Applications from AutoML technology
Artificial intelligence used to be a tool reserved for people who knew how to code and understand algorithms. Now, with AutoML, AI can teach itself how to create a new AI system.
When AI Learns to Build Itself with AutoML
According to Tuoi Tre Online , AutoML (Automated Machine Learning) is a technology that helps automate complex steps in the process of building machine learning models. From data processing, algorithm selection, to parameter adjustment and result evaluation, all can be done by the system without too much manual intervention from engineers.
Not only does this technology save time, it also opens up AI to organizations without a strong technical team. Instead of weeks spent testing algorithms, it can now be done in hours or even minutes.
Google pioneered the AutoML platform in 2017, then names like Amazon and Microsoft also launched their own AutoML solutions, integrated into their cloud services.
It’s worth noting that AutoML doesn’t work in a cookie-cutter fashion. The system can adapt its learning strategy, change its neural network architecture, or experiment with different configurations until it finds the one that works best.
In that way, AI is starting to “learn how to learn” and is gradually no longer completely dependent on the programmer.
Irreplaceable people
While AutoML simplifies the creation of AI, it doesn’t eliminate the need for humans entirely. AI models are only truly useful when the input data is correct, the problem is well defined, and the results are contextualized, but they still require thought and understanding on the part of the user.
AutoML works best when users know what they need . For example, AI can help analyze medical images, but the final diagnosis and treatment decisions still rest with the doctor. In finance, AI can identify fraud trends, but analysts need to understand what that means in a real-world context.
Automation can reduce time and effort, but it cannot replace human experience, intuition, and responsibility. Instead, AutoML acts as a support arm, making the decision-making process faster and more data-driven.
Another benefit is the ability to intelligently optimize models . AutoML doesn’t just pick a “good” model, it tries multiple options, evaluates them, and then delivers the best model based on the data the user provides. The result is that the AI system’s performance is on par with the model built by an expert, and in many cases, it’s even better because AutoML doesn’t skip any steps.
Ultimately, AutoML represents a major step toward democratizing AI , taking it out of the lab and into the real world. Teachers, doctors, marketers, and store owners can all leverage AI to solve their problems.
Source: https://tuoitre.vn/cong-nghe-automl-ai-dang-tu-hoc-cach-lam-ai-20250630110417866.htm
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