It is easy to become weary of headlines that tell us the latest tech breakthrough will “change everything.” But Generative AI (GenAI) and AI-driven large language models (LLMs) are set to live up to the hype, creating a new form of intelligence that may even surpass the creation of the Personal Computer (PC) in terms of impact. Before GenAI, the skillsets of AI were impressive but narrow — recognizing objects in images, quantifying language in text or crunching numbers in massive data sets. But LLMs can do things we previously thought were uniquely human, like creating art, writing books and making music. The intelligence of these models includes emergent capabilities, unexpected new abilities that haven’t been programmed yet and certainly, AI is set to significantly reshape the global economy, bringing new opportunities — and new risks.
It’s time to start thinking bigger about how the intelligence of AI could transform businesses. The potential of AI is exciting, not only to enhance the productivity of teams, but to also enrich customer and employee experiences. When mundane tasks are automated, employees are free to spend more time in dialogue with customers and colleagues, asking new and better questions in addition to providing answers. They have the time and headspace to execute higher level cognitive tasks that contribute to solving more complex challenges.
Generative AI is important not only by itself but also because it makes us one step closer to the world where we can communicate with computers in natural language rather than in a programming language. With the help of generative AI, models become multimodal, which means they are able to process several modalities at a time, such as text and images, which expands their areas of application and makes them more versatile.
At present, uses of GenAI are seen in -
Content Generation - Automated content generation for blogs, articles, social media posts, and marketing copy with the use of Chatgpt.
Image Generation - DALL-E 2 produces highly detailed and imaginative visuals based on prompts.
Music Composition - Amper Music generates music tracks based on user inputs like mood, genre, and instruments.
Code Generation - Integrated into popular code editors like Visual Studio Code, GitHub Copilot uses OpenAI's Codex to help developers write code faster and reduce repetitive tasks.
Conclusion
The process of simplification and democratization of human-machine interaction also positively influences the quality of the models itself since more people, including experts, are involved in their training. That means that generative models are much more than just fun or crazy art that you can generate when you have nothing better to do. In fact, generative AI might be that next step in the evolution of AI that we have all been waiting for.
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