#073 Sunday Feature - How Generative AI Is Changing The Way We Work, Play And Learn
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AI BYTE # 1 📢: How Generative AI Is Changing The Way We Work, Play And Learn
⭐ AI is not just a buzzword or a sci-fi fantasy. It is a reality that is transforming every aspect of our lives, from entertainment to education, from health care to business.
And one of the most exciting and impactful areas of AI innovation is Generative AI, which can create new content and solutions from scratch, based on data and human input.
Generative AI is the ability of AI systems to generate novel and realistic outputs, such as images, text, audio, video, code, or even physical objects.
Unlike traditional AI, which analyzes and classifies existing data, Generative AI can produce new data that did not exist before. This opens up a whole new world of possibilities for human creativity and productivity.
For example, imagine being able to write an essay, a poem, a song, or a code snippet by simply describing what you want in natural language. Or being able to create a realistic and personalized avatar that can speak in your voice and mimic your expressions.
Or being able to design a new product, a logo, or a website by just sketching a rough idea. These are some of the things that Generative AI can do, or will soon be able to do, thanks to the advances in deep learning and natural language processing.
Gen AI is not only a powerful tool for creating content, but also for learning and discovering new knowledge. By generating multiple scenarios, hypotheses, or solutions, Gen AI can help us explore the unknown, test our assumptions, and find the optimal outcomes.
It can also help us learn from our own data, by summarizing, synthesizing, and explaining the key insights and patterns.
One of the key benefits of AI is that it can understand natural language, meaning that employees can use their own words to ask for the information they need, instead of relying on complex technical queries. This makes data retrieval faster and easier, as well as more accurate.
For example, Nvidia’s CEO Jensen Huang said that Gen AI, which can create new data from existing data, is the largest market expansion of software and hardware in decades. He cited the case of ChipNeMo, an AI model that can help engineers design chips faster by writing code and finding information for them.
AI can also help employees work with data that is not easily accessible, such as internal documents or presentations.
A pilot project by Intel and Boston Consulting Group showed that an AI model trained on BCG’s data could find a presentation that human workers could not locate after eight hours of searching, in just two seconds.
These examples show that AI can enhance employee productivity, creativity, and collaboration by using data more effectively.
Adoption of Gen AI in Research and Development
One of the most impressive examples of Generative AI is the Korea Superconducting Tokamak Advanced Research (KSTAR) device, also known as the Korean Artificial Sun, which set a new world record by sustaining a nuclear fusion reaction for 30 seconds at temperatures exceeding 100 million°C - nearly seven times hotter than the core of the sun.
This is a significant milestone for the field of nuclear fusion, as it represents both the necessary heat and stability required for viable fusion reactors. The KSTAR team used a modified Internal Transport Barrier (ITB) technique, which uses AI to control the plasma pressure and temperature, and to prevent instabilities that could disrupt the reaction.
Another remarkable example of Gen AI is Microsoft’s Copilot for Microsoft 365, a productivity AI assistant that uses large-language models to help users with various tasks, such as writing, summarizing, translating, or presenting.
The Copilot can generate high-quality content from natural language descriptions, or from existing data sources, such as emails, memos, or presentations. Microsoft claims that users of Copilot can complete tasks 29% faster than those not using the service.
Gen AI is not only a game-changer for professionals and researchers, but also for everyday users who want to express themselves, learn new skills, or have fun.
There are many Gen AI tools and platforms available online, such as Adobe’s Photoshop, Illustrator, and Premiere Pro, which use AI to enhance and simplify the image, video, and audio editing process.
There are also tools like Kapwing, Runway, Peech, Synthesia, Fliki, Visla, and Opus Clip, which allow users to create, edit, and enhance videos with AI, for various purposes, such as social media, marketing, education, or entertainment.
Entertainment Adoption
Gen AI is also being used at the cutting edge of innovation across the entertainment industry as well
Art and Music Generation: Gen AI has ushered in a new era of creativity and innovation, showcasing its potential across diverse industries. From generating art and music to powering applications in gaming, Generative AI has captured the imagination of businesses and researchers alike.
AI Applications: Generative AI applications such as ChatGPT, GitHub Copilot, Stable Diffusion, and others have captured the imagination of people around the world thanks to their broad utility. These applications can perform a range of routine tasks, such as the reorganization and classification of data.
Scalable Game Development: Generative AI can help accelerate game production across the board - code, art, dialogue, and more, enabling these teams to better serve their players at scale. It can help existing teams create better content at a faster pace, with improved collaboration, ideation, and personalization.
Preproduction and Planning: AI is already being used in preproduction stages, planning out game content, and industry executives expect that within a few years, it will play a larger role in production, developing characters, dialogue, and environments.
Story Generation and Nonplayable Characters (NPCs): Generative AI could enable limitless interactive stories personalized for each player.
Prototyping: Generative AI tools allow game developers to quickly and easily create new game assets, characters, and environments without spending hours manually designing and building them. As a result, prototyping can be greatly accelerated, enabling developers to test out new ideas and concepts much faster.
Personalized Experiences: Generative AI will also help make bigger, more immersive, and more personalized experiences a reality.
Challenges and Limitations
Generative AI is not without its challenges and limitations, however. Some jobs may become obsolete or less in demand as AI takes over some of the tasks that humans currently do.
For instance, call center workers may face competition from AI models that can automate customer service requests. Similarly, artists may lose some of their clients to AI tools that can generate images and videos.
If you are interested in learning more about generative AI, and how it can change the way we work and learn, subscribe to this Substack and stay tuned for more updates.
I share latest news, trends, research, and applications of Gen AI, as well as tips and tricks on how to use Gen AI tools and platforms effectively and responsibly.
I hope you will join us on this journey of discovery and innovation, and look forward to hearing your feedback and questions. Thank you for reading!
