After entering April, the volatility of the concept of galaxies has gradually stabilized from violent explosions and plummets, and it is no longer constantly rising or falling.
But the subject of quantitative capital is excepted.
Other listed subsidiaries of Qunxingxing have successively disclosed annual reports at the end of March, but Quantitative Capital has not yet released its annual report.
Although the annual report will be disclosed by the end of April at the latest, other subsidiaries of Qunxingxing have disclosed it. Only Quantitative Capital has made no move. Everyone thinks that this company's annual report may have a big surprise.
In addition to this concern of investors, Quantitative Capital stock has risen the most before, from 6.46 yuan to 22.54 yuan, with a cumulative increase of 248.92%. Other stars have fallen sharply, so this vote is definitely There is a need to make up for the decline.
…
Wednesday, April 3rd.
At around 10:20 in the morning, Fang Hong arrived at the headquarters of Stars Capital, but his destination was not Stars Capital, but a building next door.
The 23rd floor of that building is the headquarters of Quantitative Capital.
"I didn't expect Mr. Chen to come out to greet him personally. Who is the handsome guy who calls himself Fang Hong?" At this moment, the two girls at the front desk of Quantitative Capital Company saw Chen Yu leading Fang Hong towards the inside of the company, and they couldn't help but Discuss with curiosity.
"They look like they are about the same age, maybe they are classmates or something..." the girl next to her speculated, and her colleague couldn't help but said in a flirtatious manner: "They are both so handsome..."
At the same time, Chen Yu, who came out to receive the reception, took Fang Hong into his office.
The two came to the sofa in the rest area and sat down. Fang Hong looked at Chen Yu who was sitting opposite him and said with a smile: "I heard recently that Qin Feng wants to recruit you into his SOCL computing language department, and Lao Huang also wants to invite you to join. Nvidia."
Hearing this, Chen Yu said: "I have always wanted to build a more accurate artificial intelligence quantitative trading model. The complexity of the model is getting higher and higher, and the corresponding requirements for data parameters and computing power resources are getting higher and higher. The algorithm , computing power, and data are all indispensable, especially the shortage of computing resources. If the existing hardware can meet the computing power I need, the cost is too high, and the efficiency is still too slow..."
The implication is that the current hardware level cannot keep up with his requirements.
Chen Yu said: "When we usually run models, whether it is deep learning training or inference, the first question is how much video memory is needed. Why is Xingyu Technology's graphics processor so fast? One of the reasons is that general-purpose memory gets rid of PCie The restrictions allow the CPU and GPU to exchange information faster."
"I think Xingyu Technology's SOCL has great potential and has its own ecosystem foundation. It is the most likely to challenge Nvidia's CUDA status, although it seems that there is no competition between the two parties now."
Fang Hong, who heard this, looked at him with suspicion.
Chen Yu looked at him and said in a deep voice: "But Qin Feng obviously did not realize the relationship between GPU, CPU, SOCL and AI and its significance in the field of artificial intelligence. No, it should be said that he is conscious. At least he understands better than Wall Street, otherwise There would have been no SOCL, but Qin Feng’s emphasis was far from being as high as that of the STAR series of smartphones.”
Fang Hong was quite happy, this Chen Yu was definitely a talent.
The Quantitative Capital he founded now has more than 300 employees. Fang Hong has already known the general situation of this company, but more than 80% of its employees have academic backgrounds in computer science, physics or mathematics, including top students. Chen Yu himself also has such an academic background.
Now they are studying capital markets and doing investment transactions, but this team has transformed into a powerful technology development team.
After a while, Chen Yu opened the computer on the table and said to Fang Hong: "This is a self-learning neural network AI model we ran. It has watched tens of millions of videos on Yixing Video. The goal is image recognition, but the problem is insufficient computing power. If you want to achieve this goal, you need the support of thousands of CPUs, but if you switch to GPU, you can get it done with only seven."
Hearing this, Fang Hong stared at the screen and said: "Well, I know what you want to say. Although a single computing unit of the GPU is not as versatile as the CPU, it can perform a large number of calculations at the same time."
Fang Hong's identity as the original owner in this life was that he was born in the computer science department. Although he may not be able to compare with Chen Yu and Xu Jingren in this aspect, there is no problem if he applies for a job at a major technology company. This is an advantage that other investors do not have.
Chen Yu nodded and said: "Yes, just like the printing performance at the opening ceremony of the 2008 Olympic Games. It would be quite complicated to let one or a few people who grasp the overall changes control the array in real time, but the actual performance Each member only needs to remember when to stand up and when to squat down, so that the whole can present a complex and changeable effect."
"These members are like small computing units in the GPU. Although they do not master global information, they can produce the desired effect by working together. AI computing is a scenario that requires a large number of operations at the same time. , including the AI trading model we run. Now we are using GPUs for deep learning training."
"If we just say that GPU is more suitable for AI, it will definitely not be the case, but we have to mention NVIDIA's CUDA and Xingyu Technology's SOCL. Lao Huang released CUDA1.0 five years ago, which is a computer that uses GPU to perform calculations. Although the parallel computing platform and programming model are mainly used to accelerate image processing, there is nothing revolutionary."
"But I believe that Huang has identified the potential of using GPUs for computing. The best proof is that he spares no effort to support it. Every Nvidia chip supports CUDA, and at the same time, CUDA is open to the public, and he intends to create The CUDA ecosystem speaks for itself.”
At this moment, Fang Hong had a general idea of Chen Yu, but he did not speak, but continued to listen to Chen Yu calmly: "Nvidia's current stock price is around US$12, and its total market value is less than US$7.5 billion. It can be seen that Wall Street does not understand it, let alone what artificial intelligence is. In the eyes of Wall Street, in order to cooperate with the CUDA framework, NVIDIA doubled the cost of graphics cards but could not sell them at a higher price. The profits were once too low to help look."
Fang Hong remained calm at this moment, but he was happy in his heart. Shi Yao had discovered a treasure, and he was quite accurate in the field of artificial intelligence and the potential of Nvidia.
Fang Hong, who has memories of his past life, is very clear that if nothing unexpected happens, Nvidia will soar in the next few years. First, it will step into the cryptocurrency mining trend and the huge demand for computing resources will take off. Mining Artificial intelligence took off at this time when the tide had just passed.
Ten years later, when ChatGPT became popular, within a few days, a company came out to claim how powerful a new model it had released was. One of the indicators was how many high-quality GPUs the company claimed it had. Whenever a company announced that it had the ability When participating in this competition in the AI field and unable to produce a product, they will talk about how many NVIDIA A100 graphics cards their company has, and they will soon be able to release their own large models.
It can be said that the AI track at that time was almost inseparable from NVIDIA's hardware supply. NVIDIA was also equivalent to the underlying infrastructure company of AI, and it almost monopolized the industry. If other companies wanted to play with large models, they would not have NVIDIA graphics cards. no.
But now apparently not many people are aware of this. Even Wall Street keeps asking why no one insists on why NVIDIA is doing things like CUDA. This has caused NVIDIA to be abandoned by capital, and its stock price once plummeted by more than 90% and reached It's still at a low level now.
At this moment, Nvidia’s market value is not even US$75, and Xiaomi’s valuation is US$40 billion.
The capital on Wall Street cannot understand it, but Fang Hong knows that some people understand it. Currently, there are at least two people in China who understand it.
One is Chen Yu in front of him. Judging from his discussion, it is obvious that he firmly believes that GPU will become the standard in the field of deep learning in the future. Another person who understands is Qin Feng. Xingyu Technology launched new businesses this year, including computers, tablets, etc., and SOCL also came into being.
At this point in time, Fang Hong certainly cannot let Huang’s NVIDIA monopolize the supply of underlying hardware for AI.
…
(End of chapter)
