AI has become an integral part of marketing for modern smartphones and TVs. Manufacturers advertise AI-powered processors, AI-powered cameras, AI-powered image processing, AI-powered audio, and AI-powered virtual assistants. However, the term “AI” alone doesn’t always give a clear idea of what technology is actually being used.
Some features do indeed use machine learning or neural networks, but such features are relatively few. Others are based on traditional algorithms that have been around for many years. In many cases, both approaches are used together.
The best way to understand the difference is to look at specific features.
AI in smartphones
Smartphones themselves hardly use machine learning at all; it’s more important to understand that a smartphone interacts with a data center that analyzes incoming information and provides recommendations. Specifically, AI is used in photography, speech recognition, and certain image processing tasks.
Camera Image Processing: A modern smartphone does much more than simply capture an image from the camera sensor. The phone can combine multiple frames, reduce noise, enhance HDR, recognize faces and objects, and adjust colors and exposure.
Some of these operations use traditional image processing algorithms. Others may employ machine learning models trained to recognize patterns; for example, when photographing a starry sky, AI can remove glare and overexposure to improve the image.
Speech Recognition: Speech recognition is another area where AI is widely used. For example, searches used to be based on specific words, but now AI is used to interpret the full meaning of a query. One drawback is incorrect interpretation, since AI cannot think.
Face Recognition: Modern face recognition systems can also use machine learning models. Instead of simply comparing the pixels of two photos, the system can extract distinctive facial features and compare them with previously stored biometric information. However, not every biometric system should automatically be classified as AI. The technology depends on the specific device.
Recommendations: Smartphones can recommend apps, content, or settings based on usage history. Such systems can range from simple rules to more complex machine learning models.
This is an important distinction, as automatic personalization does not necessarily mean the use of AI.
AI in TVs
TV manufacturers frequently use AI terminology when describing image and sound processing, especially in recent years, when they began promoting televisions not simply as devices for watching TV shows, but as devices capable of interacting with people. Exactly how this interaction works is not always clear, but this is how it is presented in advertising.
Video processing is one of the clearest examples of a feature that is often advertised as AI even though it does not actually require AI. Resolution upscaling is performed by algorithms built into the TV processor and based on mathematical calculations. If AI were actually used to process every frame, consider the amount of processing required for around 200,000 frames in a standard-length movie. A TV simply does not have the computing power required for such processing.
Image processing includes sharpening, color adjustment, contrast processing, and other forms of enhancement applied to the incoming video signal. Some of these functions may use machine-learning models, while others can be implemented entirely through traditional algorithms. In most cases, however, these are standard programs that have been used in consumer electronics for more than 20 years.
For example, a TV can automatically adjust brightness using a light sensor and predefined rules. No AI is needed for this process. The same applies to many automatic picture settings.
Audio processing allows a TV to improve dialogue clarity, control volume, or change the sound profile depending on the type of content. These functions can be implemented using traditional digital signal processing. Some newer systems may also use machine-learning models, but the term “AI Sound” alone does not explain how the feature actually works.
Content recommendations are different. Smart TVs use viewing history and other information to recommend shows and movies. AI can be used for this purpose, particularly when the system analyzes viewing patterns and predicts which content a user may prefer.
Speech recognition is another area where AI is actually used. Older voice-control systems often required specific commands. Today, modern systems can understand more general requests. For example, instead of saying “Switch to channel 5,” you can say “I want to watch Channel 5.” The TV can send the request to a cloud server, where the system analyzes the speech, determines the user’s intent, and converts the request into a specific command.
This illustrates an important distinction. A television can contain many conventional programs that perform tasks using predefined algorithms, while some newer functions, such as speech recognition and certain recommendation systems, can use AI technologies. The fact that a manufacturer places the word “AI” on a feature does not mean that the entire function is based on AI.
AI or ordinary automation?
The distinction is important because many automated functions do not require AI.
| Function | AI or machine learning can be used | Conventional algorithms can be used |
|---|---|---|
| Image upscaling | No | Yes |
| Noise reduction | No | Yes |
| Face recognition | Yes | Yes |
| Speech recognition | Yes | Yes |
| Image recognition | Yes | Yes |
| Brightness adjustment | Usually not required | Yes |
| Automatic picture settings | Usually not required | Yes |
| Basic sound adjustment | Usually not required | Yes |
| Content recommendations | Yes | Yes |
This is why the AI label should not be taken as a complete technical description.
What is an AI Processor?
An AI processor is not a separate “intelligence” inside a TV or smartphone. It is simply hardware designed to accelerate the calculations used by machine-learning systems.
In modern devices, different parts of the processor can perform different tasks. One part handles the operations required to keep the device running, while another performs the calculations needed for data analysis and other computational tasks.
Therefore, even if a device has an AI processor, this does not mean that it contains some separate form of intelligence. It means that the processor is designed to perform certain calculations efficiently, including calculations associated with AI.
What should buyers look for?
The term AI should not be the main reason for choosing a smartphone or TV. Instead, focus on the specific features. If a TV is equipped with an AI processor, check which features actually use it. If a smartphone has an AI-powered camera, pay attention to the specific improvements it provides.
And if an advertisement mentions AI-powered sound or AI-powered picture, check whether the manufacturer explains exactly what the system analyzes and what it changes.
