Master KLING AI 1.6 with a 4000-Line Guide and Master Video Prompt Creation GPT

If you know me, you probably know that I created a GPT to help people write Kling Video prompts. It is now used by quite a few people and is called “Top1️🏆Master Video Prompt Creation KLING AI 1.6”. You can easily find it on ChatGPT or through Google using the related keywords “Prompt Creation KLING AI 1.6”

In this article, I will walk you through every step you need, from A to Z. Of course, since I have shared my GPT for free, please consider making a donation to support this guide.

Update: What’s New in Version 1.6?

• Improved prompt adherence, with more consistent and flexible results
• Supports Standard Mode & Professional Mode, achieving an overall improvement of 195% over the KLING 1.5 Model

1. Improved prompt adherence: better responses to prompts involving motion, sequences of movements, camera movements, etc., along with an improved ability to generate elements not present in the Start Frame.

2. Improved motion dynamics: more plausible movements and more realistic facial expressions.

3. Improved image quality: greater stylistic consistency, better color rendering and aesthetics, and more realistic lighting, shadows, and details.

4. Credit costs remain the same as version 1.5

• 1.6 Model - Professional Mode (1080p): Video generation remains at 35 Credits/5s, 70 Credits/10s.
• Standard Mode (720p): Video generation remains at 20 Credits/5s, 40 Credits/10s.

Image-to-video features such as Start/End Frames, Motion Brush, Camera Movement, etc. are not yet available but will be added soon!

Introducing Kling

Kling AI is a tool powered by advanced artificial intelligence, developed by Chinese technology company Kuaishou Technology. It is designed to generate videos and images automatically and quickly from text descriptions.

Since Kling AI was first introduced this past June, the videos produced by this AI tool have received high praise from the online community for both their content and visual quality.

I chose to introduce Kling to everyone because of its impressive ability to restore old photographs and turn them into vivid videos. But the more I explore this tool, the more I find it truly worth every penny I spend.

I sincerely hope you discover similar value as you read and work through this entire guide!

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How to Register for a Kling AI Account

For the best experience, you should generally use Kling AI on a computer. However, you can also use Kling AI on your phone. Here is how to register for a Kling AI account.

Registering for a Kling AI Account on a Computer

Step 1: Visit klingai.com > Click Sign in for free credits or Sign in to register.

Step 2: Select Sign up for free > Enter your Gmail information > Verify your account using the code sent to your email address.

You will receive an OTP at the email address you registered with. Open your email and enter this OTP as instructed on the screen to complete registration.

Note:
Many people get stuck at the step where you drag the puzzle piece, or keep dragging without it moving. This happens because they click the puzzle piece itself, when they should actually click the orange-yellow button.

After registering, you will receive some free credits every day to use the software. The current allowance is 66 credits - 66 usage points / 24h, though this may change in the future.

With a free account, users can only create videos up to 5 seconds long, and the generated videos will carry a “Kling AI” watermark. If you want to create longer videos without the “Kling AI” watermark, you will need to pay for a professional account.

Registering for a Kling AI Account on a Phone

You can simply open your phone’s browser, visit klingai.com, and follow the same steps as on a computer. However, because phone screens are quite small and awkward to navigate, my honest advice is to use a computer to save time.

Understanding Some Elements of the Kling Interface

Kling currently has two main features: AI Image Generation and AI Video Generation. In addition, the Video Editor feature is under development and will be released soon.

I currently subscribe to Kling’s Pro plan, and this is my remaining monthly credit balance. You can check the tool’s pricing by clicking here:

Kling’s Basic Features

Text to Image - Generate Images from Text Descriptions

When you use the AI Image feature, Kling’s large model lets you generate images from text descriptions.

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Guide to generating images from text descriptions

For image generation from descriptions, Kling does a very good job of maintaining similarity between images. As you can see in this picture, the 4 rabbits look very similar. This makes it extremely easy to tell a story centered on a consistent character. This seems to be something Kling has deliberately built in, rather than the usual Text-To-Image feature we are familiar with.

To support this observation, I tried generating images of a Vietnamese model. You can see the results right below.

Still a Vietnamese model, but this time I used a different Prompt:

Beautiful Vietnamese woman, white ao dai, posing for a photo shot

However much assistance the tool provides, the ultimate goal for both you and me is still to master it. So experimenting and finding a formula remains something we need to do. Based on my experience, here is a formula for Kling Prompts that you can use as a reference:

💡

Prompt = Subject + Action + Setting + Style

1. Subject: The subject is the main focus of the video and a key representation of its theme. It could be a person, animal, plant, object, etc. When describing the subject, try to include details such as shape, build, fur color, clothing, accessories…
2. Action: Describe the action the subject is performing.
3. Setting: Describe the setting in which the subject appears.
4. Style: Describe the image’s style.

An example of “style”: If you are depicting a rabbit reading a book and want it to sit like a person, you should mention “3D character, cartoon style”. After all, rabbits only sit and read books like people in animated films. Conversely, if you leave out these style keywords, you will most likely get a rabbit jumping onto a book.

Also, when generating AI images, there will inevitably be times when you do not know how to describe something so that the AI generates it correctly. In these situations, Kling lets you upload a reference image so the AI model can use its style as a reference for the output image.

Notes:

• As Reference Strength decreases (toward - - -), the resulting image will have a style that differs more from the reference image and will be influenced more by your prompt. In practice, the further you lower this value, the more plastic-looking the resulting image becomes, losing realism and resembling a 3D image.
• As Reference Strength increases (toward +++), the resulting image’s style will be closer to the reference image and less influenced by the prompt you entered. In practice, however, the higher you raise this value, the more likely the resulting image is to differ from the reference, so you should keep Reference Strength at 0 or raise it slightly.
• If you want to reproduce the reference image as closely as possible, keep Reference Strength within this range. Kling will do the best job of copying clothing, fur color, hair color, skin tone, accessories… Do not set it too high or too low.

• Kling’s Reference Image feature only uses a text description of the input image as its reference. It does not work like Control-Net in Stable Diffusion**.** When you give Kling an image, it uses an AI algorithm to produce a text description of that image. This text description is then combined with the description you entered (also called the prompt) to generate the final result. It works similarly to Midjourney’s Style Reference and Image Reference features, as illustrated below:

For people, using a reference image in which the face is unclear will most likely produce a distorted face. Here is an example:

• The AI model’s ability to copy faces is not particularly impressive—just acceptable. The face in the resulting image does not resemble the original, but the realism and consistency are truly remarkable:

photoshot of Vietnamese woman, beautiful face, high details, 8k

Beautiful Vietnamese woman, big breast, blue jeans and white t-shirt, posing for a photo shot

• Kling’s text-to-image feature does not support Negative Prompts, which describe things that must not appear in the resulting image. This can impose certain limitations when generating images. Here is a small tip: “If Negative Prompts are not available, try describing something else to override the unwanted element.”

Example: I was generating an image of an older male model with the simple description “Vietnamese old man, posing for a photo shot” - “An elderly man posing for a photo.” Clearly, neither the reference image nor the description included a hat, yet the result had one on his head.

So how do you remove the hat when you cannot use a Negative Prompt?

Use something else to override it. I changed the prompt and added a description of the hairstyle. And boom =))) here is the result.

Text to Video - Generate Videos from Text Descriptions

When you enter a text passage, Kling’s large model generates a 5- or 10-second video, turning that text into visuals.

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Guide to generating videos from text descriptions

Kling currently has two video generation modes: “Standard Mode” for faster video generation and “Professional Mode” for better visuals.

Kling also supports three different video aspect ratios: 16:9, 9:16, and 1:1, to suit everyone’s creative needs.

A “Prompt” (a text instruction) is how you communicate with this model, and it determines the content of the video Kling generates. That is why understanding and learning to write effective Prompts is important for anyone who wants to create videos with AI.

Here is an easy-to-understand Prompt formula for your reference:

💡

Prompt = Main subject (Subject description)
+ Subject movement
+ Setting (Scene description)
+ Cinematography + Lighting + Atmosphere.

1. Main subject: This is the main focus of the video, which could be a person, animal, plant, object, etc.
   1. Subject description: You can describe the subject’s appearance and posture in detail using short sentences. Examples include: Athletic performance, Hairstyle and color, Clothing and accessories, Facial features, Body posture, etc.
2. Subject movement: Describe the subject’s state of motion, including both stillness and movement. This should be clear and suitable for a 5-second video.
3. Setting: This is the environment in which the subject appears, including the foreground, background, and other elements.
   1. Scene description: Briefly describe the surroundings of the subject, using a few short sentences to outline the setting without overwhelming the viewer. It should fit what can be shown in a 5-second video. Examples include: Indoor scenes, Outdoor scenes, Nature scenes.
4. Cinematography: This concerns the use of camera lenses, along with transitions and editing between shots, to convey a story or message and create specific visual and emotional effects. Techniques include: Ultra-wide-angle lenses, Bokeh (background blur), Close-ups, Telephoto lenses, Low angles, High angles, Overhead shots, Depth of field, etc. (Note: This should be distinguished from camera movement control).
5. Lighting: Light and shadow are important elements that give photographic work its soul. Using light and shadow can give images more depth and expressive power. Techniques include: Ambient light, Morning light, Sunset light, The interplay of light and shadow, The Tyndall effect, Artificial lighting.
6. Atmosphere: Describing the intended atmosphere of a video can involve various elements that establish its mood and tone.

The most basic elements in this formula are the main subject, movement, and setting, which form the most important and easy-to-understand parts of a video scene description. To describe the subject and setting in greater detail, list short descriptive statements while keeping all the elements you want in the Prompt intact. “Kling” will then use our descriptions to generate a video that matches our vision.

Example:
With the sentence “A giant panda is reading a book in a cafe”.

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A giant panda is reading a book in a cafe

We can enrich the subject and setting details by changing it to: “A giant panda, wearing black-rimmed glasses, is reading a book in a cafe, with the book on the table and a steaming cup of coffee beside it, near the cafe’s window”. This creates a more specific and controllable visual for your video.

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A giant panda, wearing black-rimmed glasses, is reading a book in a cafe, with a book on the table and a steaming cup of coffee next to it, near the cafe’s window

If you want to add cinematic elements and lighting, you can try the description “Medium shot, with a blurred background and cinematic lighting, a giant panda, wearing black-rimmed glasses, is reading a book in a cafe. The book is on the table, beside a steaming cup of coffee, near the cafe window, with a film-quality color palette”. Using this description will further improve the visual texture of the generated video, potentially producing results beyond your expectations.

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Medium shot, with blurred background and cinematic lighting, a giant panda, wearing black-rimmed glasses, reads a book in a cafe. The book is on the table, next to a steaming cup of coffee, near the shop window, with a color palette that meets movie standards.

Ultimately, the purpose of the formula above is to help you better describe the video scenes you are imagining. Here are some examples I created. Let’s take a look!!

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A circling camera shot captures a handsome young man dressed in ancient clothing, wearing white, seated by the pond with his eyes closed, meditating.

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A woman is in a tense standoff with an adversary in a narrow, rain-soaked alley. The scene is drenched in neon lights and deep shadows, with a cyberpunk atmosphere reminiscent of Blade Runner.

Tips:

• Use simple words and sentence structures, avoiding overly complicated language.
• Keep the visual content as simple as possible so it can unfold within 5 to 10 seconds.
• If you want to create videos featuring faces characteristic of a particular country:
  • Using terms such as “Eastern style”, “Chinese”, and “Asian” will readily produce Chinese styles and images of Chinese people.
  • The AI model seems to struggle with terms such as “Viet Nam”, “Vietnamese”, “Ao Dai”… The resulting faces often look Chinese or Indian instead. This only happens with AI video generation; for images, the AI responds quite well.
  • A similar issue occurs with Korean people—for example, with the word “Korean”—but the resulting video seems to feature people who look more Chinese than Korean.

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Korean young woman wearing fashion clothes, smiling, happy eyes

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Korean young woman wearing fashion clothes, smiling, happy eyes

• Current AI video models do not understand quantities, and Kling is no exception. This makes it difficult to maintain consistent counts, such as “10 puppies on the beach” in the video below.
• For split-screen scenes, you can use a Prompt such as: “4 camera angles representing spring, summer, autumn, and winter”. But as mentioned, Kling does not always understand quantities, so there is always a chance it will generate only 1 or 2 camera angles rather than 4.
• At this stage, generating complex physical movements such as a bouncing ball or the trajectory of an object thrown from a great height may produce errors. I will discuss this later.

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10 puppies on the beach

In the example of 10 puppies on the beach, the AI model clearly cannot control the quantity, as the number of puppies keeps changing.

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4 camera angles, splitted horizontal, 4 screens representing spring, summer, autumn, and winter.

This is an example of a split-screen scene. Possible keywords include “4 camera angles”, “split screen”, “4 screens”…

Image to Video - Generate Videos from Still Images

When you input an image, the “Kling” large model generates a 5- or 10-second video, turning that image into an animated scene. If you add a text description, the “Kling” model can generate a video sequence that combines the story in the text with the image.

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Guide to generating videos from still images

The tool currently supports two image-to-video generation modes:

• “Standard Mode” - “Standard Mode” for faster video generation.
• “Professional Mode” - “Professional Mode” for better visual quality.

It also supports three aspect ratios: 16:9, 9:16, and 1:1, to meet a variety of video creation requirements. However, one drawback is that you cannot control camera movement.

Image-to-video conversion is currently the most widely used feature, mainly because it offers greater control over the video generation process. Users can turn pre-generated images into animated videos, significantly reducing professional video production costs and barriers to entry.

Kling truly gives everyone a new tool to unleash their creativity. Trends such as “bringing old photos back to life”, “returning to your youth”, “children hugging their parents, grandchildren hugging their grandparents”, “mushrooms turning into penguins”… show that “Kling” is a wonderful creative tool. It offers users endless possibilities for turning what they imagine into reality. It really is magical.

For image-to-video generation, controlling the movement of subjects in the image is the core consideration. Here is a Kling Prompt formula for your reference:

💡

Prompt = Subject + Movement + Setting

1. Subject: The subject is the main focus of the video and a key representation of its theme. It could be a person, animal, plant, object, etc.
2. Movement: Describe the subject’s state of motion.
3. Setting: Describe the setting in which the subject appears.

The most basic elements in this formula are subject and movement. Unlike text-to-video generation, which requires a scene description, image-to-video generation already has the scene provided in the image. You therefore only need to describe the subjects in the image and their intended movements. If there are several subjects with different movements, list them in order. “Kling” will then use our descriptions to generate a video that matches the desired result.

If you want Mona Lisa in the painting to put on sunglasses, entering only “put on sunglasses” may make it difficult for the model to understand the instruction, and it may generate a video based on its own interpretation. When “Kling” recognizes that it is a painting, it will most likely generate a video with a camera movement effect like a shot in an art exhibition. This is also why the AI model tends to produce static videos (with little movement) in this situation.

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Put on sunglasses

As illustrated here, when we describe only the action, Kling produces a still image or a video without the desired movement.

We therefore need to describe “subject + movement” to help the model understand the instruction, for example, “Mona Lisa puts on sunglasses with her hand”. Or, for multiple subjects, “Mona Lisa puts on sunglasses with her hand, and a ray of light appears in the background”. This makes it easier for the model to produce accurate results.

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Mona Lisa puts on sunglasses with her hand, and a ray of light appears in the background

As mentioned earlier, the purpose of this formula is to help you describe the video scenes you imagine more effectively. Here are some outstanding results shared by the community. Let’s take a look!

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The lake surface is sparkling, clouds are moving in the sky, and the mountain peaks are gradually exposed.

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Beautiful Chinese model filming a commercial, smiling, hair blowing in the wind.

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Dog swimming, water ripples spreading.

Tips!

1. Use simple words and sentence structures, avoiding overly complicated language. For example, if you want two people to hug, simply describe it as “Two people hugging each other”.
2. Movements should follow the laws of physics, and it is best to describe movements that could plausibly occur within the image.
3. A description that differs too much from the image may cause a cut or scene transition.
4. At this stage, generating complex physical movements such as a bouncing ball or the trajectory of an object thrown from a great height is difficult.

Extends with Prompt - Extend Videos with Prompts

AI-generated videos can be extended by 4-5 seconds, with multiple continuations allowing a total duration of up to 3 minutes. You can continue a video by making slight adjustments to the prompt instructions.

This is the original video I created in Kling, which I will use as an example to make things easier to understand. Be sure to watch it first so you can follow what is happening.

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The “Extend with Prompts” feature is in the tab at the bottom left after you generate a video with Kling. It offers two modes: “Auto Extend” and “Customized Extend”.

“Auto-Extend” means you do not need to enter another prompt; the AI model automatically continues the video based on its interpretation of the content—in other words, its own prediction.

In this Auto Extend example, the AI predicts what might happen in the next part of the video without needing a description from you:

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In contrast, “Customized Extend” lets users control how the video continues by entering a text description. In this mode, the prompt should be “related to the original video”, clearly describe what happens, and identify the continuing “subject and movement” to ensure that the extended video remains continuous and does not disrupt the narrative.

Here is an example of “Customized Extend”. In this case, you need to enter a description of what you want in the next video segment.

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To help you do this well, I suggest the following formula:

💡

Prompt = Subject + Movement

1. Subject: This is the subject you want to animate in the uploaded image. Choosing one main subject is more effective for getting a better AI response to your text.
2. Movement: Describe the subject’s state of motion.

Here are a few more examples from my experiments. This is the original video.

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If I ask the AI model to make the next segment show “the young woman standing up” - “The young woman standing up”, Kling will most likely not respond correctly to my description. This is because the description differs too much from what is happening in the video—or, more precisely, from the facial expression.

This result demonstrates that:

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Now, if we change it to describe only changes in the face, such as “the young woman purses her lips” - “young woman puckers her lips”, the AI responds very well.

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Tips!

1. The Extend feature can only be used with videos you have generated in Kling.
2. When using “Customize Extend”, the prompt needs to match the main subject of the original video, especially its final frame. Unrelated text may cause cuts or scene transitions, or the model may fail to respond to the prompt’s description.
3. Extending videos involves an element of chance: the result may be good, bad, or not quite what you wanted, and you may need several attempts to produce a video that meets your expectations. So if you have limited credits but still want to create a long video with consistent characters or scenes throughout, you should avoid this feature and use the advanced Start and End Frames feature instead.

Kling’s Advanced Features

Standard Mode & Professional Mode

• Standard Mode: A faster video generation mode with lower processing costs, focused on High Performance. It lets users quickly test the model’s effectiveness and bring their creative ideas to life.
• Professional Quality: A mode that generates videos with more detail, up to 10 seconds long, while consuming more credits. In this mode, Kling focuses on High Quality, which costs more and runs considerably slower. In return, it can generate high-quality videos that meet creators’ needs for more advanced work.

Standard Mode and Professional Mode each have the following advantages. You can choose the appropriate mode based on your circumstances:

• Standard Mode: Cost-effective video generation. It performs very well with portraits, animals, and scenes involving substantial movement. Generated animals look friendlier, and the visuals have soft, pleasant colors. Standard Mode has been widely welcomed since Kling’s market launch.
• Professional Mode: This video generation mode is called Professional Mode. It performs well when generating videos featuring portraits, animals, architecture, landscapes… with more detail and more complex compositions and colors. It is currently the most widely used mode for complex video production or videos that require a more cinematic feel.

In the first example, the same prompt, “A dog playing soccer in green garden” - “A dog playing soccer in a green garden”, produced noticeably different results.

Using Standard Mode: ⭐⭐⭐⭐

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You can see that the dog moves naturally, and the video’s colors are soft and pleasant. However, the level of detail is low, and there are errors involving the ball.

Using Professional Mode: ⭐⭐⭐⭐⭐

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The dog in the video is more detailed, including its face, fur color, legs, and tail. The setting is more richly imagined, and camera movement is more stable. However, there are still errors involving the ball.

---

Here is another example, using the description “A medieval sailing ship is navigating the sea on a foggy night, with the bright moonlight illuminating the scene” - which translates as “A medieval sailing ship is moving across the sea on a foggy night, with bright moonlight illuminating the scene.”

Using Standard Mode: ⭐⭐⭐⭐

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Movement in the scene looks natural, although the details are not particularly striking, and the video’s colors are soft.

Using Professional Mode: ⭐⭐⭐⭐⭐

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The scene is rich in detail, the sails follow the physical laws of motion, giving it a cinematic quality, and camera movement is more stable.

Camera Movement - Camera Motion

To accommodate a wider range of video creation needs and help the AI model respond better to creators’ camera controls, Kling’s development team added the Camera Movement feature.

This feature lets us control camera movement within the video frame using precise instructions and choose the degree of movement by adjusting the movement parameters. Currently, the camera movement control feature supports 06 basic movements, including:

• Horizontal: Move horizontally.
• Vertical: Move vertically.
• Zoom: Move forward and backward, and zoom in and out.
• Pan: Rotate horizontally around a fixed axis.
• Tilt: Rotate vertically around a fixed axis.
• Roll: Rotate around a fixed axis.
• Master Shots - Move Left and Zoom In: Move left and zoom in.
• Master Shots - Move Right and Zoom In: Move right and zoom in.
• Master Shots - Move Forward and Zoom Up: Move forward and zoom up.
• Master Shots - Move Down and Zoom Out: Move down and zoom out.

Here are some camera movement examples for the Prompt: “A giant panda is playing a guitar beside a lake”.

Start and End Frames - Create a Moving Video Between 2 Images

The Start and End Frames feature lets you upload two images, which the model uses as the starting and ending frames to generate a transition video. The first image you upload, on the left, becomes the video’s first frame. The next image you upload, on the right, becomes the resulting video’s final frame.

You can use this feature by clicking the ‘Add End Frame’ option in the upper-right corner of the ‘Image to Video’ feature.

Providing the first and last images as inputs gives you more detailed control over the resulting video, helping achieve the desired animated transition.

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The resulting video using the 2 images above

Tips!

• Choose two similar images with the same subject. The contents of the first and last frames should be as similar as possible for a smoother transition within 5 seconds. Large differences may trigger scene transitions or changes in camera shots.
• Many creators generate similar images and then use the start and end frame feature to create videos. You can also use Kling’s AI Image feature to generate similar images. For example:

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• To minimize errors when generating a video from 2 start and end images, drag the Reference Strength slider all the way to the right. This limits the AI model’s tendency to invent unnecessary elements, keeps the resulting video closer to what is already in the images, and reduces the risk of errors.

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Tips for Creating Long Videos with Consistent Characters in Kling AI

There are currently 3 ways to create long videos with Kling AI:

Method 1: Use Extend Video - extend the video. There is nothing special about this approach, but it is not very effective. The results are highly likely to differ from your expectations, requiring repeated attempts and potentially consuming many credits.

Method 2: Use Text to Video - turn text descriptions into videos. With this approach, you need to keep the other components of the prompt fixed (characters, setting, colors…) and change only the main character’s actions. This increases the chances of generating videos with consistent characters, settings, colors… Once you have several short videos, you can use CapCut or ChatGPT to join them together. However, this approach is also not very effective because the results are highly likely to differ from your expectations and may consume many credits.

Method 3: Use Image to Video and enable Add End Frame - also known as adding an ending frame. With this approach, you need to use tools such as Midjourney, ChatGPT, or others to generate images with consistent characters and settings.

Once you have a sequence of images that tells a story like this.

Pair them into consecutive start and end images, then use them as inputs for Image to Video with Add End Frame enabled

Video 1: Start Frame is image 1 + End Frame is image 2 + Description (character + action, setting)

Video 2: Start Frame is image 2 + End Frame is image 3 + Description (character + action, setting)

Video 3: Start Frame is image 3 + End Frame is image 4 + Description (character + action, setting)

…

When you join these consecutive videos together in the correct order, you will get a long video just as you intended.

Troubleshooting Common Kling Issues

Not All Images Appear at the Same Time During Image Generation

This is not an error. Each image is generated in a separate processing thread, and some results may arrive a little later.

Some Generated Images Do Not Appear

Kling applies certain standards to generated images. This means that if an AI-generated image contains revealing, offensive, political, or similar elements, it will not be displayed.

Video Generation Stuck at 99%

This only happens when you are using the free version. Try upgrading to the lowest paid plan and see how it works.

Unable to Upload an Image

Your image may contain content that Kling’s AI identifies as prohibited: political content or overly revealing images. Try again with a different image.

“Your Image Must Be JPG or PNG” Error When Uploading

This happens because your image is in a format that the AI does not yet support, such as a file with a webp extension. Use an online tool to convert it to jpg or png, then upload the converted image to Kling.

Final Thoughts

Kling is a new AI tool with great potential and the capacity to develop rapidly in the near future. Its novelty brings not only challenges but also excellent opportunities to learn and apply it to your work. By seizing this opportunity and using Kling effectively, you can improve your personal productivity and get ahead of your competitors. Stay open to innovation and make the most of this advanced AI technology to set yourself apart in your career.

I wish you every success and continued progress on the road ahead! And remember to come back, as I will continue sharing new knowledge about Kling with you in the future.

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Disclosure: This article may contain product/course information or affiliate links. Review criteria & limitations of liability: review & disclosure policy. Author profile: Phạm Xuân Hiếu.

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