techxplore2d
Self-adaptive LLM dynamically adjusts its weights to learn new tasks
A trio of AI researchers at Sakana AI, a Japanese startup, has announced the development of a self-adaptive AI LLM called Transformer2. Qi Sun, Edoardo Cetin, and Yujin Tang, have posted their paper ...
GitHub2d
⚡️Sana: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer
Core designs include: (1) DC-AE: unlike traditional AEs, which compress images only 8×, we trained an AE that can compress images ... As a result, Sana-0.6B is very competitive with modern giant ...
Scientific Research Publishing3d
A Dynamic Knowledge Base Updating Mechanism-Based Retrieval-Augmented Generation Framework for Intelligent Question-and-Answer Systems ()
In the context of power generation companies, vast amounts of specialized data and expert knowledge have been accumulated. However, challenges such as data silos and fragmented knowledge hinder the ...
LinkedIn15d
How do you use and fine-tune pre-trained models for NLP portfolio projects?
If you want to showcase your NLP skills in a portfolio project, you might wonder how to use and fine-tune pre-trained models for your specific task. Pre-trained models are powerfu ...
Business Insider17d
Over 300 customers pre-ordered AC Future’s newly launched AI Transformer Home using BioMatrix Proof of You AI Tokens on the first day of CES 2025.
Las Vegas, NV, Jan. 09, 2025 (GLOBE NEWSWIRE) -- Over 300 customers pre-ordered AC Future’s newly launched AI Transformer Home using BioMatrix Proof of You AI Tokens on the first day of CES 2025.
marktechpost19d
Transformer-Based AI Models for Ovarian Lesion Diagnosis: Enhancing Accuracy and Reducing Expert Referral Dependence Across International Centers
The models were trained on this dataset using a transformer-based architecture, applying leave-one-center-out cross-validation. The study used various evaluation metrics to compare AI model ...
eLife20d
Using normative models pre-trained on cross-sectional data to evaluate intra-individual longitudinal changes in neuroimaging data
In this manuscript, the authors provide a method aiming to accurately reflect the individual deviation of longitudinal/temporal change compared to the normal temporal change characterized based on pre ...
marktechpost21d
Graph Generative Pre-trained Transformer (G2PT): An Auto-Regressive Model Designed to Learn Graph Structures through Next-Token Prediction
Researchers from Tufts University, Northeastern University, and Cornell University have developed the Graph Generative Pre-trained Transformer (G2PT), an auto-regressive model designed to learn graph ...
GitHub24d
axinc-ai/ailia-models
ailia SDK is a self-contained, cross-platform, high-speed inference SDK for AI. The ailia SDK provides a consistent C++ API across Windows, Mac, Linux, iOS, Android, Jetson, and Raspberry Pi platforms ...