Generative AI is the next big step in the world of artificial intelligence. It is something most would view as a revolutionary advancement to AI because it focuses on the creative side of AI. Generative AI is a groundbreaking type of artificial intelligence that can create new content, such as text, images, and music, by learning patterns from large sets of existing data.
These AI systems work through special computer models, mainly neural networks, which are designed to learn and mimic the patterns they see in the data that are fed to them. To train these models, they are fed massive amounts of data so they can understand and recreate the style and structure of the input data. For example, a generative AI trained on thousands of paintings can learn to create new artwork that mimics the style of the originals.
Some of the key models used in generative AI are Generative Adversarial Networks (GANs) and transformers like GPT-4. GANs have two parts: one that creates new content (the generator) and one that tries to spot flaws in that content (the discriminator), working together to improve the results.
Transformer models use a technique called attention to generate human-like text that makes sense in context. The concept of the AI mindset emphasizes the importance of designing and interacting with AI systems that are adaptable, continuously learning, and optimized for performance. Despite the advanced capabilities of generative AI, human involvement remains crucial for curating training data, fine-tuning models, and ensuring ethical and responsible AI deployment.
There is a significant difference between models and products. Models are the core algorithms trained to perform specific tasks. While, products are the applications that make use of these models to provide value to the end-users. and to generate income for themselves(scratch that). For example, a language model like GPT-4 can be integrated into a variety of products, from chatbots to content creation tools.
Now, to get the most out of these generative AI there are skills required such as prompt engineering. Prompt engineering is an essential skill in the effective use of generative AI, involving crafting precise and context-rich inputs to guide the AI in producing desired outputs. This is especially important as AI systems become more autonomous, acting as agents capable of performing complex tasks with minimal human intervention.
In summary, generative AI stands at the forefront of technological innovation, blending advanced modeling techniques, human oversight, and autonomous capabilities to transform content creation and automation. Watch this detailed video to learn about how AGI tools like Chat GPT work.
