With the announcement of the 2025 college entrance examination results, candidates have entered the critical stage of volunteering. Internet giants have launched upgraded versions of AI college entrance examination volunteer filling tools, such as Baidu APP, Quark, Weibo Smart Search, etc., using deep thinking reasoning models and agent applications to provide candidates with personalized and accurate application suggestions, and strive to narrow the information gap and achieve technological empowerment. However, the differences in algorithms and data limitations of each platform have led to differences in suggestions, and AI’s ability to solve the problem of ambiguous planning that is common in candidates’ families still needs to be improved.
At present, the 2025 college entrance examination has been scored and entered the volunteer filling link, and Hurricane’s AI technology is around this to provide assistance for candidates’ families to fill in the volunteer application.
AI Blue Media Hui learned that the mainstream Internet companies in the market have launched corresponding AI products, such as Baidu APP, Quark, Weibo Smart Search, Tencent Yuanbao, etc., all of which are showing their strength.
Compared with the past, this year’s AI college entrance examination volunteer filling products of major manufacturers have achieved further iterations, such as the introduction of deep thinking and reasoning models represented by DeepSeek, such as the addition of Agent applications including volunteer reports, etc.
Major manufacturers hope to use their AI capabilities to bridge the information gap in college entrance examination volunteer applications as much as possible, achieve scientific and technological equality, and improve the efficiency of volunteer filling.
The vision is good.
But there is still no shortage of doubts in the market.
One of the most basic facts is that unlike AI doing questions, it will do, and it will not be. Volunteering for the college entrance examination is essentially a choice and game under the trade-off of multiple information. From score ranking, batch line, professional hot and cold, to employment prospects, personal interests, and inclined cities, every variable affects the whole body.
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AI Blue Media also experienced the mainstream AI college entrance examination volunteer filling products on the market, trying to answer whether AI that is currently close to the doctoral level can meet the needs of candidates’ parents in this link, and which directions should be explored by subsequent manufacturers.
AI to “deep”
“Henan candidates in 2025, physics, score 485 points, which schools can they apply for.”
AI Blue Media Exchange sent the above requirements to Baidu APP, Quark, and Weibo Zhisou’s corresponding college entrance examination volunteer product pages. In a very short period of time, all three products can identify user needs, list the reference colleges and universities according to the three gradients of “rush”, “guarantee” and “stability”, and give the expected probability based on past data, so that candidates and parents know in advance which schools can be prioritized this year and which majors are more likely to be admitted.
For example, on the Baidu APP, with “college priority”, 104 “impactable”, 106 “safer”, and 151 “guaranteed” are listed, specific to each college, and further subdivided into “optional majors”, and also lists the difficulty of specific majors.
Baidu, Quark, etc. also list in detail the enrollment of specific schools and majors in Henan through their own college entrance examination databases, as well as the lowest rankings and lowest scores in the past, which candidates and parents can see at a glance.
While generating application suggestions, Weibo Smart Search (College Entrance Examination Edition) also gives “score positioning and competition situation”, “professional selection strategy”, and “risk warning”. Due to the lack of competitiveness of the Henan candidate’s score of 485, some schools that can be filled in may have high tuition fees, and Weibo Zhisearch has reminded them accordingly.
These are all to further simulate the decision-making process of candidates’ families filling in the college entrance examination volunteers.
It is clear that it is the change brought about by the reasoning model based on deep thinking.
AI Blue Media Hui learned that in the past many years, large manufacturers have also been laying out the college entrance examination volunteer filling products, but at that time it was mostly big data technology based on database screening, but after the addition of large models, especially the deep thinking model represented by DeepSeek, in addition to giving filling suggestions, it can also intuitively show candidates “what” and “why”.
Especially in further processing the more personalized needs of candidates, it is smarter than before.
On the basis of the above questions, after adding the personalized needs of “biased towards engineering, also accepting arts and sciences, and first-tier cities first”, Quark conducted a detailed dismantling and analysis of the candidate’s needs through the agent application of “volunteer report”, and the corresponding “rush”, “stability” and “guarantee” were also aimed at about 10 in a straight line from hundreds of before.
Baidu and Weibo intelligent search are in the form of chat dialogue to further meet the more personalized needs of candidates.
Taking Weibo Smart Search as an example, in the process of deep thinking, it can be clearly seen that AI first conducted a targeted search on the whole network around this demand to judge the past admission institutions of the user’s ranking and score, and at the same time extracted key points and matched the corresponding application strategy.
For example, the grain engineering major of Henan University of Technology has close cooperation with COFCO and other enterprises; the industrial design of Zhengzhou University of Light Industry is highly recognized in the Pearl River Delta manufacturing enterprises.
It can be seen that since the beginning of this year, the AI college entrance examination volunteer products of major manufacturers have become more “deep” in filling the information gap, understanding user portraits, interest preferences, etc., and at the same time, based on these in-depth understandings, the filling suggestions given are also more professional.
There are still pain points
However, AI Blue Media Hui also noticed that no matter how the AI college entrance examination volunteer products of large companies compare with themselves, once they are compared horizontally, there is a very confusing problem – the same demand, different answers.
In essence, there are limitations to each other’s algorithms.
On the one hand, the training data of each product is different, and the algorithm weights are different, and the results of model training will naturally be biased for the specific scenario of “non-standard” volunteer filling in the college entrance examination. On the other hand, it is mainly based on the fact that AI cannot fully grasp first-hand information, and there is still a lot of noise in the database itself.
And this inevitably makes candidates wonder whether AI’s suggestions are reliable.
In addition, there are many candidates’ families in China who do not have enough information accumulation to lack a clear life plan. The real dilemma they face is vague interests, weak sense of direction, and limited professional cognition.
In fact, Baidu Quarks are also aware of this problem, in addition to giving suggestions and decisions, the above-mentioned agent functions such as AI chat volunteering are hoping to further tap users’ interests and personalization.
However, the core pain points are still not fully addressed.
When users can put forward clear needs to AI, the interactive way of AI chatting about volunteering can greatly improve the efficiency of volunteer filling. But on the contrary, for those student families who cannot accurately plan their lives and have vague cognition, AI products have not made achievements in solving this precursor link.
Many tool-based AIs on the market still use the deterministic model of “input requirements or data-algorithm rules-output results”. This means that when dealing with non-standardized problems, it is difficult for these AI tools to correlate multi-dimensional information, making it prone to noise.
For example, when a student proposes to “choose a promising major”, the tool-based AI can only output results based on standardized indicators such as employment rate and salary data, but cannot dismantle the personalized dimensions behind the “prospect”, such as interest matching, regional development tendencies, etc., or the real needs of many students’ families are often hidden in vague expressions such as “my child has average grades and wants to go to college”, but AI cannot clarify the deep goals through multiple rounds of questioning.
In other words, in the scenario of non-standard and vague needs, the “algorithm” is not omnipotent, and the AI college entrance examination volunteer filling product should be transformed into a “cognitive assistant” to conduct a “heuristic search” on candidates.
At this time, based on the information square related to the college entrance examination, the experience of those who have been there, the guidance of big Vs, the suggestions of college entrance examination volunteer filling experts, and the latest real-time changes in college information and professional information, etc., are particularly important.
On the one hand, it is the information gap, especially the further filling and contrast of the first-hand information gap, on the other hand, in this information square, candidates can discover their interests and preferences, and under the guidance of experience, suggestions, etc., they can develop their own life plans.
AI Blue Media Hui learned that Weibo embeds the college entrance examination volunteer filling product into the intelligent search system, relying on the content ecology of the Weibo platform, and integrating the information of a large number of industry big Vs, experts, media and other authoritative professionals active on the platform, and has made a slight step forward in solving the above problems.
For example, for the candidate’s volunteer application, after generating the filling suggestions, Weibo Zhisearch also attached very vertical and real-time high-quality blog post information. “Treasure University Amway Plan”, “Professional Application Guide”, “Henan Undergraduate Score Line” and other tags under the tags, such as big V, experts, etc., and even the experience of students from related schools as visitors, etc., to help students’ families understand what they want, and at the same time bring a sense of closeness and trust that is different from AI.
“Human experience” is always vivid, vivid, and warm. In the college entrance examination volunteer application scenario, these massive “human experiences” are excellent supplements in addition to algorithms and AI, further assisting candidates to discover, explore, and understand.
Content ecology is the key
In fact, in recent years, major manufacturers have also realized this problem.
In particular, when everyone maintains the same level of technical level, when deep thinking models and agent applications become the standard configuration of large factories, under the homogeneity of technology, on the one hand, the focus of competition is naturally to turn to data freshness, scene understanding depth and ecological barriers, and try to improve the roles and strategies of AI experts to let AI evolve in the direction of real experts as much as possible Multi-dimensional experience with real-time interaction.
And this shows that the content ecology has become the core competition point.
For example, Quark has built a college entrance examination knowledge base covering more than 2,900 colleges and universities across the country and nearly 1,600 undergraduate majors, and Baidu has introduced more than 20,000 real seniors and seniors online to share Q&A, more than 10 big names in college entrance examination topic conversations and other services this year.
Weibo Smart Search is backed by Weibo, so it naturally has a fertile soil.
Based on the exclusivity of social media, during the hot topic of college entrance examination volunteering, Weibo’s own huge PUGC content, big V matrix, and strong interactive community can continuously output relevant “human experience”.
Even most of them are spontaneous, unique to the market, and of high quality.
For example, on June 23, Wang Xingxing, the founder of Yushu Technology, posted on Weibo, putting forward some application suggestions for college entrance examination candidates.
The practical suggestions he put forward and the personal experience of the industry can be said to solve the blind spot of AI to some extent.
Moreover, Wang Xingxing, as a current entrepreneurial star, starts from his personal experience, Wang Xingxing’s personal perception, and this close interaction itself cannot be brought about by mechanical AI.
For example, Zhou Hongyi’s life advice on Weibo that “failure in the college entrance examination does not mean failure in life”, such as expert Lou Lei said that it is not recommended that candidates gamble on AI majors and other voices, these high-quality content are aggregated in Weibo smart search, and will also be presented in Weibo Square in the form of relevant hot search tags, so as to better serve the volunteer filling needs of candidates’ families.
The insights, experiences and emotional resonance of real, professional, and highly trusted experts, big Vs, and people who have been there on these platforms are not only extremely scarce content, but also the information supply urgently needed by candidates’ families, and they are also constantly fed to AI on Weibo Smart Search for efficient aggregation, screening and structuring.
This forms a virtuous ecological cycle.
It is not even focused on the college entrance examination scenario, but also serves a wide range of AI search application scenarios.
The market also knows that whether it is Baidu Quark or Tencent Yuanbao Weibo Smart Search, behind the application scenario of college entrance examination volunteer filling in by major manufacturers is the secret battle based on AI search.
In the expectations of practitioners, the era of AI search is destined to come, because compared with traditional search, the imagination space of A search is to improve efficiency and become a practical and reliable life and work assistant.
But it is still in the exploratory stage.
Baidu, Alibaba, Tencent, etc. continue to lay out and iterate on large models, intending to keep up with OpenAI’s upcoming GPT5, while Weibo Smart Search provides a more solid content soil for AI search through two-way empowerment of AI technology and content ecology.
With each other’s consistent cultivation, AI search gradually has the possibility of becoming the prototype of Iron Man’s AI butler “Jarvis”.
