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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.15 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Proposed Solutions for DALL-E 2 |
| Authors Name: | Mohammad Arkam , Aditya Thakur , Dr.Sandeep Kumar |
| Unique Id: | IJSDR2212004 |
| Published In: | Volume 7 Issue 12, December-2022 |
| 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. |
| Keywords: | DALL-E 2, Machine Learning, Artificial Intelligence |
| Cite Article: | "Proposed Solutions for DALL-E 2", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 12, page no.16 - 27, December-2022, Available :http://www.ijsdr.org/papers/IJSDR2212004.pdf |
| Downloads: | 000201529 |
| Publication Details: | Published Paper ID: IJSDR2212004 Registration ID:202854 Published In: Volume 7 Issue 12, December-2022 DOI (Digital Object Identifier): Page No: 16 - 27 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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