Generative AI Evolution Of Artificial Intelligence AI CD

Slide 1: This slide introduces Generative AI: Evolution of Artificial Intelligence. State your company name and begin.
Slide 2: This is an Agenda slide. State your agendas here.
Slide 3: This slide shows Table of Content for the presentation.
Slide 4: This slide shows title for topics that are to be covered next in the template.
Slide 5: This slide provides information regarding generative AI technology that enables AI model to generate content in terms of images, videos etc.
Slide 6: This slide presents information regarding historic transformation of generative AI technology across several years.
Slide 7: This slide displays information regarding historic transformation of generative AI technology across several years.
Slide 8: This slide provides information regarding generative AI which helps in developing range of data variants in terms of images, video, audio, text and 3D models.
Slide 9: This slide presents information regarding potential use cases of generative AI technology which comprises of generating written content etc.
Slide 10: This slide provides information regarding comparative assessment of generative AI and artificial intelligence technologies.
Slide 11: This slide shows title for topics that are to be covered next in the template.
Slide 12: This slide provides information regarding architectural overview of generative AI with five layers associated to it.
Slide 13: This slide displays information regarding data preprocessing layer associated with generative AI architecture.
Slide 14: This slide provides information regarding generative model layer associated with generative AI architecture.
Slide 15: This slide presents information regarding feedback and improvement layer associated with generative AI architecture.
Slide 16: This slide provides information regarding the deployment and integration layers associated with generative AI architecture.
Slide 17: This slide displays information regarding monitoring and maintenance layer associated with generative AI architecture.
Slide 18: This slide provides information regarding generative AI tech stack layer in terms or applications, fine-tuning, foundation models, data and infrastructure.
Slide 19: This slide shows title for topics that are to be covered next in the template.
Slide 20: This slide provides information regarding training procedure of various types of generative AI models such as transformer-based model training, GAN model training etc.
Slide 21: This slide displays information regarding different ways to analyze the generative AI models on various parameters such as high quality of samples generated etc.
Slide 22: This slide provides information regarding metrics required for performance evaluation of generative AI model in terms of diversity, coverage etc.
Slide 23: This slide shows title for topics that are to be covered next in the template.
Slide 24: This slide provides information regarding significant methodologies of machine learning approach such as supervised learning, unsupervised learning etc.
Slide 25: This slide displays information regarding deep learning technology that helps systems to learn from large datasets through supervised or semi-supervised method.
Slide 26: This slide provides information regarding the operation of deep learning models with various layers of neural networks.
Slide 27: This slide presents information regarding implementation of large language model with generative AI model.
Slide 28: This slide provides information regarding the importance of prompt engineering in gaining desired results through generative AI systems.
Slide 29: This slide shows title for topics that are to be covered next in the template.
Slide 30: This slide provides information regarding AI-enabled generative model. This technique is useful for data augmentation, unsupervised learning etc.
Slide 31: This slide provides information regarding AI-based discriminative model. Such model is suitable for making predictions, classification tasks etc.
Slide 32: This slide displays information regarding diffusion model that helps in analyzing and predicting system’s behavior in accordance with time.
Slide 33: This slide provides information regarding different kinds of diffusion models such as denoising diffusion probabilistic models etc.
Slide 34: This slide displays information regarding various use cases of diffusion models integrated in AI. It assists in delivering optimum quality video generation.
Slide 35: This slide shows title for topics that are to be covered next in the template.
Slide 36: This slide provides information regarding generative adversarial networks (GANs) that are type of generative models to create new data samples.
Slide 37: This slide displays information regarding architecture of generative adversarial networks (GANs) which comprises of generator, discriminator.
Slide 38: This slide provides information regarding different types of GAN models such as Vanilla GAN, conditional GAN, deep convolutional GAN etc.
Slide 39: This slide presents information regarding different use cases of GANs in terms of image synthesis or generation, image-to-image translation etc.
Slide 40: This slide shows title for topics that are to be covered next in the template.
Slide 41: This slide provides information regarding recurrent neural networks which are developed to assess sequential data.
Slide 42: This slide displays information regarding different kinds of recurrent neural networks such as one to one RNNs or vanilla neural network etc.
Slide 43: This slide provides information regarding advanced versions of recurrent neural network such as bidirectional neural network and long short-term memory networks (LSTMs).
Slide 44: This slide presents information regarding comparison of recurrent and deep neural network on various parameters such as type, input, output applications etc.
Slide 45: This slide displays information regarding comparison of recurrent, convolutional and artificial neural networks on various parameters.
Slide 46: This slide shows title for topics that are to be covered next in the template.
Slide 47: This slide provides information regarding autoencoders which are neural network that utilized unsupervised learning.
Slide 48: This slide displays information regarding essential components of autoencoder architecture in terms of encoder, latent space etc.
Slide 49: This slide provides information regarding autoencoders as a versatile tool for data preprocessing and has various applications such as image or audio compression etc.
Slide 50: This slide displays information regarding advantages and disadvantages of autoencoders which make them relevant for specialized tasks along with potential challenges.
Slide 51: This slide shows title for topics that are to be covered next in the template.
Slide 52: This slide provides information regarding variational autoencoders are a type of generative model that develops upon the concept of conventional autoencoders.
Slide 53: This slide displays information regarding training process of variational autoencoders which are competent in generating new samples by learning from training dataset.
Slide 54: This slide shows title for topics that are to be covered next in the template.
Slide 55: This slide provides information regarding generative AI market insights in terms of market size along with growth rate etc.
Slide 56: This slide displays information regarding various generative AI tools that utilize machine learning and deep learning techniques to perform certain tasks.
Slide 57: This slide provides information regarding various generative AI tools that utilize machine learning and deep learning techniques to perform certain tasks.
Slide 58: This slide presents information regarding ChatGPT platform in terms of its features such as capability to interact in conversational dialogue pattern.
Slide 59: This slide provides information regarding key elements of ChatGPT architecture which is based on a neural network, including input layer etc.
Slide 60: This slide displays information regarding the various applications of ChatGPT platform for users in terms of consumer assistance, content development etc.
Slide 61: This slide provides information regarding the potential video generation platform Synthesia AI which enables users to create professional videos.
Slide 62: This slide displays information regarding various steps through which videos can be created through Synthesia AI platform.
Slide 63: This slide provides information regarding GPT-4 model, which is the upgraded version of GPT-3 and advanced multimodal version competent in processing text, images and videos.
Slide 64: This slide presents information regarding the superiority of GPT-4 in comparison to previous models such as language or dialect expertise etc.
Slide 65: This slide shows title for topics that are to be covered next in the template.
Slide 66: This slide provides information regarding generative AI ethics which are essential to manage ethical implications and potential challenges imposed by sophisticated AI model.
Slide 67: This slide displays information regarding significant ethical concerns associated with generative AI governance in terms of unknown capabilities etc.
Slide 68: This slide provides information regarding relevant measures to address ethical implications of generative AI in terms of diversification of training data etc.
Slide 69: This slide displays information regarding best practices to be followed while implementing enterprise generative AI architecture.
Slide 70: This slide provides information regarding different way explainability in generative AI systems can be improved by model simplification etc.
Slide 71: This slide shows title for topics that are to be covered next in the template.
Slide 72: This slide provides information regarding future of generative AI which is captures great potential for several industries and applications.
Slide 73: This slide displays information regarding potential facts associated with generative AI usage in the future.
Slide 74: This slide provides information regarding primary focus areas of generative AI initiatives in terms of customer experience, revenue growth etc.
Slide 75: This slide shows title for topics that are to be covered next in the template.
Slide 76: This slide provides information regarding the economic potential of generative AI systems in driving productivity with substantial impact on various sectors.
Slide 77: This slide provides information regarding transformation of customer operations with the advancement of generative AI systems.
Slide 78: This slide displays information regarding transformation of marketing and sales with the advancement of generative AI systems along strategization etc.
Slide 79: This slide provides information regarding transformation of software engineering with the advancement of generative AI systems along inception and planning etc.
Slide 80: This slide presents information regarding transformation of research and development (R&D) with the advancement of generative AI systems.
Slide 81: This slide shows all the icons included in the presentation.
Slide 82: This is a Thank You slide with address, contact numbers and email address.