What is Generative AI?
Generative AI is a type of artificial intelligence technology that can produce various types of content including text, imagery, audio and synthetic data.
Is generative AI a new technology?
NO, it is not brand-new. Generative AI was introduced in the 1960s in chatbots. But it was not until 2014, with the introduction of generative adversarial networks, or GANs a type of machine learning algorithm that generative AI could create convincingly authentic images, videos and audio of real people.
How does generative AI work?
Generative AI starts with a prompt that could be in the form of a text, an image, a video, a design, musical notes, or any input that the AI system can process. Various AI algorithms then return new content in response to the prompt. Content can include essays, solutions to problems, or realistic fakes created from pictures or audio of a person.
What are the examples of Generative AI?
CahtGpt,Google Bard ,Dall-E
Where can Generative AI be used?
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Implementing chatbots for customer service and technical support.
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Deploying deep fakes for mimicking people or even specific individuals.
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Improving dubbing for movies and educational content in different languages.
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Writing email responses, dating profiles, resumes and term papers.
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Creating photorealistic art in a particular style.
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Improving product demonstration videos.
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Suggesting new drug compounds to test.
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Designing physical products and buildings.
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Optimizing new chip designs.
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Writing music in a specific style or tone.
Benefits of Generative AI
Automating the manual process of writing content.
Reducing the effort of responding to emails.
Improving the response to specific technical queries.
Creating realistic representations of people.
Summarizing complex information into a coherent narrative.
Simplifying the process of creating content in a particular style.
Limitations
It does not always identify the source of content.
It can be challenging to assess the bias of original sources.
Realistic-sounding content makes it harder to identify inaccurate information.
It can be difficult to understand how to tune for new circumstances.
Results can gloss over bias, prejudice and hatred.
How can companies utilize generative AI in future?
They can take in such content as images, longer text formats, emails, social media content, voice recordings, program code, and structured data. They can output new content, translations, answers to questions, sentiment analysis, summaries, and even videos. In the future, there is potential for generative AI to make an impact in health care and life sciences—to make diagnoses or find new cures for diseases.
Conclusion
Even Though AI has limitations buts it really has the potential to change industries . With the ability to generate new content with existing data. There is no doubt that it has the capacity to change the future of technology.