Learning Artificial Intelligence - Part 7 (Why Generative AI is popular?)

There are several reasons why generative AI has become increasingly popular:

Increased computing power: 

With advancements in technology, there has been a significant increase in available computational resources. This has allowed researchers to develop and train larger and more complex models, which makes them more capable of generating realistic and detailed output.

Improved algorithms: 

Machine learning algorithms used in generative AI have improved over time, allowing them to learn patterns in data faster and produce higher quality results. Recent breakthroughs in deep learning techniques, particularly in areas like transfer learning, have contributed significantly to the growth of generative AI.

Multi-modal generation: 

One of the main challenges in generative modeling is creating output that spans multiple modalities - i.e., audio, video, text, images, etc. However, recent advances in multi-modality have enabled generative AI to create highly engaging cross-platform content.

Wide range of Applications: 

Finally, generative AI has wide application potential ranging from entertainment industry where movie scenes, songs or characters can be generated and fine tuned by humans or other generative algorithms. To scientific research, where the AI may propose theories/hypothesis, or accelerate processes through automation. Its impact may spread into medicine, finance, business and many more fields.

Accessibility : 

As open source projects matured and large companies started offering cloud services to host these models on , access to powerful generative ai became possible via user friendly interface without requiring expensive hardware and technical expertise.

Ethics & Regulation : 

Finally, increased attention on the ethical implications of AI technologies have driven interest in developing and deploying AI systems in a responsible manner. Researchers and policymakers alike want to ensure that the benefits of AI technologies are equitably distributed and that the risks associated with these systems are minimized.