workflows关键词检索结果

为 Amazon Bedrock 构建主动 AI 成本管理系统 – 第 1 部分

Build a proactive AI cost management system for Amazon Bedrock – Part 1

In this post, we introduce a comprehensive solution for proactively managing Amazon Bedrock inference costs through a cost sentry mechanism designed to establish and enforce token usage limits, providing organizations with a robust framework for controlling generative AI expenses. The solution uses

Metagenomi 使用 AWS Inferentia 经济高效地生成数百万种新型酶

Metagenomi generates millions of novel enzymes cost-effectively using AWS Inferentia

In this post, we detail how Metagenomi partnered with AWS to implement the Progen2 protein language model on AWS Inferentia, achieving up to 56% cost reduction for high-throughput enzyme generation workflows. The implementation enabled cost-effective generation of millions of novel enzyme variants u

AI驱动的学习在与Arist的联合创始人兼首席执行官Michael Ioffe的工作流程中

AI-Powered Learning in the Flow of Work with Michael Ioffe, CoFounder and CEO of Arist

欢迎与与Arist的创始人Michael Ioffe一起进行学习的鼓舞人心的对话,Arist的创始人是一家非常有趣的教育工作。迈克尔(Michael)是30岁以下的福布斯(Forbes)和蒂尔(Thiel)的研究员。迈克尔加入主持人迈克·帕尔默(Mike Palmer)分享自己的旅程,从早期对教育的痴迷开始,受到难民的父母的影响。他的经验,包括将与企业家的免费现场对话扩展到18岁的50个国家 /地区的500个城市,导致了对也门战争区的关键见解:提供教育资源和Internet访问的学习的最佳方法是通过文本消息。这导致建立Arist,这重点是与他们所在的人见面,并使学习对话和消化。我们探索约束如何

abb和Landingai释放了生成AI的机器人视觉的力量

ABB and LandingAI Unleash the Power of Generative AI for Robotic Vision

• Strategic investment secures ABB’s use of LandingAI’s vision AI capabilities, such as LandingLens, for robot AI vision applications• Pre-trained models, smart data workflows and no-code tools reduce training time by 80% and accelerate deployment in fast-moving sectors including logistics, healthca

数据中心以外:高盛的硅谷实地考察发现AI从筹码转移到工作流程

Beyond The Data Center: Goldman's Silicon Valley Field Trip Finds AI Moving From Chips To Workflows

Beyond The Data Center: Goldman's Silicon Valley Field Trip Finds AI Moving From Chips To WorkflowsGoldman analysts led by George Tong returned to Silicon Valley for their second AI field trip, meeting with AI startups, public companies, VCs, and professors from Stanford, UCSF, and UC Berkeley to as

通过将Salesforce Agent Force与Amazon Bedrock Agents集成来自动企业工作流程

Automate enterprise workflows by integrating Salesforce Agentforce with Amazon Bedrock Agents

这篇文章探讨了实用的合作,将Salesforce Force与Amazon Bedrock Agents和Amazon Redshift集成,以使Enterprise Workflows自动化。

在微风中构建算法 - 敏捷的ML管道

Build Algorithm-Agnostic ML Pipelines in a Breeze

该框架现在是用于流线型ML Workflows的开源Python软件包,邮政构建算法 - 敏捷的ML管道在微风中首先出现在数据科学上。

Bruker揭幕了新的ProteoEleute™Nanolc系统和Pepse®高级NLC列,可提高50%的改善肽灵敏度

Bruker Unveils New proteoElute™ nanoLC System and PepSep® Advanced nLC Columns for up to 50% Improved Peptide Sensitivity

At the 73rd Conference on Mass Spectrometry and Allied Topics (ASMS), Bruker Corporation has announced the new proteoElute™ nanoLC system, featuring ceramic valves, proteoTrap™ trapping columns, and next-generation PepSep® Advanced nLC columns, further enhancing robustness, sensitivity and proteome

分支:用于协作 ML 的 4 个 Git 工作流

Branching Out: 4 Git Workflows for Collaborating on ML

完成硕士学位已经 15 年多了,但我仍然被管理 R 脚本的令人抓狂的挫败感所困扰。作为一个(正在恢复的)完美主义者,我非常系统地按日期命名每个脚本(想想:ancova_DDMMYYYY.r)。我*知道*的系统比 _v1、_v2、_final 及其敌人更好。对吗?问题是,每次我想 […]The post Branching Out: 4 Git Workflows for Collaborating on ML 最先出现在 Towards Data Science 上。

Curvestone 推出“AI 工作流程”,Walker Morris 签约

Curvestone Launches ‘AI Workflows’, Walker Morris Signs Up

技术开发集团 Curvestone 宣布推出 Workflows,这是其 WorkflowGPT genAI 平台的新模块。律师事务所 Walker Morris 是其……

在 LLM 代理框架之间进行选择

Choosing Between LLM Agent Frameworks

构建定制的基于代码的代理和主要代理框架之间的权衡。作者提供的图片感谢 John Gilhuly 对本文的贡献。代理正处于发展阶段。随着多个新框架和该领域的新投资,现代 AI 代理正在克服不稳定的起源,迅速取代 RAG 成为实施优先事项。那么 2024 年最终会成为自主 AI 系统接管编写电子邮件、预订航班、与我们的数据对话或任何其他任务的一年吗?也许,但要达到这一点还有很多工作要做。任何构建代理的开发人员不仅必须选择基础——使用哪种模型、用例和架构——还必须选择要利用哪个框架。您会选择长期存在的 LangGraph 还是新进入的 LlamaIndex Workflows?或者你走传统路线,自己

自动化研究工作流程正在加快科学发现的步伐 - 新报告提供了促进其发展的建议

Automated Research Workflows Are Speeding Pace of Scientific Discovery - New Report Offers Recommendations to Advance Their Development

Automated research workflows — which integrate computation, laboratory automation, and tools from artificial intelligence — have the potential to increase the speed of research activities and accelerate scientific discovery. A new report recommends ways to advance their development.