ChatGPT is successful because American AI is not bad for money?

Text: Brain Polar Body Source: Titanium Media

Image source: Generated by Unbounded Layout AI

Recently, there is a saying: the reason why such a successful AI application as ChatGPT was born in the United States, not in China, is because Chinese companies in the AI ​​field are eager for quick success and quick profits, and investors are exhausted.

There are many arguments for similar conclusions. For example, when looking at AI projects in China, the investment circle must look at the scenarios and commercial potential, and do not look at basic model projects that do not see returns in the short term. Chinese AI companies, even big ones, attach great importance to commercialization, and immediately demanded to point to the industry and point to revenue as soon as they started a project. On the contrary, ChatGPT integrates OpenAI’s long-term research and development ideas without consideration of returns, and finally completed the accumulation of accumulation.

It can be deduced that after several years of development in China’s AI, there is still no star technology, and it seems that most of the investors and companies are too short-sighted. In other words, when our companies and capital are not short of money like the American AI circle, and do not love money, our AI basic research and core technology will have a bright future.

At first glance, this statement sounds reasonable and has sufficient evidence, and it is also very consistent with the discourse habit of “capital does not determine internal affairs” in today’s public opinion field.

But does this really stand up to scrutiny?

ChatGPT exploded, which is really enviable. I understand that everyone is in a hurry, so let’s take it easy. If under this kind of crude “reflection”, the final conclusion is that it does not consider commercial returns and does not care about individual gains and losses, China’s AI will be better. That may be the real road to the opposite.

Because this logic of occupying the moral high ground is untenable from the starting point, and will obscure the brightest part of China’s AI development so far.

Is OpenAI, and even American AI, really so reckless?

Recently, we have been hearing such a narrative: ChatGPT was born because OpenAI, a company that dared to challenge great research, succeeded regardless of rewards.

But this narrative thread may be fundamentally problematic. In this story, OpenAI is a group of young people with dreams who gather together to change the world. There is a mistake of confusing cause and effect here. It is not that OpenAI chose greatness, but that when investors founded and launched OpenAI, a scientific research entity, they positioned themselves to only do research with great transformational significance.

When Musk and his friends launched OpenAI in 2015, the idea was to bring together the world’s top AI talents to develop the most cutting-edge AI technology on a non-profit basis. This model targets more semi-academic and semi-enterprise scientific research entities like Bell Labs that can generate huge social value. The direct competitor is DeepMind, which was just acquired by Google.

Therefore, it is not that OpenAI chose the underlying technology research, but that it was born for the underlying technology of AI. Another point to note is that a company like OpenAI is itself a star enterprise that was born under a special opportunity by integrating the world’s top rich people, top scholars, and massive public attention. Comparing the technological capabilities of such a company with a specific Chinese company or investment institution is itself suspected of exaggerating the responsibility of the latter.

Seeing this, some people may say. So OpenAI can be successful, isn’t it still not bad for money, and doesn’t consider commercial returns in exchange for it? This is also problematic. Because by 2019, OpenAI voluntarily gave up its non-profit attributes and turned to embrace commercialization.

At that time, with the withdrawal of a group of early investors such as Musk, and the expenditure on computing power, data, and talents became larger and larger. OpenAI began to realize more and more clearly that the non-profit model is unsustainable, so with Sam Altman as the CEO of OpenAI, the company transformed into a restricted profit-making entity (OpenAI LP), with restrictions on profit ceilings, revenue types, etc. way to explore a new balance between commercialization and non-profit organizations.

This model of “using business to support research” is basically successful so far. On the one hand, it promotes a large number of OpenAI’s technical achievements to the market in exchange for profits to fund follow-up research and form a positive R&D funding chain. In addition, it also opened the door for OpenAI to receive more funding. Therefore, in July 2019, OpenAI accepted a strategic investment of US$1 billion from Microsoft. One of the costs was that OpenAI became the exclusive technology supplier in Microsoft’s cloud computing field. This also created today, a few years later, when Microsoft used ChatGPT to push old rivals such as Google and META into a corner.

It is not difficult to see that OpenAI is not as “high-cold” as some media say, but its development track highlights a pragmatism of “moving the dead and moving the living, there are always more ways than difficulties”. Today, OpenAI can achieve more than $35 million in annual revenue, which is certainly not much for a commercial technology company. But for a semi-profit scientific research entity, it has solved a lot of development problems. From the perspective of revenue methods, OpenAI is not only deeply tied to Microsoft, but also continuously obtains investment from Microsoft to serve as its technology supplier. It can also realize many of its products through commercial subscriptions, API paid access and other modes, such as OpenAI’s Take Vincent’s large model DALL.E as the behind-the-scenes support of many AI drawing software.

Compared with OpenAI, its old rival DeepMind seems to be a little silent in this round of explosion of large language models. Of course, there are many reasons for this, such as the problem of technical route selection, but there is one problem that absolutely delays DeepMind’s development efficiency and technical layout capabilities, and that is commercialization.

In the past few years, it can be seen that DeepMind has been losing money year after year, which has led to news of Google’s dissatisfaction. Its co-founder has publicly stated that if it hadn’t been for Google’s acquisition that year, DeepMind should have gone bankrupt. However, these years have been turbulent, and the landlord’s family has little surplus food. Because DeepMind has always had a high degree of independence and is more inclined to an idealized and academic research atmosphere, it has been repeatedly criticized and suspected by Google. There were a lot of contradictions.

Of course, with the fire of OpenAI, Google seems to have found that it still has to rely on DeepMind, so the relationship tends to pick up recently. But in any case, the shortcomings of commercialization did not help DeepMind soar into the sky. Instead, it became a development obstacle that it was constantly criticized by its parent company, the research process slowed down, and even layoffs and bankruptcy crises occurred repeatedly.

It can be said that DeepMind is the image of a strange man who “does everything well and doesn’t take home any money”. But this image, at least for now, has not brought success, but has brought doubts about it from the outside world.

But I want to add that here is not the meaning of looking down on DeepMind. Its massive research in recent years is really breakthrough and imaginative. When it finds a suitable fast track for its own development, the next phenomenon comparable to AlphaGO and ChatGPT Advanced AI technology has to be done by it. I hope that we will reflect on it at that time, and don’t let the American AI ignore the rewards again…

In fact, there are a lot of money-losing projects in China’s AI field. For many industries + AI solutions, manufacturers make one and lose one. Numerous doctors have gone to factories and farmland, and the final settlement fee may not even be enough for the salaries of the doctors. This model is still advancing in an orderly manner in China, at least proving that China’s AI is by no means equal to quick success.

Conversely, American AI companies and investment institutions also love money, and society’s criteria for judging new technologies and technology companies is whether they are successful in commercialization. We have seen many Chinese AI start-up companies, even if revenue is difficult, they can survive through government support, joining the industrial ecology of large manufacturers, and integrating into vertical industries. On the contrary, a large number of American AI companies are crowded in a small track, and they lack support from the bottom line. The final outcome is short-lived.

From another perspective, it’s not that Chinese investors love money more, while American investors don’t love money. For example, a data report released by a university not long ago stated that from 2015 to 2021, investment from the United States accounted for 37% of the total financing of Chinese AI companies. If the data is correct, it is difficult for us to explain why American investors who “regardless of returns” have come to invest in Chinese companies that “lose money”?

Pursuing commercial returns is the nature and vocation of enterprises and commercial capital, and there is absolutely nothing wrong with it.

Many media and KOLs like to beautify a wonderful narrative of “using useless things for great use”. Because this kind of story has drama and contrast, it also has flow, and it can also cater to a certain psychological expectation of “China’s technology is not good enough”.

wake up. It’s not that OpenAI doesn’t plan to commercialize it, it just has a better plan.

Then why was ChatGPT not born in China?

Then someone asked again. Having said so much, isn’t a well-known application like ChatGPT made in the United States?

Behind this question, there is more anxiety in the context of the Sino-US game and the “technological bottleneck”. It is very understandable, but it should be viewed calmly.

Since the publication of the “New Generation Artificial Intelligence Development Plan” in 2017, China’s AI industry has entered a stage of rapid development, and the results obtained have been obvious. In the field of AI, China neither has the heavy historical burden of chip manufacturing, nor does it have a sense of illusion that cannot be seen or touched like the cutting-edge technologies such as brain-computer interface and quantum computing. The achievements and solidity of China’s AI development are visible to the naked eye. From macro indicators such as industrial scale, leading companies, and industrial ecological construction, to core technical infrastructure such as AI chips, AI development frameworks, and large models, it can be said that China’s AI has no obvious shortcomings.

The two companies OpenAI and DeepMind are themselves special companies that have gathered the world’s top talents, strength and capital under special circumstances. Their achievements and foresight are difficult to match in a short period of time among global AI companies, including all other American companies.

These two companies are like the last penalty kick in the World Cup final. Does that mean that French football is far behind Argentina? Probably not. Of course, if football can lose even Vietnam, then don’t come out to discuss it.

Using the particularity of these two companies to judge a large number of Chinese companies is an unfair comparison in itself, just as the United States is inferior to China in many key technologies of 5G. Does this prove that American communications as a whole are not good enough?

If you really want to discuss why ChatGPT did not appear in China, you must first face up to the complexity behind this issue.

For example, can OpenAI’s talent pool and source of talent be exchanged by Chinese AI companies and even the AI ​​industry regardless of returns, or even by spending money at will? For another example, the opportunities for the rise of OpenAI and DeepMind are very special, with the right time, place and people, and a positive snowball effect has been formed, which is difficult for Chinese companies to replicate.

In fact, OpenAI and DeepMind have gradually developed into forward-looking AI research institutions of Microsoft and Google. This model really needs to be compared. It is more like Huawei 2012 Lab, Alibaba Dharma Institute, and Baidu Research Institute. Of course, there are many inconsistencies. These Chinese enterprise research institutes also do a lot of forward-looking research regardless of returns, but they may not be as successful and well-known as ChatGPT, but at least it does not need to be said that Chinese enterprises only love money.

If AI technology is simply summed up as that it can be done well without bad money, it will often be counterproductive. Just like the AI ​​models made by Chinese universities and scientific research institutions in recent years have been spectacular, but a large number of projects have no follow-up after acceptance, papers, evaluations, and awards. Open source models are not used by anyone, lacking ecological vitality, and their input and output are disproportionate.

This kind of research relies on scientific research funding, and of course it can ignore commercial returns, but will it really improve China’s AI in a substantial way? Maybe also doubtful.

In fact, most technologies require multiple levels of R&D investment. Commercial R&D and forward-looking research need to go hand in hand, but the characteristics of AI technology make it easier for the results to be directly perceived by the outside world.

ChatGPT was not born in China, just like why China can’t make 7nm chips, it is a complex and widely related issue.

He is strong and he is strong, the breeze blows the hills

Fortunately, ChatGPT was not born in China, so it doesn’t really matter. In today’s China, the AI ​​model is only a question of “sooner or later”, and it is by no means a contradiction of “yes and no” like chip manufacturing.

In a sense, we don’t need to worry about who made this breakthrough first. It is good to be the first to break through, but it doesn’t mean too much. The IP network was born in the Atom energy center in Europe, the Internet industry was finalized in the United States, and the economic miracle of Internet + happened in China. Can we say that Internet technology belongs to Europe, the United States or China? It can only be said that most technologies are ultimately long-distance races, and the results belong to all mankind.

Since AI is also a long-distance race, it will eventually form a long industrial chain in terms of time and space. Every advantage is an advantage; every advantage is an opportunity.

This is also the topic I want to discuss at the end of writing this manuscript: China’s AI speech must mention the scene, and talking is the industry, seems to be a bad thing?

On the contrary, this so-called “quick success” is not a bad thing, but the biggest hole card of China’s AI.

We know that AI is a general-purpose technology that can bring value to almost any field, and the source of value is obviously not only on the Internet, but more in various industries to achieve productivity liberation through intelligent technology, such as autonomous driving. , which greatly liberated the productivity of the transportation industry.

In this regard, China has many industries, abundant industrial scenarios, and complex industrial structure, and the whole society has a very high acceptance of smart technology and Crypto-real integration. After years of advancement, the introduction of AI technology into the industry has achieved results in breadth and depth in China.

Opening your mouth is the industry, and shutting your mouth is the scene. This is not because Chinese companies and investors only love money, but because Chinese AI really has industry integration and scene exploration capabilities.

As a counter-example, a large number of AI start-ups in the United States are inseparable from the one-acre three-point land of the Internet. The first stop of ChatGPT’s commercial landing is search, and industrial AI projects are always difficult to scale in the United States.

We have visited Section C of Tianjin Port, which is the world’s first unmanned terminal driven by AI technology in the true sense. However, similar applications are difficult to promote in Europe and the United States. Dock unions will prevent all unmanned and intelligent projects from entering.

Heaped up in the consumer Internet, unwilling to touch the industry, and unable to penetrate the industry’s Western AI circles, the opportunities left to China are hidden in those industries and scenes, and hidden in those commercial values ​​​​full of “copper smell”.

We once said that the real core of the Chinese version of ChatGPT is “industrial scene + ChatGPT-like application”.

Everything is strong, and Chinese AI has scenarios and business paths, which is not a bad thing. Our business prospects are better and the business path is shorter. Of course, we must give priority to the development of commercialization and industrialization. The reason why China’s AI is unique in the world lies in the words “industrial AI”.

Some people will ask again, after talking so much, can’t make a Chinese AI of ChatGPT, has it made something that the United States does not have?

Made it. For example, a well-known operating system in China can solve the problem of intelligent connection of multiple devices in mines and tunnels; a deep learning framework in China, which highlights the capabilities of large-scale distributed training and push-training integration, is suitable for industries, The needs of these financial scenarios.

The innovation and uniqueness of China’s AI comes from industrial thinking and industry scenarios. As the saying goes, come from the people and go to the people.

Interestingly, when I give examples of China’s AI technology achievements, I can’t even name them. Otherwise, many platforms and many readers should naturally have ideas such as “soft articles and advertisements” in their minds. On the contrary, how can American AI technology boast? It doesn’t matter how outrageous the praise is, this may also explain something.

If you really want to make China’s AI stronger and better, you must first stop the erroneous comparison of “they are not short of money, we only love money”. Dai, it doesn’t really mean anything.

Next, we must give full play to our strengths and strengthen our weaknesses, so that AI technology will become the driving force for Chinese-style modernization, and the huge industrial chain will become the source of China’s AI progress.

If we can do more, we should try our best to stop internal friction, stop rivalries between friends and businessmen, stop keeping secrets when we say that Chinese AI is good, and of course stop meaningless excessive self-promotion.

Then, perhaps we can look at issues such as talent training and ecological construction. Only one day, when China has a large number of super-class AI scholars, students and R&D teams, and AI talents from all over the world are willing to join a certain Chinese AI company, then we will have the possibility to discuss the Chinese version of OpenAI.

Otherwise, it is basically useless to rely on a few celebrities to recruit and recruit with some lucrative treatment.

Today, we have reached such a consensus: Chinese football is not about the 11 players; Chinese chips are about the whole of China.

Then you must also know that China’s AI is not a matter of a few companies and a few investors, it is a matter of the Chinese people, and it is a matter of the whole world.

He is strong and he is strong, and the breeze is blowing on the hills; When you are anxious about ChatGPT and Chinese AI, think about these few words.

Source of information: compiled from 8BTC by 0x Information.Copyright belongs to the author, without permission, may not be reproduced

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