The seeds sown by AIGC have blossomed into flowers with different aromas

The development of AI technology has ushered in a new wave. Now, AIGC is also widely used. So, specifically, what are the directions of AIGC application? In this article, the author disassembles and analyzes the landing direction of AIGC. Let's take a look.

"I don't know if Miaoya even understands the recent circle of friends."

Recently, an AI camera app called "Miaoya Camera" has become popular in WeChat Moments, triggering a wave of sharing "personal photos" in WeChat Moments. This is an AIGC application based on AI face recognition. Users can get an exclusive digital avatar by uploading multiple personal photos for 9.9 yuan, generating a "personal photo" under a set of system templates.

However, facing the operation of uploading 21 clear frontal photos, many users also expressed concerns. Controversies have arisen one after another, such as whether it is possible to upload photos of others and whether the photos will have other uses.

Over the past year, we have witnessed the "explosive" growth of AI in the fields of art, management tools, literary creation, and even medicine. Under this wave, major companies have increased their investment in AI research and development, setting off a new round of "AI revolution". Some AI technologies have gradually been implemented on the C-end. The application of AI in writing, painting, games, programming, audio and video editing, etc. has brought AI technology closer to users.

Today, AIGC is being used more and more widely. In addition to content generation, its application in work efficiency improvement and brand marketing is becoming more mature. Driven by technology, AIGC has gradually found its way out of the fork in the road, and the controversial points are becoming more dispersed.

1. AIGC and content generation

MiaoYa Camera is a universal application of AIGC in content creation. The original intention of AIGC was to assist in content creation, which is also the most mainstream application direction at present.

Content creation has always been a "patent" of humans, from rock wall paintings in ancient times to poetry and songs, and now to videos, music, and pictures. The ability to create content is an important mark that distinguishes humans from other animals. The development of AIGC technology seems to have begun to give AI this human characteristic.

Before 2021, AIGC mainly generated text, but now the new generation of models can process content in formats including text, voice, code, images, videos, robot movements, etc. AIGC is considered to be a new content creation method after professionally produced content (PGC) and user-generated content (UGC), which can give full play to its technical advantages in terms of creativity, expression, iteration, dissemination, personalization, etc.

In 2021, the OpenAI team brought the cross-modal deep learning model CLIP to people's attention. According to public data, the CLIP model has collected more than 4 billion "text image" training data on the Internet, which laid the foundation for the subsequent AIGC, especially the input text to generate images and video applications. Since 2022, the iteration speed of AIGC has accelerated. The continuous improvement of deep learning models, the promotion of open source models, and the possibility of exploring commercialization of large models have jointly promoted the accelerated development of AIGC.

The picture comes from [New Economic Guide]

From the perspective of deep content generation, AIGC can help creators capture inspiration and innovate interactive forms. For example, in the animation industry, producers and art staff often have misunderstandings due to communication. Through AIGC, a large number of sketches can be generated in the early stages of design, on which basis producers and art staff can better understand and confirm each other's needs.

At the same time, AIGC can directly generate storyboards based on the script or story outline, which will then be screened, processed, and integrated by professional staff, and the entire story and pictures will be further improved, which comprehensively improves the efficiency of professional content generation and creates an incremental space for large-scale content production.

For ordinary C-end creators, AIGC makes content creation simple and convenient, lowering the threshold for creation. Clour interviewed many creators who applied AIGC to their daily creations. They said that AI-generated content can fundamentally solve the creators' difficulties in accumulating materials. This is especially true for knowledge-based content, which requires professional knowledge reserves and clear logical thinking, and has relatively weak entertainment and personal emotional attributes. It can give full play to the advantages of AIGC and play to its strengths while avoiding its weaknesses.

Some content creators also expressed their concerns to Clour. Human creation is based on the creator's sensibility and imagination, while AI creation is based on the training and data it receives. Human taste, creative intent, and long-formed content style cannot be imitated. Over-reliance on AIGC technology will cause creators to fall into a certain inertia, and in the long run, content creation will lose subjective thinking and original value.

Regarding this point, Clough believes that AIGC at the current stage plays an assistant role, which is limited to being an efficiency tool based on understanding the needs of creators. The final content decision and responsibility still have to be borne by people. Even if the boundary between AI-synthesized works and personal original works is becoming increasingly blurred, the more so, the independent thinking and original value of the creators will become more prominent.

2. AIGC and Enterprise Efficiency Improvement

In addition to content production, cloud strategy, artificial intelligence, and edge computing are driving changes in enterprise management business, helping enterprises to control business models, improve management efficiency, and ensure business security. All walks of life have begun to embrace AIGC, and service providers have also launched exclusive industry models.

For example, in June this year, H3C Group released the private domain big model "Baiye Lingxi", which aims to provide secure, customized, exclusive and growing intelligent cloud services for customers in vertical industries and exclusive regions; last month, China UnionPay Business released a mapping product based on generative AI technology - "Yin Shang Tiantu", and announced the development of a big language model application product called "Tianyan" and a code generation-specific big language model product called "Tianma"...

In addition, AIGC has also been put into practical application for front-line task scenarios. For example, in scenarios where there is a strong demand for lead acquisition but insufficient online customer service capabilities, Baidu Business has developed its own lead robot, which uses a large model generated by tens of billions of conversations to replace the manually configured conversation template system, thereby providing merchants with consulting and reception services that automatically switch between multiple scenarios.

For the internal management of enterprises, AIGC's core advantage lies in improving the efficiency of office and management.

AIGC technology can enable the company's automated process management, help enterprises improve process design efficiency, and optimize office collaboration processes. This allows companies to focus more on core business and reduce human resources investment in tedious work. In addition, automated process management also helps reduce human errors and reduce risks.

For example, in information management, AIGC technology can automatically generate information classification schemes, improve information management efficiency, and facilitate subsequent retrieval. This helps to better utilize internal resources, optimize business processes, improve overall office collaboration efficiency, and promote communication and collaboration between different departments within the enterprise.

However, in the B-side application scenario, AIGC is still at the stage of handling basic work and still has certain shortcomings when facing complex problems. For example, for problems involving multiple departments, cross-domain knowledge or complex business logic, AIGC may find it difficult to provide solutions that meet actual needs. In this case, enterprises still need to rely on manual decision-making and processing.

3. AIGC and Brand Marketing

When AIGC was just beginning to be applied, among the many discussions about AIGC, one hot topic was "whether AIGC will replace search engines." From a marketing perspective, search connects platforms, advertisers, and users. If search changes, marketing also needs to be adjusted in a timely manner.

From the perspective of advertising production, AIGC can, in an ideal state, refine the algorithmic logic of advertising content creation through key technologies such as target semantic extraction and association analysis, content-based cross-media analysis and retrieval, and opinion and sentiment mining, and then produce large-scale advertising content for classification. Different advertising content can be produced according to the user's age, gender, region, education level, personality, and hobbies, thereby achieving personalized advertising delivery for thousands of people or even one person.

At the same time, AIGC's ability to generate visual content such as pictures and videos provides some categories with an entry point for leveraging marketing.

Taking beauty products as an example, AIGC can play the role of a makeup artist to a certain extent. In the past, each terminal store had to invest a lot of money in professional knowledge training for makeup artists and shopping guides, but AIGC can truly present standardized makeup effects, reduce consumers' dependence on professional makeup artists, and achieve zero loss of makeup samples, helping stores reduce daily operating costs.

ModiFace has also developed an app called FaceLift that allows consumers to clearly see the effects of skin improvement. It can simulate more than 20 anti-aging effects and provide suggestions for improving skin conditions. L'Oréal launched the first dynamic virtual makeup trial application on WeChat mini-programs... When interactive experience scenes spread from offline to online, in addition to building scenes and improving the experience, brands provide consumers with virtual makeup trial scenes that can form a marketing closed loop on e-commerce platforms and product apps.

In addition, the creativity of the virtual world brought by AI has created a "cyberpunk" concept for consumers, which is very attractive to young consumers. For example, AI-generated virtual human images have been widely used in brand image building and endorsement fields.

For example, SuperX once released five specially packaged products, four of which were created by AI designers. After the products were released, the brand invited users to guess whether the four new products were designed by human designers or AI designers, adding a sense of futurism and suspense to the products in an interactive way similar to the Turing test. The setting of AI and humans jointly designing the bottle not only makes the product more attractive, but also triggers the thinking of the coexistence of AI and humans, attracting the attention of young consumers.

However, there are also some controversies in the application of AI in brand marketing. The first is the privacy issue. AI needs to collect a large amount of user data to learn and make decisions, which may involve the risk of personal privacy leakage in the process. The second is the uncertainty of artificial intelligence technology. The decision-making process of AI systems is often a "black box" and its decision-making basis cannot be fully explained, which may cause users to distrust the brand.

In the future, the development direction of AI in brand marketing will focus more on personalization and emotionalization. AI can provide services and promotion methods that are more in line with user psychology by gaining a deeper understanding of consumer needs and emotional states.

4. Final Thoughts

Chen Xiyan, CTO of Yilan Technology, once said in an interview with the media: "At present, the capabilities of AI are increasingly recognized by the industry. What it does is by no means some trivial work, but some exquisite and creative things. However, the premise for making AI more powerful is that the operators behind it must be more imaginative and creative."

AIGC has brought unlimited "imagination" to all walks of life, and reasonable application can improve creative efficiency. But the more this is the case, the more important people's subjective ideas are in content creation. We look forward to the continued advancement of AIGC technology and the promotion of content production in a more creative and imaginative direction. We also look forward to the emergence of AI application scenarios in all walks of life and the discovery of new commercial space.

References:

[Is AIGC a tool or an innovative disruptor? ]/New Economy Guide

[AIGC under the new breakthrough of AI capabilities: a new paradigm of content production] / Young reporter

[Providing better cloud services in the AIGC era]/Live Report

Author: Dake

Source: TopKlout (ID: TopKlout), a self-media ecological observation account that combines good-looking and informative content