SUI

https://youtu.be/SU5k4TpDYfM?si=A1j4YYILdyFiJbBP 마이크로소프트의 OpenAI 파트너십 결정 배경: AI 기술 발전 속도가 가속화되고 있음을 인지 마이크로소프트가 경쟁력 유지를 위해서는 AI 분야의 선도적 위치 확보가 필수적 컴퓨팅 인프라 구축과 전문성 확보를 위해 OpenAI와의 협력이 중요했음 AI의 사회문제 해결 잠재력: 의료 서비스 접근성이 떨어지는 시골 지역 등에 AI 의료 어시스턴트를 제공하여 의료 불평등 해소 가능 온라인 교육 플랫폼과 AI 튜터링 서비스로 양질의 교육 기회 제공 기술 활용 역량 강화를 통해 저소득층과 농촌 지역 경제 활성화에 기여 AI가 일자리에 미칠 영향: 단기적으로 일부 업무의 자동화로 일자리 감소 우려가 있으나, 장기적으로는 인간의..

https://arxiv.org/abs/2307.02486 LongNet: Scaling Transformers to 1,000,000,000 Tokens Scaling sequence length has become a critical demand in the era of large language models. However, existing methods struggle with either computational complexity or model expressivity, rendering the maximum sequence length restricted. In this work, we intr arxiv.org https://github.com/microsoft/torchscale GitH..

https://arxiv.org/abs/2306.14892 Supervised Pretraining Can Learn In-Context Reinforcement Learning Large transformer models trained on diverse datasets have shown a remarkable ability to learn in-context, achieving high few-shot performance on tasks they were not explicitly trained to solve. In this paper, we study the in-context learning capabilities o arxiv.org 1. 다양한 데이터셋에서 훈련된 대형 트랜스포머 모델은 ..

https://arxiv.org/abs/2306.14824 Kosmos-2: Grounding Multimodal Large Language Models to the World We introduce Kosmos-2, a Multimodal Large Language Model (MLLM), enabling new capabilities of perceiving object descriptions (e.g., bounding boxes) and grounding text to the visual world. Specifically, we represent refer expressions as links in Markdown, i arxiv.org https://github.com/microsoft/uni..