주민건

Large language models have exhibited exceptional performance on variousNatural Language Processing (NLP) tasks, leveraging techniques such as thepre-training, and instruction fine-tuning. Despite these advances, theireffectiveness in medical applications is limited, due to challenges such asfact…

The recently proposed segment anything model (SAM) has made a significantinfluence in many computer vision tasks. It is becoming a foundation step formany high-level tasks, like image segmentation, image caption, and imageediting. However, its huge computation costs prevent it from wider applicat…

Generating realistic human motion from given action descriptions hasexperienced significant advancements because of the emerging requirement ofdigital humans. While recent works have achieved impressive results ingenerating motion directly from textual action descriptions, they often supportonly…

We introduce phi-1, a new large language model for code, with significantlysmaller size than competing models: phi-1 is a Transformer-based model with1.3B parameters, trained for 4 days on 8 A100s, using a selection of ``textbookquality” data from the web (6B tokens) and synthetically generated t…

An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Model for All. - GitHub - OptimalScale/LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Found...

Singing Voice Conversion via diffusion model. Contribute to prophesier/diff-svc development by creating an account on GitHub.

택시가 두 차선에 걸쳐 전복된 고속도로나 공룡 복장을 한 행인이 차도에 뛰어드는 모습 등 현실에서는 수집하기 어려운 상황을 합성 데이터로 생성해주는 인공지능(AI) 도구가 나왔다.자율주행차나 드론 등에 적용하는 AI 시스템을 훈련하는데 필요하지만 실제로는 부족한 데이터를 생성해 AI 시스템 훈련을 보다 효과적으로 진행할 수 있게 됐다. 테크크런치는 19일(현지시간) 미국 스타트업 패러렐도메인이 이와같은 합성 데이터를 생성할 수 있는 새로운 API인 ‘데이터 랩(Data Lab)’을 출시했다고 보도했다.데이터 랩은 생성 AI를 활용해

Robots are quickly becoming part of our everyday lives, but they’re often only programmed to perform specific tasks well. While harnessing recent advances in AI could lead to robots that could help in many more ways, progress in building general-purpose robots is slower in part because of the time n…

의료 인공지능(AI) 기업 루닛이 미국 정부가 추진하는 암 정복 프로젝트에 참여한다. 19일 관련 업계에 따르면 루닛은 미국의 암 연구소인 모핏 암 센터(Moffitt Cancer Center)와 디지털의학학회(Di

GPT4 passes all MIT Math, EE & CS (EECS) courses testss with near 100% accuracy -4,550 questions from the 30 MIT Math & CS courses required for a degree Test… | 239 comments on LinkedIn