Nvidia Perfusion: A Fresh Approach to AI Image Generation
The scientists at Nvidia have pioneered a new technique that converts textual content into imagery, helping to tackle the data storage predicaments that arise during the formation of novel models. Currently, the specifics of a single concept occupy roughly 100 KB. This efficiency stems from the fact that the approach doesn’t reengineer the entire model; instead, it adjusts select “internal representations”, bypassing the need to retrain the model entirely.
On this page
The scientists at Nvidia have pioneered a new technique that converts textual content into imagery, helping to tackle the data storage predicaments that arise during the formation of novel models.
Currently, the specifics of a single concept occupy roughly 100 KB. This efficiency stems from the fact that the approach doesn't reengineer the entire model; instead, it adjusts select “internal representations”, bypassing the need to retrain the model entirely.
The content on The Coinomist is for informational purposes only and should not be interpreted as financial advice. While we strive to provide accurate and up-to-date information, we do not guarantee the accuracy, completeness, or reliability of any content. Neither we accept liability for any errors or omissions in the information provided or for any financial losses incurred as a result of relying on this information. Actions based on this content are at your own risk. Always do your own research and consult a professional. See our Terms, Privacy Policy, and Disclaimers for more details.
Articles by this author
