Difference Between AI and Generative AI: 3 of The Biggest Difference
- June 10, 2024
A lot has changed since artificial intelligence came into the picture. People have changed the way they work and the way they understand work. Having said that, there is also a lot of fear surrounding the term. While people may have found comfort in AI Development, another popular term has come up: Generative AI. Now, what is the difference between AI and Generative AI?
Understanding Artificial Intelligence (AI)
Definition and Scope
AI, or artificial intelligence, was born from the vision to make machines smart. We wanted to make machines smart enough to take up some of our tasks with minimal human intervention. AI development eventually gave way to various levels of intelligence that can execute various degrees of tasks. The idea was never to replace humans but to improve what they do.
Types of AI development
- Narrow AI: This type is also known as weak AI. It can perform more straightforward tasks with multiple constraints.
- General AI: General AI, or strong AI, is the type that can understand, learn, and apply itself. Its output is close to what a human can create.
- Superintelligent AI: This type is a step ahead. The idea was to create a machine that could perform tasks at a higher level than humans.
Applications of AI
- Finance: Fraud detection, algorithmic trading, and customer service chatbots.
- Transportation: Autonomous vehicles and traffic management systems.
- Retail: Personalized shopping experiences and inventory management.
- Entertainment: Recommendation systems and content generation.
- Healthcare: Diagnostic systems, personalized medicine, and robotic surgery.
Read about our AI case studies that highlight the applications of AI. Click here to read.
Understanding Generative AI
Definition and Scope
Generative AI is a kind of AI that is being trained to generate more brilliant results than the average human. It can create new content based on prompts and help increase the speed of more complex tasks.
Applications of Generative AI
Generative AI is applied in various creative and functional domains:
- Art and Design: Creating new artworks, designs, and virtual environments.
- Music: Composing original music or aiding musicians in the creative process.
- Writing: Generating articles, stories, and other textual content.
- Gaming: Creating new characters, environments, and storylines.
- Healthcare: AI can help us generate synthetic training data for medicine and healthcare.
Key Difference Between AI and Generative AI
While Generative AI is a subset of AI, it has distinct characteristics that set it apart from the broader field.
Objective and Functionality
- AI: The main goal is to perform smaller or redundant tasks.
- Generative AI: Generative AI can create new data from thin air, helping humans finish complex tasks more quickly and efficiently.
Applications and Use Cases
- AI is widely used in practical applications requiring data analysis, prediction, and decision-making. Examples include autonomous vehicles, fraud detection systems, and virtual assistants.
- Generative AI: Predominantly used in creative fields and scenarios requiring new content generation. Examples include generating realistic images or videos, composing music, and writing articles.
Impact on Society
- AI: AI has had a vast and impressive impact on the society. The effect started with a sense of fear. People feared they would lose their jobs. Eventually, when used, AI proved that it wasn’t here to take up jobs but to increase employee efficiency. Now, we can see an impressive improvement in decision-making because of AI.
- Generative AI: Generative AI threatens the creative industries. It has made artists, musicians, and writers fear for the value of their work. There are also concerns regarding the authenticity of art. This is why most artists still avoid using AI in their work.
Ethical Considerations
The difference between AI and Generative AI is also clearly visible in the ethical considerations for the two:
AI Ethics
- Privacy: Since AI processes a lot of data daily, concerns around data privacy and security are natural.
- Job Displacement: One of the most popular controversies about the use of AI is whether it could remove a few jobs from the market.
Generative AI Ethics
- Misinformation and Deepfakes: One of the most significant controversies around Generative AI came from the deepfakes. Technology can create hyper-realistic content, which is an ability that certain people misuse. One of the core focuses in the field of Generative AI is stopping it from being used badly.
- Intellectual Property: Some people may even accidentally infringe other people’s intellectual property if their AI prompt returns with its use. This is also another primary concern.
Read more about the top 10 ethical considerations to take into account when working with. Click here.
Future Directions
The future highlights the difference between AI and Generative AI:
AI
- Advancements in General AI: The world is ready to see what more AI development & the other parallel fields can do.
- AI in Everyday Life: Artificial intelligence will slowly become a very important part of our everyday lives, enabling smaller tasks like making coffee.
Generative AI
- Enhanced Creativity Tools: We can make art & creativity-related tools with the help of Generative AI.
- Real-world Applications: Generative AI can also help us with complex fields like medicine and healthcare.
Conclusion
While most people use AI and Generative AI interchangeably, there is a vast difference between AI and Generative AI. One can analyze, and the other can create. One can execute, and the other can strategize. Together, they can make your day-to-day much more efficient and easy. Have you tried using any of the two in your business yet? If you need help, you must contact us to empower your business with AI development services.
