GuShiio.com ①DeepSeek was born to let the market see the forward-looking layout of quantitative private placement on AI;
② Two major advantages: no shortage of money, no urgent pressure to commercialize; no shortage of people, gathering the brightest “heads”;
③ Ten billion quantitative private placements have been added one after another, and the development of artificial intelligence in China seems to be even more worth looking forward to.
Financial News Agency, February 25 (Reporter Yan Jun)While DeepSeek is driving global capital to reassess the value of China’s technology investment, it is also behind the forward-looking nature of quantifying the private equity industry’s layout in artificial intelligence.
Recently, tens of billions of dollars in quantitative Kuande’s WILL Intelligent Learning Laboratory talent recruitment, and nearly 10 billion dollars in quantitative private equity Mengxi Investment AI Lab was launched new, openly recruiting a team of machine learning interns and shouting the slogan of “becoming a factor that changes the world.”
The development of quantitative private placement is accompanied by machine learning and deep learning technology, and it is also the early group that successfully applied artificial intelligence technology to financial markets.
In addition to magic squares, head quantitative private placements including Jiukun Investment and Mingyu Investment have laboratories and North American Investment Research Centers respectively. Although quantitative private placements including Black Wing Assets and Pansong Assets have not established a special AI laboratory, AI applications run through the company’s investment process.
Quantitative investment requires the application of mining factors such as deep learning in daily investment research. It is exposed to artificial intelligence earlier and has a deeper understanding. At that time, a large number of chips were invested for investment needs, and a group of smart “heads” were gathered.First, there is no shortage of money, and second, there is no shortage of people. This is also the basis for cultivating a purely technical model in quantifying the soil.
DeepSeek is customized as a small company with its values to make technology better and its goal is AGI (General Artificial Intelligence). It promotes the progress of the technology community through open source. Therefore, there are no commercialization and financing considerations in the short term.From the industry’s perspective, without the commercial pressure brought by financiers, quantitative private equity teams are generally small in size, and the high efficiency brought by agile teams allows artificial intelligence companies with quantitative backgrounds to go further.
When these tens of billions of quantitative private placements are added one after another, the development of artificial intelligence in China seems to be even more worth looking forward to.
It is worth noting that many companies have said that laying out AI does not mean entering large models, and there are still many innovative implementation methods at the application level. “DeepSeek’s big model is already very advanced and open source. There is no need for the company to make big models again.” A certain head quantitative private placement said.
Exploring cutting-edge technologies, Mengxi invested in establishing AI Lab
“The future is here, waiting for you to open the box.” After the establishment of the AI Lab Laboratory under Mengxi Investment, the recruitment of interns was launched. According to the recruitment profile, the main recruitment target is machine learning researchers (AI), with three job responsibilities: one is to use machine learning models to develop quantitative trading strategies; the second is to track cutting-edge models and technologies in the field of machine learning and try to use them in the field of quantitative finance; The third is to use machine learning and deep learning methods to research, analyze and count historical data to find relevant trends and laws.
The reporter from Cailian also learned that although it is an internship position, interns can have access to a real factor library and desensitized platform data. The company hopes that these young people can play a supporting role while providing creativity and diverse thinking models.
Interestingly, the AI Lab laboratory is in Hefei and its office is in Shanghai. Why did it abandon Shanghai’s university resources and go to Hefei to recruit people?
It is understood that this may be related to Li Xiang, the founder of Mengxi Investment. Public information shows that Li Xiang is from Anhui Province and graduated from University of Science and Technology of China. He is currently an industry instructor for the Master of Finance (MF) graduate student of University of China. He placed the laboratory in Hefei. On the one hand, it is to find alternative ways to preferably meet outstanding students of University of Science and Technology of China, and there is also a feeling of giving back to his alma mater. “Hefei’s university foundation and scientific and technological genes have long been important.” There are also industry people who commented.
It is reported that Mengxi Investment upgraded its intern fund in Hefei, Anhui Province in July 2023. Previously, there were also internship positions such as quantitative strategy researchers, machine learning researchers (AI), high-frequency development engineers (C++) and data development engineers. Recruitment.
Quantitative private placement has always attached great importance to talents. Black Wing Assets said that the company has systematically cultivated all types of talents and created three major recruitment plans, the “Fuyao Plan” for interns, the “Wing Plan” for campus recruitment for recent graduates around the world, and the “Kunpeng Plan” for social recruitment established for mature and top talents.
In terms of retaining talents, Black Wing Assets introduced that in addition to providing competitive salary and benefits, it pays special attention to employee happiness, including basic benefits such as wages, bonuses, project incentives and health insurance. In addition, we pay attention to the overall development of employees and provide employees with a high-quality working environment, continuous training courses and the latest technical equipment. At the same time, design clear career development channels so that employees can effectively plan their career prospects.
40 billion giant Kuande WILL Laboratory simultaneously recruits personnel
Kuande Investment also released the recruitment of AI laboratories. On February 24, the 40 billion giant Kuande Investment released a tweet on talent recruitment for its intelligent learning laboratory.
The path of Kuande WILL Laboratory is similar to DeepSeek. The original intention of the company was to think strategically about AI. With the support of Kuande Investment, WILL will serve as an independently incubated and independently operated entrepreneurial laboratory, focusing on a super technology assistant in the field of scientific research.
According to the recruitment, the key recruitment direction of WILL Laboratory focuses on researchers and engineers with solid AI technical foundation and scientific research ideals, and said it hopes to “jointly participate in this intelligent scientific research journey that requires long-term investment.”
In terms of AI technology accumulation and development planning, Kuande Investment introduced that it has continued to make systematic investment in the field of quantitative research for many years and built complete AI infrastructure and data processing capabilities. WILL will continue the excellent gene of Kuande Investment, starting with quantification but not just financial scenarios, and setting sail towards the stars of artificial intelligence.
In the golden age of AI development, mature technical teams can provide solid guarantee for AI research and development, and a sound talent training mechanism can support innovation iteration. This is also the reason why Kuande invests in recruiting talents.
Jiukun, Mingyu and other heads have layout
Although many quantitative private equity investors have said that they may be suspected of “riding the heat” in promoting their AI layout, the market is still concerned about this information on AI.
Jiukun Investment and Microsoft Research Asia recently published an article stating that they have successfully reproduced DeepSeek-R1 for the first time, especially its results in the field of enhanced learning, while providing innovative insights at the technical level. The academic article is called Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning, and was co-written by Microsoft Research Asia, Ubiquant and other independent researchers.
According to the paper, the team also discovered for the first time that output length has nothing to do with improvement in inference performance, that language mixing (such as mixing Chinese and English) will significantly reduce inference ability, and that reasoning tokens do improve inference performance.
It is reported that Jiukun Investment has established AI lab very early and has strong technical reserves and talent reserves in terms of data, algorithms, and computing power. Since 2020, it has successively established artificial intelligence laboratories and data laboratories. The laboratory and the water drop laboratory correspond to research in areas related to data, algorithms, and transaction execution respectively. In addition, the company will also cooperate with the Guangdong-Hong Kong-Macao Greater Bay Area Digital Economy Research Institute to establish the “Jiukun-IDEA” joint laboratory in 2021 to explore new cooperation and development models in the field of digital finance.
In recent years, Jiukun Investment has continued to conduct systematic and in-depth research in the field of cutting-edge AI technologies. It not only explores general technologies for a long time and promotes their scenario applications, but also conducts diversified research and expansion in multiple sub-fields to strive to build a more comprehensive AI technology system.
Also having corresponding reserves in AI is Minghao Investment. In 2020, Minghao Investment established an investment research center in North America to provide world-leading technical support for the A-share stock picking model. The algorithm iteration speed of the model is based on high-performance computing power. From a few simple CPU servers in the early days to large-scale high-performance computing clusters, Mingyu has been actively building its own high-specification computing power rooms to further improve its supercomputing processing capabilities and levels.
At present, Mingyi Investment’s own high-performance computing cluster has thousands of GPU cards, tens of thousands of CPU cores, and memory and disk storage with superimposed multi-Pb. In the application scenario of financial data, the AI computing power can reach 400P Flops, ranking among the top 500 list of the world’s supercomputing rankings.
What talents do quantitative giants like?
Ten billion private equity black wing assets have also been deploying the artificial intelligence field since 2017 and established an AI algorithm team. They have been cultivating and reserving data analysis and machine learning talents. Even if no special AI laboratory has been established, full-process AI has been implemented in quantitative investment.
“In terms of employment standards, we prefer AI talents who have a deep understanding of machine learning and deep learning technologies, and are full of love and curiosity.” Black Wing Assets said that if you have research internship experience in well-known AI-related laboratories, research institutes and companies at home and abroad, have rich research results, have published relevant papers in international top conferences or journals, or have ACM/IOI/NOI/Top Coder/Kaggle and other algorithm competitions, you will be more rewarding.
Pansong Assets said that in recent years, there are three main reasons why the quantitative industry has concentrated on recruiting artificial intelligence talents such as deep learning:
The first is the exponential growth in data dimensions and complexity. At present, traditional quantitative models have difficulty efficiently mining effective signals in unstructured data, and AI technology is urgently needed to achieve fusion analysis and feature extraction of multimodal data.
Second, the deepening of market games has put forward higher requirements for strategic adaptability. The advantages of deep learning in nonlinear relational modeling and dynamic pattern recognition can help strategies capture market microstructure changes faster.
Third, the competition for technical barriers has risen to a strategic level. The quantitative industry is gradually building a closed-loop ecosystem of “AI+ quantitative”, which requires teams to have interdisciplinary collaboration capabilities, and compound talents have become scarce resources.
Just like Black Wing Assets, many quantitative private equity investors interviewed told reporters from Financial News Agency that the application of AI to strategies is a common phenomenon in the industry. Pansong Assets said that AI technology currently has three main applications: one is to refine data to achieve more precise characterization of systematic investment logic and mine factors with more economic implications; the other is to empower the investment process; Third, in the company’s internal operations, an efficiency committee has been established, which is responsible for using artificial intelligence technology to improve the efficiency of daily work and operations.
Interestingly, there are not many talents with overseas backgrounds on DeepSeek’s team, and some market participants are worried that overseas hedge funds do have a “siphon effect” on top talents with their global brands, mature training systems and more attractive salary structures. In the battle for talents, what do China’s localized institutions need to do well?
Pansong Assets believes that localized institutions still have strong advantages for three reasons:
First of all, the local market’s in-depth awareness and agile response capabilities.China’s capital market has certain characteristics in terms of trading mechanism and investor structure. Localized institutions can have a deeper understanding of the investment logic of the A-share market, while systematic investment can deeply explore the economic logic of market phenomena. To establish a more accurate mapping relationship through historical experience and data precipitation, the research process needs to penetrate both the “interpretability” of economic logic and the “statistical significance” of the model. Local institutions have natural advantages in long-term accumulation of data samples and sensitivity training. This “logic + data” dual verification mechanism can significantly enhance the confidence of factor mining and the continued vitality of strategies, while overseas institutions often need longer. Adaptation cycle.
Secondly, the efficiency of scenario implementation of technological innovation.The domestic team is closer to the “high volatility and strong game” characteristics of the local market in terms of strategy iteration speed and model fault tolerance mechanism design, which is crucial to the practical value transformation of AI talents.
Third, the compatibility of organizational culture and long-term incentive design.Compared with overseas institutions, localized private equity institutions can enhance their appeal to top talents through a flat decision-making mechanism, deep coupling of technology and investment research (such as the “researcher-engineer” dual-track promotion channel), and medium-and long-term binding methods such as equity incentives.
