Difference between revisions of "Generative AI"
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* [[Case Studies]] ... <i>too numerous to list here</i> | * [[Case Studies]] ... <i>too numerous to list here</i> | ||
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* [[Capabilities]] | * [[Capabilities]] | ||
** [[Video]] ... [[Generated Image]] ... [[Colorize]] ... [[Image/Video Transfer Learning]] | ** [[Video]] ... [[Generated Image]] ... [[Colorize]] ... [[Image/Video Transfer Learning]] | ||
Revision as of 15:51, 21 March 2023
YouTube ... Quora ...Google search ...Google News ...Bing News
- Generative AI ... OpenAI's ChatGPT ... Perplexity ... Microsoft's BingAI ... You ...Google's Bard ... Baidu's Ernie
- Assistants ... Hybrid Assistants ... Agents ... Negotiation
- Development ...AI Pair Programming Tools ... Analytics ... Visualization ... Diagrams for Business Analysis
- Case Studies ... too numerous to list here
- Capabilities
- AI Solver
- Discriminative vs. Generative
- Generative Model | Wikipedia
- Generative Pre-trained Transformer (GPT)
- Generative Query Network (GQN)
- Data Augmentation, Data Labeling, and Auto-Tagging
- Python ... Generative AI with Python ... Javascript ... Generative AI with Javascript ... Game Development with Generative AI
- Generative AI for Business Analysis
- Natural Language Generation (NLG)
- Emergence from Analogies
- Demos, generating...
- Music: Generating Piano Music with Transformer | I. Simon, A. Huang, J. Engel, C. "Fjord" Hawthorne - Google on Colab play with pretrained Transformer models for piano music generation, based on the Music Transformer model
- Faces: TF-Hub generative image model | The TensorFlow Hub Authors - Google use of a TF-Hub module based on a generative adversarial network (GAN). The module maps from N-dimensional vectors, called latent space, to RGB images.
- 3D Objects: 3D Style Transfer | Google uses Lucid to implement style transfer from a textured 3D model and a style image onto a new texture for the 3D model by using a Differentiable Image Parameterization.
- Three main types:
- Autoencoder (AE) / Encoder-Decoder
- Sequence Models
- Adversarial Networks
- Natural Language Processing (NLP) ...Generation ...LLM ...Tools & Services
Generative AI could improve the speed and accuracy of product research and development. Generative AI technology can also help with product engineering by allowing teams to simulate products in virtual environments. This allows for complex problems to be solved more quickly and efficiently, leading to improved design accuracy. - The Generative AI Revolution Is Creating The Next Phase Of Autonomous Enterprise | Mark Minevich - Forbes
Background: What is a Generative Model? | Google More formally, given a set of data instances X and a set of labels Y:
- Generative models capture the joint probability p(X, Y), or just p(X) if there are no labels.
- Discriminative models capture the conditional probability p(Y | X).
A generative model includes the distribution of the data itself, and tells you how likely a given example is. For example, models that predict the next word in a sequence are typically generative models (usually much simpler than GANs) because they can assign a probability to a sequence of words.
Informally:
- Generative models can generate new data instances.
- Discriminative models discriminate between different kinds of data instances.
Roblox
Roblox is a gaming platform and publishing system that allows users to create and play 3D games online. Some of the technologies used with Roblox are:
- Roblox Studio, a development environment that provides tools for creating and publishing games on Roblox
- Roblox VR, a virtual reality feature that enables users to enjoy the games in immersive 3D environments
- Generative AI, a new technology that uses artificial intelligence to generate code, assets, and content for Roblox games
- Amazon AWS, a cloud computing service that hosts Roblox’s servers and data centers
Deep Generative Modeling
Generative Modeling Language