RoadMap to GenerativeAI: 2023
In 2022, the global generative AI market was valued at $1.2 billion, and it is expected to reach $34.6 billion by 2028.
Generative AI: The Future of Creativity
The year 2023 is a remarkable one in the field of GenerativeAI, LLM model acts as a stepping stone. The number of AI tools that spring out is humongous making it difficult to track them and in the coming days, the number is expected to touch the roof. Being mindful of these GenerativeAI tools is a necessity, as many firms have already started to use these tools in their daily work.
Generative AI is a rapidly developing field of artificial intelligence that is capable of creating new content. This includes text, images, music, video, and even code. If you have come across any fancy and creative images in social media that would be one from any of these GenerativeAI tools. Generative AI is still in its early stages, but it has the potential to revolutionize the way we create and consume content.
One of the most exciting things about generative AI is its potential to democratize creativity. In the past, only a few people had the skills and resources to create new content. But with generative AI, anyone can be a creator. It has the potential to level the playing field and give everyone a voice.
Of course, there are also some ethical concerns associated with generative AI. For example, some people worry that generative AI could be used to create deepfakes or other forms of synthetic media that could be used to deceive or manipulate people. It is important to be aware of these concerns and to use generative AI responsibly.
But overall, the potential benefits of generative AI outweigh the risks. Generative AI has the potential to make the world a more creative and interesting place. It can help us to solve problems, to communicate better, and simply enjoy ourselves more. The full potential of GenerativeAI tools will be explored more in the upcoming months.
Few of the Popular Generative AI Tools
12-Week Roadmap to Master GenerativeAI
Week 1–2: Basics of Machine Learning and Deep Learning
Start with brushing up on your fundamentals of Machine Learning (ML) and Deep Learning (DL). Understand ML algorithms, neural networks, loss functions, backpropagation, and more.
Week 3–4: Specialize in Neural Networks
Dive deeper into various types of neural networks like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). Learn their architecture, working, and applications.
Week 5: Introductory Generative Models
Start exploring generative models. Understand what they are and how they differ from discriminative models.
Week 6–7: Deep Dive into Autoencoders
Study Autoencoders in detail. Learn about their architecture, encoding, decoding, and loss functions. Implement simple autoencoders using Python and TensorFlow.
Week 8–9: Exploration of Generative Adversarial Networks (GANs)
Move to GANs. Understand the generator-discriminator game, and learn about different types of GANs and their applications. Implement a simple GAN for generating images.
Week 10: Variational Autoencoders (VAEs)
Study VAEs, which are a type of generative model that adds a probabilistic spin to autoencoders. Implement a VAE and compare its output with GANs.
Week 11: Advanced Generative Models
Explore advanced topics in generative models like CycleGANs, StyleGANs, and GPT models. Understand their architecture and how they’re used in creating complex and realistic output.
Week 12: Final Project
Implement a final project of your choice using Generative AI. It could be generating images, creating music, building a chatbot, or anything else that interests you.
Remember to constantly work on projects throughout these weeks, as practical understanding is key when learning about Generative AI. Explore different datasets and try to implement what you learn on them to see the results firsthand.
Since GenerativeAI is an evolving topic new tools and technologies pop out on a daily basis. So, I highly recommend you stay active in the GenerativeAI communities which help them to keep you up to date. I have listed a few here.
Resources
Generative AI Discord: https://decentralizedcreator.com/best-generative-ai-art-discord-server-for-ai-artist/
Generative AI Slack: https://futurumgroup.com/insights/salesforce-unveils-slack-gpt-a-generative-ai-tool-to-boost-employee-productivity/
Generative AI Reddit: https://econsultancy.com/online-community-dying-generative-ai-content-marketing/
Generative AI Stack Exchange: https://venturebeat.com/ai/stack-overflow-jumps-into-the-generative-ai-world-with-overflow-ai/
Generative AI Meetup: https://www.eventbrite.com/e/artificial-intelligence-weekly-community-meetup-tickets-666327011027
— — — — — — — — — — — — Happy Learning! — — — — — — — — — — — — —