Category: Uncategorized
-
아마존, 구직자의 흔한 실수 정리한 ‘입사 면접 가이드’ 공개
실수가 반복되면 더 이상 실수가 아니다. 그렇다고 한 번의 실수는 괜찮은가? 그것도 아니다. 단 한 번의 실수가 모든 것을 뒤 바꾸는 경우가 허다하다. 이를 테면 입사 면접에서 사소한 또는 황당한 실수가 그렇다. 아마존이 ‘아마존 채용 면접에서 절대 하지 말아야 할 6가지’를 통해 공개했다. 그만큼 이런 ‘실수’가 많다는 얘기다. 아마존 마케팅 관리자인 브리트니 번치는 아마존의 채용… Read more
-
NVIDIA AI Researchers Explore Upcycling Large Language Models into Sparse Mixture-of-Experts
Mixture of Experts (MoE) models are becoming critical in advancing AI, particularly in natural language processing. MoE architectures differ from traditional dense models by selectively activating subsets of specialized expert networks for each input. This mechanism allows models to increase their capacity without proportionally increasing the computational resources required for training and inference. Researchers are… Read more
-
OpenAI unveils experimental ‘Swarm’ framework, igniting debate on AI-driven automation
OpenAI has unveiled “Swarm,” an experimental framework designed to orchestrate networks of AI agents. This unexpected release has ignited intense discussions among industry leaders and AI ethicists about the future of enterprise automation, despite the company’s emphasis that Swarm is not an official product. Swarm provides develo…Read More Read more
-
클라우데라-스노우플레이크 협력 발표··· 개방형 통합 데이터 레이크하우스 지원
클라우데라에 따르면 기업은 데이터 수집, 처리, 소비를 위해 클라우데라와 스노우플레이크의 두 가지 도구를 결합해 모든 데이터, 분석, AI 워크로드 전반에 걸쳐 통합 결과물을 도출할 수 있다. 클라우데라는 데이터가 비즈니스의 가장 강력한 자산이라며 정보에 기반한 의사결정을 이끌고, 경쟁 우위를 제공하며, 혁신의 기회를 발견할 수 있게 한다고 설명했다. 2022년 영국 경제경영연구소(CEBR) 조사에 따르면, 기업의 80%는 실시간 데이터… Read more
-
F5-TTS: A Fully Non-Autoregressive Text-to-Speech System based on Flow Matching with Diffusion Transformer (DiT)
The current challenges in text-to-speech (TTS) systems revolve around the inherent limitations of autoregressive models and their complexity in aligning text and speech accurately. Many conventional TTS models require complex elements such as duration modeling, phoneme alignment, and dedicated text encoders, which add significant overhead and complexity to the synthesis process. Furthermore, previous models like… Read more
-
Holistic Evaluation of Vision Language Models (VHELM): Extending the HELM Framework to VLMs
One of the most pressing challenges in the evaluation of Vision-Language Models (VLMs) is related to not having comprehensive benchmarks that assess the full spectrum of model capabilities. This is because most existing evaluations are narrow in terms of focusing on only one aspect of the respective tasks, such as either visual perception or question… Read more
-
Apple Researchers Introduce GSM-Symbolic: A Novel Machine Learning Benchmark with Multiple Variants Designed to Provide Deeper Insights into the Mathematical Reasoning Abilities of LLMs
Recent progress in LLMs has spurred interest in their mathematical reasoning skills, especially with the GSM8K benchmark, which assesses grade-school-level math abilities. While LLMs have shown improved performance on GSM8K, doubts remain about whether their reasoning abilities have truly advanced, as current metrics may only partially capture their capabilities. Research suggests that LLMs rely on… Read more
-
LLMs can’t outperform a technique from the 70s, but they’re still worth using — here’s why
Why we must develop methods, procedures and practices to make sure that improvements in some areas don’t eliminate LLMs’ other advantages. Read More Read more
-
Data center tech is exploding but adoption won’t be easy for startups
The data center industry is expanding rapidly to keep up with the flywheel growth of AI. While these data centers are necessary AI infrastructure, they store an AI company’s compute, they are expensive to build, seemingly more so to run, and they are a huge energy suck. Startups are looking to make data centers more… Read more
-
11 Best Lubes of 2024, Tested and Reviewed
For the most sensitive parts of the human body, friction is the enemy. Here’s how to keep it at bay with our favorite lubes made of water, silicone, or natural oil. Read more