Paper Title

Proposed Solutions for DALL-E 2

Authors

Mohammad Arkam , Aditya Thakur , Dr.Sandeep Kumar

Keywords

DALL-E 2, Machine Learning, Artificial Intelligence

Abstract

The successor to DALL-E from 2021, DALL-E 2, was unveiled by OpenAI, a research facility for artificial intelligence, In April. Both AI systems are capable of producing pictures that resemble photos, graphics, paintings, animations, and pretty much any other art form you can think of from text descriptions in natural language. Better resolution, quicker processing, and an editing function in DALL-E 2 upped the ante. These features allow users to alter created images using only text commands, such as "replace that vase with a plant" or "enlarge the dog's nose." Additionally, users can contribute their own images and instruct the AI algorithm how to riff on them. The DALL-E 2 system creates unique, artificial images that correspond to input text used as a caption. DALL-E 2 initially sparked awe and excitement throughout the world. In a matter of seconds, any assortment of items and creatures could be assembled, any artistic style could be imitated, any location could be portrayed, and any lighting conditions could be portrayed. As participants listed the industries that could very easily be affected by such a technology, there were also waves of worry. The findings that have surfaced in recent months speak volumes about the limitations of current deep-learning technology, providing us with a glimpse into what AI comprehends about the human world—and what it completely lacks.

How To Cite

"Proposed Solutions for DALL-E 2", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 12, page no.16 - 27, December-2022, Available :https://ijsdr.org/papers/IJSDR2212004.pdf

Issue

Volume 7 Issue 12, December-2022

Pages : 16 - 27

Other Publication Details

Paper Reg. ID: IJSDR_202854

Published Paper Id: IJSDR2212004

Downloads: 000347257

Research Area: Computer Science & Technology 

Country: Gautam Budh Nagar, Uttar Pradesh, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2212004

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2212004

About Publisher

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

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