Editorial Office Compiled from AIGC Summit
量子位 | 公众号 QbitAI
In the era of AIGC, how should an algorithm company make a profit?
This may be the most direct question that every "player" should think about when the current wave of large models is pushed to the stage of application is king.
In response to this problem, Xu Yuanchun, COO of Xiaoice Company, combined his own digital human and large model technology at the China AIGC Industry Summit, and brought the latest thinking summarized by Xiaoice Company in practice.
In order to fully reflect Xu Yuanchun's thinking, on the basis of not changing the original meaning, Qubit has edited and sorted out the content of the speech, hoping to bring you more inspiration.
The China AIGC Industry Summit is an industry summit hosted by qubits, with 20 industry representatives attending the meeting. Nearly 1,000 offline attendees and 3 million online live viewers participated in the conference, which received extensive attention and reports from mainstream media.
Talking points
- AIGC technology has allowed ordinary people to start making money
- The real challenge for AIGC is how to put it to practical use
- AIGC has made almost every hardware with a screen an interactive carrier
- The digital workforce is connected to the brains of the enterprise
The following is the full text of Xu Yuanchun's speech:
AIGC technology has allowed ordinary people to start making money
In recent years, we have often asked, as an algorithm company, if you are doing AIGC or large models or digital humans, many people will ask you what is the use of making this thing.
The latest question is, what are the business scenarios, what are the business closed loops, and where is the growth space for business in the future?
In fact, when asking this question, our first reaction is: how to make money as an algorithm company?
In the past two years, I have reflected that this question may be a bit problematic, how to make money as an algorithm company and how to make money as an AIGC industry company, this is the last question to be answered. The first question to be answered is, how do you make money with this thing?
We're going to share a few examples with you today.
First of all, a small aesthetic studio from Yunnan "Banaman Image Aesthetics", which is a small business operator focusing on aesthetics. The reason why her business is considered small is that as of now, she has only 8,667 followers on social platforms.
She's not the kind of internet celebrity whose followers soar to millions overnight, but an obscure industry micro-practitioner.
We told her story to show how she created a digital clone of herself using our digital avatar and large-scale SaaS platform to publish video content about women's grooming, styling and makeup tips. In this way, she produces a lot of video content.
After 40 days of using our platform, the data shows that her average video views have reached 2 million. What's more, her offline store attracts an average of 6 to 8 potential customers per day.
Maybe in previous years, people would have scoffed at the statistic of 6 to 8 new customers per day, and would have liked to hear 60 to 80 customers per day. But for a merchant who has actually experienced the market, these 6 to 8 customers a day are enough to make their business thrive and grow healthily.
The reason why she's able to do this is worth digging into because at a time when people are talking about how to use big models to write all kinds of copy and create all kinds of content, her case shows a real business success story: her business has grown significantly with our platform.
In the communication with her, her enthusiasm and yearning for using our platform and AIGC technology are overflowing. This is in stark contrast to concerns a few years ago about the threat that AI could pose, potentially displacing human jobs.
With the deepening of industrial applications, especially in all corners of society, we find that the actual participants in the market have a very practical and simple view of AI: can this technology help me do things that I couldn't do before, and can it make my business better?
For them, the turnaround of their business is not just about increasing the number of customers, but also about really improving the quality of their business and ensuring that they can continue to survive in a complex economic environment.
Therefore, this case not only gave great confidence to many people, including her, but also proved to us that AIGC technology - a cross-era AI technology and large model that actually gives ordinary people, even small entrepreneurs, the ability and opportunity to compete with larger enterprises.
The real challenge for AIGC is how to put it to practical use
Let's look at another example.
The reason why we know this customer is because we have a partner who has been active in Yunnan for a long time, which is a small and medium-sized enterprise. After starting to use our technology platform, the company gradually transformed its business.
Originally known as Kunming Xianbang, they provide software development, technology enablement, and back-end support services. However, after realizing that AIGC technology and big models can help grow their business like the previously mentioned customers, they made a major transformational decision.
Instead, they are using large models and AIGC technology to empower small and medium-sized enterprises (SMEs) and help them grow. The previous case was one of their achievements.
So far, since July last year, they have provided AIGC empowerment services to about 300 small and medium-sized enterprises in Yunnan, and have received good feedback from the market.
From consumers to small and medium-sized enterprises to medium-sized service providers, they have achieved a benign business closed loop, covering data flow, technology flow, and business flow. Here's an introductory video they made.
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Through this sharing, I would like to express how this partner has transformed his company into AI, from the company owner to the person in charge of sales management, and even every salesperson.
Before watching their video, I barely realized it was done through a digital persona.
I want to say more than just how advanced the technology is or how much change it will bring in the future, it goes without saying. The real challenge is how to put these technologies into practice and may not be what those of us who specialize in algorithms and product development do best.
In fact, the real value is realized by the partners of the companies and ecosystems that are closely connected to the market, providing services, and are able to find better use cases and methods.
An interesting phenomenon is that these digital sales receive many comments after interacting with people on the web, and we can even see the analytics data in the background. This suggests that people may have been less resistant to interacting with AI in the past.
When people communicate with digital salespeople and inquire and interact with each other on the premise of knowing that they are digital, this in itself is an enlightening phenomenon, indicating that people's understanding and acceptance of AI applications is deepening and broadening.
Almost every piece of hardware with a screen has become an interactive carrier
Let's move on to another case.
Following on from the aforementioned small practitioner and her partners, let's now turn to a leading company in the industry – Seemantech. It is a listed giant based in Shenzhen and one of the leading hardware manufacturing companies in China.
They manufacture or contract commercial displays and hardware products that you can see almost anywhere. From another point of view, what we call digital people today, not long ago, everyone usually accessed them through a single carrier called mobile phones, whether it was a short video platform or other media.
We have worked closely with Seematel to diversify our offerings. We have leveraged digital human and large-scale model technology to deeply integrate with Seemantech in terms of motherboards, cameras, microphone arrays, and device management platforms.
This allows their hardware products to be "out-of-the-box", while the large models in the background can be dynamically updated in real time.
In other words, the digital human or large model products you buy today no longer need to be taken home for cumbersome installation and setup, you only need to buy a device to take home and use it directly, which greatly facilitates the entire application chain and use path.
The range of hardware products they are currently involved in has exceeded my expectations, as they produce a wide range of hardware products, including shelf strip screens and transparent advertising machines.
Today, with the continuous expansion of large models and digital human application scenarios, almost every hardware device with a screen can become a new interactive carrier. I even believe that in the near future, the screen in front of me to remind me of the time will also take on a whole new form, telling me that time is running out.
The digital workforce is connected to the brains of the enterprise
Next, let's explore some of the deeper applications that may not be common in the world.
Now we are deeply embedding large models and digital applications into enterprise workflow and task systems. I really appreciate the concept of "native workflow" that Mr. Wu mentioned earlier, which sounds both professional and in-depth.
When we talk about workflow, we mean how the core business of an enterprise operates. Today, we have integrated digital human and big model technologies into the internal enterprise of enterprises, such as RPA systems. Through these systems, digital employees can be called on directly.
Such digital employees are not only able to achieve highly realistic interactions, but more importantly, they are connected to the data brain of the enterprise, that is, a brain that integrates the closed loop of enterprise knowledge and data, and is constantly upgraded.
This intelligent system, which combines large models and enterprise knowledge industry data, can make the entire business process smoother and communicate with customers and consumers more conveniently.
Nowadays, in the financial industry, many customers have begun to use the hybrid solution of digital human + large model recommended by us in the process of account opening and follow-up consultation, and even when they have some simple interactions.
We have also observed that large enterprises that are industry leaders are often the first to adopt technology, and they are always at the forefront.
The reason for mentioning them at the end of today's presentation is to give you a glimpse into how smaller, more real-world market players are adopting the technology, because these cases are more indicative of the fact that the use cases of the technology are becoming more and more widespread and deeper.
There are several dimensions of the entire business closed loop that are worth paying attention to:
- The first is cloud + end, that is, the closed loop of the combination of software and hardware products we have witnessed;
- The second is interaction + content, a closed loop in form.
The most important thing is our deep understanding that the business scene has changed from the perspective of traditional algorithm companies to real business individuals, no matter how big or small, they are using this technology to gain more competitiveness and business improvement.
That's the most important part of the cycle, because it's only when their business improves, becomes more competitive, and adds value that they'll be willing to buy and use your technology, closing the loop for the longer term. This is the most central power source in the closed loop.
Therefore, we believe that the real digital human model or the commercial closed loop of AI technology is actually the closed loop of the value chain. This requires you to identify the key points at the core of each value chain and activate the most important drivers at those points to achieve a true closed loop.
That's all for today's sharing, thank you!
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