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ACCELERATE OUTCOMES WITH A BACKBONE FOR ARTIFICIAL INTELLIGENCE.

makes machine learning operational by connecting models to the real-world decisions they inform. Often, AI/ML algorithms live in experimental vacuums. Foundry provides the end-to-end infrastructure an organization needs to apply AI/ML to real problems and real data:

  • A data foundation.  provides the data engineering capabilities an organization needs to deploy AI/ML models it can trust. Organizations use  to build a solid foundation of sufficient, quality data, then bring that data into daily operations.

  • Production deployment infrastructure. revolutionizes the way organizations build and deploy AI/ML by combining a data foundation with end-to-end algorithm deployment infrastructure. Data scientists and engineers can customize, deploy, assess, and compare across homegrown, open-source, and third-party algorithms. All models are tightly integrated with end-to-end platform capabilities, ranging from feature curation and health checks to model management to inference/serving to outcome monitoring.

  • Faster feedback loops. AI/ML models rarely work on a "set it and forget it" basis.  integrates the full model lifecycle with end user actions and feedback, and with operational decisions and outcomes. This enables operationally oriented model monitoring, management, understanding, selection, and adjustment. The result is more adaptable and ambitious AI/ML, faster.

UNITE THE ORGANIZATION AROUND A SHARED ENVIRONMENT FOR MACHINE LEARNING.

The most effective AI/ML encodes and supercharges an organization's unique expertise. That requires uniting an organization's data scientists, decision-makers, and everyday employees in an environment for collaborating on AI/ML-powered operations.  collaboration infrastructure drives AI/ML that brings the organization together:

  • A unifying ontology. ontology translates an organization's complex data landscape into human-readable concepts. built models reflect how an organization views the world and unite data scientists, engineers, analysts, executives, and operational end users around a common semantic layer.

  • Granular security controls. lets organizations define granular access control policies at the integration stage, then propagates those policies intelligently across the system. Organizations can promote collaboration confidently with granular data security and transparent data governance.

  • Model templates.model templates empower low-code and no-code AI/ML so even non-technical users can use AI to accelerate and enrich their workflows.

MAXIMIZE IMPACT AND MINIMIZE RISK WITH A PLATFORM DESIGNED FOR RESPONSIBLE ENGINEERING.

Our approach to AI/ML in  reflects our foundational belief in augmenting human intelligence, not replacing it. We believe AI/ML algorithms are most effective when they empower humans to ask complex questions, interpret answers, and act on results. At public and private sector organizations around the world, driven AI/ML is accelerating human decision-making by:

  • Surfacing new leads in dark web, weapons trafficking, financial fraud, and drug trafficking investigations so investigators can identify persons of interest more quickly

  • Aggregating and correlating biomedical research data to streamline drug discovery

  • Processing entity resolution suggestions so analysts can focus on making assessments rather than manually sorting and tagging data

  • Analyzing massive-scale sensor data so that engineers can make better aircraft maintenance decisions

  • Rapidly generating simulations while allowing operators to tweak scenario variables, leading to better-informed decisions optimized for different variables (e.g., safety rating and production quantity)

I see our approach to ethical machine learning as being grounded in an appreciation for both the promise and limitations of human-computer collaboration. The promise of AI is in augmenting and enhancing human intelligence, expertise and experience. Think helping a aircraft mechanic make better, more accurate and more timely repairs – not automating the mechanic out of the picture.

— Anthony Bak, Co-Lead of Palantir's Machine Learning team, in an interview with CTOVision

Protecting privacy and preserving civil liberties is fundamental to our mission.ships with technical capabilities that enable ethical engineering and ethical machine learning, including data protection features such as granular access controls, data provenance and lineage tracking, data retention and deletion management, and audit logging.  also enables industry-leading monitoring and validation for AI models. Its flexible, configurable tools let organizations evaluate model bias, in terms of both the data used to train the model and model outcomes.

We recognize that technology alone can't fully mitigate the risks of machine bias. Our dedicated Privacy and Civil Liberties team works with our engineers and our customers to approach building and deploying AI/ML thoughtfully.

使人们更加自由和快乐。任何场合,任何机会创建一个可以获取各种可能性的社会。专注于技术和愿景这是一家明显改变社会的公司。

Make people more free and happy.
Any occasion and any opportunity
Create a society where you can access the possibilities.
Focusing on technology and vision
It is a company that clearly changes society.

在地球上工作
全面的远程工作总计1000人或以上
“在任何地方工作和生活”
创建一个可以使人们摆脱地方困扰并追求其潜力和价值的世界。
通过产品(Virtual Office SaaS)和Slack,总共有100多人进行协作。
这是一家以世界为目标的科技公司,在未来创造世界的未来。

Working on earth
Full remote work total 1000 people or more
"Work and live anywhere"
Create a world where people can be freed from places and pursue their potential and value.
Over 100 people in total collaborate through their products (Virtual Office SaaS) and Slack.
It is a technology company aiming at the world from China, creating the future of the world in the future.

 

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Company

会社情報

Company profile

会社概要

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China
会社名

哈牛桥智能科技集团

HOC Intelligent Technology GROUP

所在地

邮编210094中国南京市江北新区星火路17号创智大厦801室-845

Room 801, Chuangzhi Building, No. 17 Xinghuo Road, Jiangbei New District, Nanjing, China

設立

2019年7月

代表者名

Yuhonghong于红红, GuoLong国龙

董事会:于红红

执行官:国龙

执行官:多原精钢

业务      AI, IoT, Internet of Things, RPA, OCR-AI, ERP, cloud, bigdata, blockchain, ICT, 5G, 3D, AR, VR, iCLIP, core industrial software, smart chips, smart driving, core algorithms, neutrinos, quantum Top cutting-edge technologies such as computing, artificial intelligence, robotics and automation systems, smartphones and cloud computing, and smart cities.,这些核心技术全部来自于自主研发,拥有自主知识产权。 AI自然语言处理有关的商业活动研发

提供AI服务解决方案

AI课程

开发咨询

开户行    中国银行 三井住友銀行 三菱銀行 楽天銀行

Our Partners

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CEO message

社长致辞

Yuhonghong       GuoLong

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HOCIT Co.,Ltd.总裁于红红 员工700多人所有远程工作,工作方式改革实施公司
HOCIT Co.,Ltd.总裁于红红 员工700多人所有远程工作,工作方式改革实施公司
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哈牛桥智能科技有限公司(以下简称哈牛桥)是一家“AI医疗互联网平台运营商”,公司成立于2019年,历史可回溯,总部位于南京,杭州。上海,沈阳研发中心。 
      在国内,哈牛桥率先提出了“AI医疗”概念并自主研发了基于云计算的协同医疗平台及相关服务,为“基层首诊、双向转诊、急慢分治、上下联动”的分级诊疗模式提供高性价比的专业解决方案,切实缓解百姓“看病难、看病贵”的难题,促进优质医疗资源下沉,推动医疗资源均衡配置,提升医疗、健康服务可及性,使广大百姓受益。

公司使命

 

使命:让科技普惠大众健康

 

愿景:成为中国基层医疗最具影响力的互联网平台运营商

 

 

业务范畴

公司经营互联网医疗业务,定位于“AI医疗互联网平台运营商”,致力于改善中国基层医疗,武装基层医生,努力成为对健康中国有价值贡献的组织。

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软件企业

红十字荣誉证书

浦东新区企业技术研发机构

浦东新区高技术服务企业

CMM5认证

ISO9001:2020质量管理体系认证证书

文化和价值观

人核心价值观:      分享、诚信、创新、坚持

历史及里程碑

  • 2020年

公司承建的“AI医疗建设项目”获得国家卫生计生委“全国基层卫生信息化应用创新大赛优秀奖”互联网+医疗精准扶贫及分级诊疗”项目,IEEE Award ,ACM Award

2019年

公司建设的全国首家基层“互联网+分级诊疗”服务中心运营

首创“互联网+医疗精准扶贫”模式

入选全国基层医疗投资机遇关注企业

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