage in training, fostering knowledge sharing and iterative improvements.

Notably, although several influential large language models exist worldwide, we remain in an exploratory phase, uncovering many unknown areas. Therefore, researchers must maintain an innovative spirit, break traditional mindsets, experiment with new techniques, and strive for breakthroughs.

Risk Prevention: Building a Safe and Reliable AI Ecosystem

Sustained growth in international trade AI software hinges on a robust risk management system. Given prevalent issues such as data breaches and copyright disputes, crafting a secure AI environment is imperative.

Microsoft's legal action against hackers highlights fundamental governance rules. Authorities should strengthen regulatory frameworks, supporting law-abiding enterprises, while firms need to fortify internal controls and train employees regularly to bolster cybersecurity awareness.

International cooperation is crucial to combat transnational cybercrime. Governments and civil organizations should form closer partnerships and consider uniform certification standards or resource-sharing platforms.

Developers must adhere to ethical guidelines and avoid misuse of AI tools. Upholding values wins societal recognition.

Looking Forward: Preparing for the Next Decade of AI Revolution

Looking ahead ten years, AI applications will witness unprecedented opportunities. According to IDC, by 2025, global enterprise spending on AI hardware will reach tens of billions, with a notable share attributed to the Asia-Pacific region. Policy support and talent pools will foster AI development in China.

Amidst this transformation, cross-industry collaborations will thrive. AI with IoT and edge computing could revolutionize smart home systems. In healthcare, predictive models for disease trends and proactive measures become feasible, hinting at endless possibilities.

Recent TSMC financials showing a 40% sales hike signify robust momentum driven by next-generation IT innovations. Mastering frontier technologies aligns businesses with future success.