Generative AI uses a number of techniques that continue to evolve, but foremost are AI foundation models.
Generative AI foundation models are trained on a broad set of unlabeled data that can be used for different tasks, with additional fine-tuning. Complex math and enormous computing power are required to create these trained models, but they are, in essence, prediction algorithms.
What separates generative AI from AI in general is that generative AI can learn from existing artifacts to generate new, realistic artifacts (at scale) that reflect the characteristics of the training data but don’t repeat it.
Consequently, generative AI can produce a variety of novel content, such as images, video, music, speech, text, software code and product designs.
Generative AI in Natural Language Processing (NLP) is the technology that enables machines to generate human-like text or speech. Unlike traditional AI models that analyze and process existing data, generative models can create new content based on the patterns they learn from vast datasets.
These models utilize advanced algorithms and neural networks, often employing architectures like Recurrent Neural Networks (RNNs) or Transformers, to understand the intricate structures of language.
Generative AI models can produce coherent and contextually relevant text by comprehending context, grammar, and semantics. They are invaluable tools in various applications, from chatbots and content creation to language translation and code generation.
At the heart of Generative AI in NLP lie advanced neural networks, such as Transformer architectures and Recurrent Neural Networks (RNNs).
These networks are trained on massive text corpora, learning intricate language structures, grammar rules, and contextual relationships. Through techniques like attention mechanisms, Generative AI models can capture dependencies within words and generate text that flows naturally, mirroring the nuances of human communication.
Want to learn more? Tonex offers Generative AI Training Course, a comprehensive cutting-edge 2-day course that covers the fundamentals of generative AI, including Natural Language Processing (NLP), Machine Learning (ML), and Deep Learning (DL).
The course is designed for beginners and intermediate learners, and it provides a solid foundation in the principles of generative AI.
The course also includes a number of hands-on projects that allow learners to apply the concepts they have learned.
Additionally, be sure to check out two new neural learning labs by Tonex:
NLL.AI (Neural Learning Lab AI)
NLLCI.org (Neural Learning Lab Cybersecurity Institute).
For more information, questions, comments, contact us.