A New Framework for How the Brain Compresses Our Noisy World
(翻译)大脑压缩嘈杂世界的新框架
An updated view of categorization reflects the modern understanding that the nervous system is more of a prediction engine than a filing cabinet.

(翻译)大脑压缩嘈杂世界的新框架
An updated view of categorization reflects the modern understanding that the nervous system is more of a prediction engine than a filing cabinet.

(翻译)将手语AI交到用户手中
Introducing sign-language-to-text (SL2T), our breakthrough model powering new sign language features for Deaf and hard of hearing users.
(翻译)衡量语音识别中的基准优化
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
(翻译)使用Snowflake、Amazon SageMaker Canvas和Amazon Quick构建无代码机器学习工作流——第1部分:设置Snowflake环境
Healthcare, retail, and life sciences teams store large volumes of operational data in Snowflake, but turning it into predictions is hard. In Part 1 of this series, you set up your AWS account and Snowflake environment for a no-code ML workflow with Amazon SageMaker Canvas, laying the foundation for
(翻译)使用 NVIDIA FLARE 构建联邦多模态 AI 工作流
Modern vision-language models (VLMs) can support tasks such as visual question answering, captioning, and image-text reasoning. In practice, however…

(翻译)DiffusionGemma:文本生成速度最高提升4倍
An overview of DiffusionGemma, an exceptionally fast text generation model with up to 4x faster speeds.

(翻译)使用Snowflake、Amazon SageMaker Canvas和Amazon Quick构建无代码ML工作流——第3部分:使用Amazon Quick Sight可视化洞察
In Part 3 of this no-code ML series, you bring fraud detection predictions to life. Import your Amazon SageMaker Canvas predictions into Amazon Quick Sight, build interactive dashboards, use generative BI to answer questions in natural language, and publish AI-generated executive summaries for stake
(翻译)AWS 向量解决方案:在数据所在之处构建智能体 AI
AWS offers a broad portfolio of vector search built directly into the databases and storage services you already use, with no standalone vector database or data migration required. This post covers six purpose-built services, a decision framework for choosing the right engine, and customer proof poi
(翻译)CUDA Python 1.0:稳定API、统一基础、完整平台访问
For years, a Python developer who needed a GPU had two realistic choices: Learn NVIDIA CUDA C++ well enough to write an extension, set up a build toolchain…

(翻译)将 Nunchaku 4-bit 扩散推理引入 Diffusers
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
(翻译)使用Amazon Quick Desktop和Amazon FSx for NetApp ONTAP实现受治理的报告
Build a governed weekly reporting workflow with Amazon Quick Desktop and Amazon FSx for NetApp ONTAP. An Amazon S3 access point exposes an approved folder to a Quick knowledge base, and a custom skill drafts cited weekly reports and Slack summaries with human review before anything is shared.
(翻译)量化感知修复:性能超越全精度原版的压缩 4 比特模型
A Blog post by Multiverse Computing on Hugging Face

(翻译)Granite 4.2 大语言模型:它们是如何构建的
A Blog post by IBM Granite on Hugging Face

(翻译)MolEmb:多模态大语言模型可以成为强大的分子嵌入模型
Abstract page for arXiv paper 2608.23646: MolEmb: Multimodal Large Language Models Can Be Strong Molecular Embedding Models
11 套英伟达 GB200 连续跑 3 个月,大模型最昂贵的“炼丹过程”被彻底摊开。
