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Boardwalk Empire: How Generative AI is Revolutionizing Economic Paradigms

The relentless pursuit of technological advancements has ushered in a new era where artificial intelligence (AI) is not only a powerful tool but also a critical economic driver. At the forefront of this transformation is Generative AI, which is catalyzing a paradigm shift across industries. Deep generative models, an integration of generative and deep learning techniques, excel in creating new data beyond analyzing …

Licence
OPEN CC-BY-4.0
Authors
Subramanyam Sahoo, Kamlesh Dutta
Published
2024-10-19 · arXiv
Language
en
Length
14263 words
Type
narrative text

Cites 34 works

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Appendix Section

Examples of Generative AI models

These illustrations show the range of uses and domains for which generative AI is appropriate. Not only do the models demonstrate impressive capabilities, but they also highlight the necessity of a more thorough investigation of the moral dilemmas, possible biases, and the critical requirement for responsible implementation that exist in both the developmental and operational stages of generative AI systems.As we work throughout the broad field of generative AI, we need to be mindful of the subtle nuances that come with using such strong technology, and we must carefully address ethical concerns. It entails a thorough examination of any biases that might unintentionally arise during deployment or training, and it encourages researchers and practitioners to implement safety precautions to prevent undesirable results.Furthermore, ethical use of generative AI is necessary, which means that any possible harm to society must be kept to a minimum. This suggests that these systems need to uphold moral principles and advance the goals of the greater technological community. This is a turning point in the responsible development of AI, since it highlights how important it is to integrate generative AI with care and purpose given the intricate relationship between technical progress and societal wellness.

GENRATIVE MODELS SOFTWARE TOOL NAME
Text to Image (T2I) DALLE-E 2 Stable Diffusion Craiyon Jasper Imagen MidJourney NightCafe GauGAN 2 Wombo Wonder neural.love Pixray-test2image
Text to Video (T2V) Runway Gen-2 ModelScope ZeroScope VideoCrafter Synthesis Kaiber Wonder Studio Phenaki Meta’s Make-A-Video Nvidia’s Latent Diffusion Model
Text to Audio (T2A) Murf.ai Play.ht Resemble.ai WellSaid Descript lovo.ai Speechify Listnr Sonantic Woord
Text to Text (T2T) Simplified Frase Requstory Grammarly Market Muse HubSpot Flowrite SudoWrite Copysmith Ideasbyai
Text to Motion (T2M) MDM: Human Motion Diffusion Model TREEInd. VQGAN-CLIP
Text to Code (T2C) StarCoder OpenAI Codex GitHub Copilot CodeT5 Polycoder Replit Ghostwriter Tabine
Text to NFT (T2N) ArtBreeder DeepDreamGenerator Deep Art Effect StyleGAN RunwayML Google Muse AI Prisma NeuralStyle AI
Text to 3D (T2D) DreamFusion Clip - Mesh GET 3D Mochi Masterpiece Studio Spline AI Meshcapade

Table 3: Examples of Generative AI models by taking Text data as Source

GENRATIVE MODELS SOFTWARE TOOL NAME
Audio to Text (A2T) 1.WaveNet 2.DeepVoice 3.tacotron 4.MelGAN 5.hiFiGAN 6.Descript 7.AssemblyAI 8.Whisper(OpenAI)
Audio to Video (A2V) 1.Audio2Vec 2.MusicVAE 3.MoCoGAN 4.VCGAN 5.Diffusion models
Audio to Audio (A2A) 1.AudioLM 2.VOICEMOD

Table 4: Examples of Generative AI models by taking Audio as Source