Currently, as college entrance examination candidates enter the stage of filling out their college applications, many parents and candidates are seeking help from artificial intelligence (AI). However, some users have provided feedback that the information recommended by some "AI filling in preferences" tools contains obvious factual errors and outdated data, which can easily mislead candidates in filling out their preferences.
In recent years, with the continuous breakthroughs and iterations of AI technology, "AI+" is empowering thousands of industries with unprecedented breadth and depth, and is blooming in more and more application scenarios.
However, it is worth noting that some AI application tools, such as some so-called "AI+" products or services, simply overlay AI technology on existing products and scenarios, making "AI+" superficial and even becoming a marketing gimmick. For example, in the medical field, some "AI doctors" prescribe prescriptions based solely on individual symptoms described by patients, which can easily lead to misdiagnosis; In the field of culture and tourism, some "AI tour guide" applications claim to have built-in voice explanation and photo recognition functions, but the explanation content is like "memorizing texts", which cannot deeply interact with tourists, and photo recognition errors are frequent.
The starting point of these "AI+" products and services may be good, but the problem is that most of them only achieve shallow integration with AI big models, without fully mining industry data or finely customizing for specific scenarios and populations. As a result, they are prone to AI "illusions" and difficult to truly integrate into practical scenarios. They can only scratch the real pain points of the industry, making it difficult to achieve deep and effective empowerment.
Empowering thousands of industries with AI is not simply about adding and rigidly grafting AI onto different scenarios. To promote the implementation of "AI+", we should thoroughly understand the underlying operational logic of various industries, focus on the needs of industry transformation and upgrading, identify the pain points and bottlenecks that constrain industry development, deeply sort out industry vertical data, and seamlessly embed AI into specific business processes, thereby achieving true quality and efficiency leaps.
Taking "AI+Metallurgy" as an example, it is necessary to conduct in-depth research on complex process flows such as sintering, coking, ironmaking, and steelmaking. Starting from high-value scenarios such as intelligent batching, furnace temperature control, converter flame recognition, and steel surface defect detection, we can solve the common problems currently faced by the steel industry and enable AI to solidly promote the green, intelligent, and high-end development of the steel industry.
In fact, the successful attempts of "AI+" in other industries follow a similar approach. In the textile industry, broken fibers can easily cause defects in textiles. The use of AI vision technology for automatic detection of broken fibers has significantly improved the quality of textiles. In the pharmaceutical field, the development cycle of new drugs is long, the cost is high, and the success rate is low. Relying on AI to screen pathogenic targets and design drug molecules can shorten the development cycle, save costs, and improve efficiency. Undoubtedly, only by achieving endogenous collaboration between AI and various industries can "AI+" achieve precise and breakthrough value release, rather than just superficially riding on hot topics and playing with concepts.
To deeply implement "AI+", we must abandon the formalism of "AI for AI's sake" and let AI take root in real-life scenarios, promoting technology from surface grafting to deep integration. Its ultimate goal is to enable AI to reshape production processes and service logic, solve real problems, serve real needs, create real value, promote cost reduction and efficiency improvement, transform and upgrade, and inject strong momentum into the high-quality development of thousands of industries.