Search Results
DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale
As the training of giant dense models hits the boundary on the availability and capability of the hardware resources today, Mixture-of-Experts (MoE) models become one of the most promising model architectures due to their significant training cost reduction compared to a quality-equivalent dense model.
USP: A Unified Sequence Parallelism Approach for Long Context Generative AI
Sequence parallelism (SP), which divides the sequence dimension of input tensors across multiple computational devices, is becoming key to unlocking the long-context capabilities of generative AI models.
MusicAgent: An AI Agent for Music Understanding and Generation with Large Language Models
For developers and amateurs, it is very difficult to grasp all of these task to satisfy their requirements in music processing, especially considering the huge differences in the representations of music data and the model applicability across platforms among various tasks.
EasyPhoto: Your Smart AI Photo Generator
By training a digital doppelganger of a specific user ID using 5 to 20 relevant images, the finetuned model (according to the trained LoRA model) allows for the generation of AI photos using arbitrary templates.
PyRIT: A Framework for Security Risk Identification and Red Teaming in Generative AI System
To meet this need, we introduce the Python Risk Identification Toolkit (PyRIT), an open-source framework designed to enhance red teaming efforts in GenAI systems.
Retrieval-Augmented Generation for AI-Generated Content: A Survey
We first classify RAG foundations according to how the retriever augments the generator, distilling the fundamental abstractions of the augmentation methodologies for various retrievers and generators.
SocratiQ: A Generative AI-Powered Learning Companion for Personalized Education and Broader Accessibility
Traditional educational approaches often struggle to provide personalized and interactive learning experiences on a scale.
Computers and Society
Leveraging Speculative Sampling and KV-Cache Optimizations Together for Generative AI using OpenVINO
Inference optimizations are critical for improving user experience and reducing infrastructure costs and power consumption.
Adversarial Diffusion Distillation
We introduce Adversarial Diffusion Distillation (ADD), a novel training approach that efficiently samples large-scale foundational image diffusion models in just 1-4 steps while maintaining high image quality.
Programming Is Hard -- Or at Least It Used to Be: Educational Opportunities And Challenges of AI Code Generation
The introductory programming sequence has been the focus of much research in computing education.
