- Why AI image generation stops choosing the environment
- Why is our understanding of the environment so wrong?
- Structure of cloud AI and local AI
- Changes in practice and the market (structures created by differences in the environment)
- example：Differences in production flow depending on environment
- Advantages and disadvantages of cloud AI
- Advantages and disadvantages of local AI
- Differences in major services (understand by connecting to the environment)
- Role sharing between human production and AI environment
- summary：The environment is determined by the production design.
Why AI image generation stops choosing the environment
When trying to incorporate AI image generation into practice、Many people stop at ``What kind of environment do I need?''。
- Do I need a high-performance PC?
- Is cloud alone enough?
- Should I prepare a local environment?
If this judgment remains ambiguous、The implementation itself is not progressing。
The only important thing here is、Environmental issues are not “specs”、
How much of the production process do you control?The point is that it is a design problem.。
Why is our understanding of the environment so wrong?
Cloud or local、Eventually the image will be generated.。
Therefore、
- Looks like you can do the same thing with either
- Difficult to tell the difference
The state will be。
However, in practice it is clearly different.。
- Who is in charge of the generation process?
- How much control can you have?
- Can you reproduce the same result?
This difference、This directly affects the stability and scale of production.。
Structure of cloud AI and local AI
First, organize the structure。
Cloud AI：Mechanism that can be completed with external processing
Typical cloud type：
- Midjourney
- DALL-E
- Adobe Firefly
- Gemini
- ChatGPT
- Grok et al.
Cloud AI is、All image generation processing is done on the server side。
The user、
- Enter text or image
- receive the generated results
Only。
In other words、
The generation mechanism is provided as a black box.です。
local AI：Mechanism to control within the PC
represent：
- Stable Diffusion
Local AI is、
- AI model
- Generation settings
- processing process
Handle everything on your PC。
This means、
An environment where generation is treated as a “process” rather than a “result”です。
Changes in practice and the market (structures created by differences in the environment)
Visual production、1The structure has changed from creating points.。
- submit multiple ideas
- Verify and choose
- make only what you need
In this flow、
- Cloud = verification
- local = production
There has been a division of。
The difference in environment is、The production flow will be different.。
example：Differences in production flow depending on environment
For example, creating product visuals.。
When proceeding only with the cloud
- Generate multiple patterns
- choose a good one
The work has been put in the adult category because of the photo showing the bust of the cut.、
- speed is fast
- Initial quality is high
But、
- Unable to reproduce the same composition
- Difficult to continue operation
There is a restriction that。
When incorporating local
- Fixed conditions
- Generated with the same composition
The work has been put in the adult category because of the photo showing the bust of the cut.、
- reproducible
- Mass production possible
instead、
- Environment construction required
- Requires understanding of settings
becomes。
Advantages and disadvantages of cloud AI
merit
No environmental dependence
- Regardless of PC specs
- GPU does not need
→ Ready to implement
High initial quality
- Consistent quality with no settings required
→ Strong in rough production
Easy to increase the number of trials
- Instant generation
→ Suitable for verification process
Disadvantages
narrow control range
- Difficult to fix composition
- Unable to reproduce conditions
I can't see the internal specifications.
- I don't know why that result
There are restrictions
- Number of times limit
- Not customizable
Advantages and disadvantages of local AI
merit
Wide control range
- Conditions can be set in detail
→ Can be incorporated into the production process
reproducible
- Can be generated under the same conditions
→ Suitable for continuous production
scalable
- Models and settings can be changed
Disadvantages
Environment construction required
- Setup required
hardware dependent
- Influenced by GPU/memory performance
Highly difficult to operate
- Requires understanding of settings
Differences in major services (understand by connecting to the environment)
Roles are different even in cloud type。
Midjourney
- Strong against atmosphere generation
→ Directional design
DALL-E
- Easy to follow instructions
→ Composition verification
Adobe Firefly
- Production tool collaboration
→ Actual production connection
Stable Diffusion
- Control/Mass production
→ Production project
Role sharing between human production and AI environment
Choosing the environment is just a matter of division of roles.。
cloud
- rough generation
- Tone confirmation
- Initial verification
local
- Conditions are fixed
- Reproduction
- Continued production
people
- concept design
- brand judgment
- final quality
summary：The environment is determined by the production design.
The environment for AI image generation is、
- specs
- tool
It is not decided by。
There are three criteria。
- Do you need control?
- Do you need reproducibility?
- Should it be incorporated into the production process?
Considering these three points、
- Is the cloud enough?
- Do you need local?
becomes clear。
Environment selection、
The design itself of the production processです。
▶︎ [What is AI image generation? Understand the mechanism and main services]
▶︎ [AI image generation depends on PC performance | Differences between Mac and Windows environments]
▶︎ [PC specs required for AI image generation | Memory, GPU, storage]
