风险思维：Riskthinking.AI 如何利用机器学习为不确定的世界带来确定性
公司规模
11-200
地区
- America
国家
- Canada
产品
- CovidWisdom app
- Pachyderm
技术栈
- Machine Learning
- AI architecture
- Data Science
- Docker containers
实施规模
- Enterprise-wide Deployment
影响指标
- Innovation Output
- Productivity Improvements
技术
- 分析与建模 - 机器学习
- 应用基础设施与中间件 - 数据交换与集成
适用行业
- 城市与自治市
- 医疗保健和医院
适用功能
- 商业运营
用例
- 预测性维护
- 公共交通管理
服务
- 数据科学服务
关于客户
Riskthinking.AI 是一家专门衡量气候变化财务风险的公司。他们与公司和政府合作，帮助他们在不确定的未来做出最佳决策。例如，他们可以帮助电力公司决定是否在过去引起森林火灾的同一地点重建变压器，或者将其置于不同的配置中，以减少未来再次引发火灾的可能性。他们还帮助公司确定他们能够以多快的速度扩建太阳能发电场以及应该将其建在何处。然而，他们很早就意识到，虽然他们有预测未来的专家，但他们缺乏构建 AI 架构的专业知识。
挑战
Riskthinking.AI 是一家专门衡量气候变化财务风险的公司，在接手 CovidWisdom 项目时，该公司正处于加强内部 AI 基础设施的早期阶段。该项目响应了加拿大政府的号召，旨在评估主要疫情政策对经济的影响。该项目的挑战在于预测实施社会层面应对措施（如封锁）的最佳方式，同时将对日常生活和经济的损害降至最低。然而，该团队意识到，他们有预测未来的专家，但没有构建 AI 架构的专家。他们让数据科学家使用笔记本电脑工作，通过 VPN 将数据拉取和推送到远程工作点，甚至构建自己的 Docker 容器。他们需要从临时转向 MLOps。
解决方案
Riskthinking.AI 决定使用 Pachyderm，该平台允许其科学家专注于模型的复杂性，而不是弄清楚哪个模型是在哪个版本的数据集上训练的复杂性。它为他们提供了处理数据和在机器学习循环中部署任何所需 ML 工具的基础。随着 Riskthinking.AI 的数据科学家对 pachctl 和命令行越来越熟悉，他们使用 Pachyderm 同时运行多个模型，并通过易于理解的图像可视化回测结果。当天表现最佳的模型会自动推送到应用程序中。可视化不仅适用于数据科学团队。他们还可以与非技术或技术水平较低的利益相关者分享他们的进展。
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