DeepSeek is driving global capital to reevaluate the investment value of Chinese technology, and behind it is the forward-looking layout of the quantitative private equity industry in artificial intelligence. Recently, under the billion-dollar quantitative fund Kuandet, the WILL Intelligent Learning Laboratory announced talent recruitment, and the billion-dollar quantitative private equity Monarch Investment AI Lab launched a new recruitment initiative, openly recruiting a team of machine learning interns and declaring a slogan of "become the factor that changes the world." The development of quantitative private equity is accompanied by machine learning and deep learning technologies, and they are among the first group to successfully apply artificial intelligence technology to financial markets. In addition to Huizong Investment and Mingchuang Investment, other leading quantitative private equity firms have established laboratories and North American investment research centers. Companies like Heiwing Asset and Panson Asset, although they have not established dedicated AI laboratories, have integrated AI applications into their investment processes. Quantitative investing requires the use of deep learning and other factors in daily investment research, and those who have had earlier exposure to artificial intelligence have a deeper understanding. At that time, in order to meet investment demand, a large number of chips were invested, along with a collection of a group of clever minds. Lacking neither money nor people, this is also the basis for cultivating pure technical models in the quantitative field. DeepSeek defines itself as a small company with the core values of improving technology and aiming for AGI (artificial general intelligence). By promoting progress in the technology community through open-source initiatives, the company does not consider commercialization or financing in the short term. In the industry's view, without financing pressure to commercialize, quantitative private equity teams are typically not large, and the efficiency brought by agile teams is what enables AI companies with quantitative backgrounds to go further. With these billion-dollar quantitative private equity firms gradually joining in, the development of artificial intelligence in China seems more promising. It is worth noting that several companies have stated that their AI layouts do not necessarily mean they are entering the realm of large models, as there are still many innovative ways to implement AI at the application level. "DeepSeek's large models are already very advanced and open-source, so the company does not need to develop large models further," said a top quantitative private equity firm. Exploring cutting-edge technologies, Monarch Investment establishes AI Lab "With the future already here, waiting for you to unbox." After the establishment of the AI Lab under Monarch Investment, the recruitment of interns has begun. According to the job description, the main recruits are machine learning researchers (AI), and the responsibilities include developing machine learning models for quantitative trading strategies, tracking advanced models and technologies in the field of machine learning and attempting to apply them to the quantitative finance field, and studying, analyzing, and statistically analyzing historical data using machine learning and deep learning methods to identify trends and patterns. It was reported that although it is an internship position, interns will have access to real factor databases and anonymized platform data. The company hopes that these young people can assist while providing creativity and diverse modes of thinking. Similar to other quantitative companies recruiting technical personnel, the AI Lab requires candidates to have experience in various competitions such as Kaggle, in addition to their educational qualifications. Interestingly, the AI Lab is located in Hefei but the office is in Shanghai. Why did they choose Hefei over the resources available in Shanghai? It is understood that this may be related to Monarch Investment's founder, Li Xiang. Public information shows that Li Xiang is from Anhui, graduated from the University of Science and Technology of China, and is currently a teacher at the University of Science and Technology of China's Master of Finance (MF) program. Placing the laboratory in Hefei may not only allow them to access outstanding students from the University of Science and Technology of China, but also reflects a sense of loyalty to their alma mater. "The foundation and technological genes of universities in Hefei have long been underestimated," commented industry professionals. It is reported that Monarch Investment upgraded the intern fund in Hefei, Anhui in July 2023. Previously, they had internship positions in quantitative strategy research, machine learning researcher (AI), high-frequency development engineer (C++), and data development engineer available for recruitment. Quantitative private equity firms have always valued talent development. Heiwing Asset stated that the company systematically cultivates various talents and has launched three major recruitment plans: the "Fuyao Plan" for interns, the "Yuyi Plan" for campus recruitment of global graduates, and the "Kunpeng Plan" for mature top talent. In the aspect of retaining talent, Heiwing Asset introduced that in addition to providing competitive salaries and benefits, they pay special attention to the happiness of employees, including providing basic benefits such as wages, bonuses, project incentives, and health insurance. They also focus on the comprehensive development of employees, providing a high-quality working environment, continuous training courses, and the latest technological equipment. Additionally, they design clear career development paths to allow employees to effectively plan their career prospects. 400-billion-dollar giant Kuandet WILL Lab also recruits in sync Similarly, Kuandet Investment, a 400-billion-dollar giant, released a tweet on February 24 announcing the talent recruitment for its WILL Intelligent Learning Laboratory. The path of Kuandet's WILL Lab is similar to DeepSeek, as the company was founded with strategic considerations for AI. With the support of Kuandet Investment, WILL will operate as an independent incubator, focusing on a super tech assistant in the field of research. According to the recruitment information, the WILL Lab is mainly recruiting researchers and engineers who have a solid foundation in AI technology and have scientific research ideals, hoping they can "jointly participate in this long-term intelligent research journey." In terms of AI technology accumulation and development planning, Kuandet Investment stated that they have been investing systemically in the field of quantitative research for many years, building a complete AI infrastructure and data processing capabilities. WILL will continue the excellent genes of Kuandet Investment, starting with quantitative but not limited to financial scenarios, and setting sail towards the vast ocean of artificial intelligence. In this golden age of AI development, mature technical teams can provide a solid guarantee for AI research and development, and a sound talent development mechanism can support innovation and iteration. This is also the reason for Kuandet Investment's recruitment of talent. Leading firms such as Jiukun and Mingchuang also have their layouts Although many quantitative private equity firms have stated that their promotion of AI layouts may be seen as "riding the wave," the market still pays attention to these developments.Quantifying the head in terms of information in AI.Nine Kun Investment and Microsoft Asia Research Institute recently published an article stating that they have successfully reproduced DeepSeek-R1 for the first time, especially its achievements in the field of reinforcement learning, and have also proposed innovative insights at a technical level. The academic article is titled Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning, co-written by Microsoft Asia Research Institute, Ubiquant, and other independent researchers. According to the paper, the team also discovered issues such as the length of output being unrelated to reasoning performance, language mixing (such as mixing Chinese and English) significantly reducing reasoning ability, and the fact that reasoning tokens do improve reasoning performance. It is reported that Nine Kun Investment, also a quantitative giant, established an AI lab early on and has strong technical reserves and talent reserves in data, algorithms, and computing power. Starting in 2020, they established the Artificial Intelligence Laboratory, the Data Laboratory, and the Droplet Laboratory, corresponding to research in the areas of data, algorithms, and trade execution. In addition, the company also cooperated with the Greater Bay Area Digital Economy Research Institute in 2021 to establish the "Nine Kun-IDEA" joint laboratory to explore new modes of cooperation and development in the field of digital finance. In recent years, Nine Kun Investment has been actively conducting systematic and in-depth research in the frontier technology field of AI. They have not only been exploring general technologies and promoting their application scenarios, but have also been conducting diversified research in multiple niche areas to build a more comprehensive AI technology system. Another player with corresponding reserves in AI is Minghong Investment. In 2020, Minghong Investment established a research center in North America to provide cutting-edge technological support for A-share stock selection models. The model's algorithm iteration speed is based on high-performance computing power. From early simple CPU servers to large-scale high-performance computing clusters, Minghong has been actively building high-spec computing facilities to further enhance supercomputing processing capabilities. Currently, Minghong Investment's self-owned high-performance computing cluster has thousands of GPU cards, tens of thousands of CPU cores, and stacked memory and disk storage of multiple Pb. In the application scenarios of financial data, the AI computing power can reach 400P Flops, ranking highly in the world's supercomputing TOP500 list. What kind of talents do quantitative giants like? Black Wing Asset Management, a billion-dollar private equity firm, has been focusing on the field of artificial intelligence since 2017 and has formed an AI algorithm team, constantly cultivating and reserving talents in data analysis and machine learning. Even without establishing a dedicated AI laboratory, they have already achieved full-process AI optimization in the quantitative investment process. "In terms of recruitment standards, we prefer AI talents who have a deep understanding of machine learning, deep learning technology, and are filled with passion and curiosity for AI," said Black Wing Asset Management. Having research internship experiences in well-known AI labs, research institutes, and companies at home and abroad, having rich research achievements, publishing relevant papers in top international conferences or journals, or having won awards in algorithm competitions such as ACM/IOI/NOI/Top Coder/Kaggle will be a plus. Pansong Asset Management stated that in recent years, the quant industry has been recruiting talents in deep learning and other artificial intelligence fields for three main reasons: Firstly, the exponential growth in data dimensions and complexity. Traditional quantitative models are finding it difficult to efficiently extract effective signals from unstructured data, and they urgently need AI technology to integrate and analyze multimodal data for feature extraction. Secondly, the deepening market competition requires higher adaptability of strategies. The advantages of deep learning in modeling nonlinear relationships and dynamic pattern recognition can help strategies quickly capture changes in the market's microstructure. Thirdly, the competition in technological barriers has risen to a strategic level. The quant 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 Asset Management, several interviewed quant private equity firms told Cailian press reporters that applying AI to strategies is a common phenomenon in the industry. Pansong Asset Management stated that AI technology currently has three main applications: fine-tuning data for a more detailed characterization of systematic investment logic, empowering the investment process, and internally establishing an efficiency committee to use AI technology to enhance the efficiency of daily work operations. Interestingly, there are not many talents with overseas backgrounds in the DeepSeek team, and some market participants are concerned that hedge funds abroad do attract top talents with their global brand, mature training systems, and more attractive compensation structures, forming a "sucking" effect. In the talent war, what do Chinese local institutions need to do? Pansong Asset Management believes that local institutions still have strong advantages, for three reasons: First, a deep understanding of the local market and agility in response. The Chinese capital market has certain characteristics in terms of trading mechanisms and investor structure. Local institutions can better understand the investment logic of the A-share market, systematically dig deeper into the economic logic behind market phenomena, establish more accurate mapping relationships through historical experience and data accumulation, and research processes that simultaneously penetrate the "interpretability" of economic logic and the "statistical significance" of models. Local institutions have a natural advantage in long-term data sample accumulation and sensitivity training, and this dual verification mechanism of "logic + data" can significantly enhance the confidence in factor exploration and the sustainability of strategies, whereas foreign institutions often require a longer adaptation period. Secondly, the scenario-based efficiency of technological innovation. Domestic teams are more closely aligned with the characteristics of the local market, which is characterized by "high volatility" and "strong game-playing." This is crucial for the practical value realization of AI talents in strategy iteration speed and model fault tolerance mechanism design. Thirdly, organizational culture compatibility and long-term incentive design. Compared to overseas institutions, local private equity firms can achieve better decision-making mechanisms through flat decision-making mechanisms, deep coupling of technology and research (such as the dual track promotion channel of "researcher-engineer"), and equity...Incentive schemes such as medium- to long-term vesting methods enhance the attractiveness to top talent.This article is republished from Caijing Society, edited by GMTEight: Chen Wenfang.