Centaur Labs Secures $16M in Series B Funding to Help Health and Scientific Organizations Accelerate AI DevelopmentBOSTON, Mass., October 9, 2024-- Centaur Labs, a leader in health data annotation, today announced the successful completion of a $16M+ oversubscribed Series B funding round led by SignalFire, with additional participation from Matrix, Susa Ventures and new investors Samsung Next and Alumni Ventures.

2024年10月9日，半人马实验室（Centaur Labs）获得了1600万美元的B系列资金，以帮助健康和科学组织加速人工智能的发展。马萨诸塞州波士顿——半人马实验室（Centaur Labs）是健康数据注释领域的领军者，今天宣布成功完成了由SignalFire牵头的1600多万美元超额认购的B系列资金，Matrix、Susa Ventures和新投资者三星Next和校友Ventures也参与了这轮融资。

In addition, Centaur Labs launched its on-demand AI data labeling product, which enables AI developers to collect labels from experts in less than one hour..

此外，半人马实验室推出了按需人工智能数据标签产品，使人工智能开发人员能够在不到一小时的时间内从专家那里收集标签。。

Funding will enhance health data labeling solution

资金将增强健康数据标签解决方案

While approximately 30% of the world's data is generated by the healthcare industry, the majority of it is unstructured or poorly annotated. As AI and analytics play an increasingly large role in healthcare, the consequences for bad quality inputs or outputs grow. Many organizations struggle with the scalability, quality, and speed of data annotation necessary for model training and evaluation in healthcare, facing challenges such as low quality, management burdens, and difficulty sourcing skilled annotators.

虽然世界上大约30%的数据是由医疗保健行业生成的，但其中大多数是非结构化的或注释不佳的。随着人工智能和分析在医疗保健中发挥越来越大的作用，质量差的输入或输出的后果越来越严重。许多组织都在为医疗保健中的模型培训和评估所必需的数据注释的可扩展性、质量和速度而斗争，面临着诸如质量低、管理负担重以及难以找到熟练注释员等挑战。

Generative AI models specifically can create an enormous volume of possible outputs, and it is up to humans to review those outputs for both factual accuracy (i.e., quality control) and preferred phrasing and framing of content (i.e., human preferences)..

生成性人工智能模型特别可以产生大量可能的输出，这取决于人类如何审查这些输出的事实准确性（即质量控制）以及内容的首选措辞和框架（即人类偏好）。。

Centaur Labs helps health and science organizations accelerate AI development by using its network of over 50,000 experts to label multimodal data for model training, evaluation, monitoring, and feedback. Experts compete to be the best annotators on the company's mobile app, DiagnosUs, ensuring only the most skilled annotators contribute to the data.

半人马实验室通过使用其超过50000名专家的网络为模型训练、评估、监控和反馈标记多模式数据，帮助健康和科学组织加速AI开发。专家们争相成为该公司移动应用程序DiagnosUs上最好的注释者，确保只有最熟练的注释者才能为数据做出贡献。

As a result, Centaur Labs delivers greater accuracy and faster annotations relative to in-house teams or outsourced generalists - all on a HIPAA-compliant platform..

因此，相对于内部团队或外包的多面手，半人马实验室提供了更高的准确性和更快的注释-所有这些都在符合HIPAA的平台上。。

'In healthcare, where AI hallucinations can cost lives, 'garbage in, garbage out' data problems are unacceptable and models need to be ongoingly evaluated and monitored once they're deployed,' said Erik Duhaime, CEO of Centaur Labs. 'We see a future where AI, continuously refined by human expertise in real time, powers scientific breakthroughs and improves human health.

半人马实验室（Centaur Labs）首席执行官埃里克·杜哈伊姆（ErikDuhaime）说，在医疗保健领域，人工智能幻觉可能会夺去生命，“垃圾输入、垃圾输出”的数据问题是不可接受的，模型一旦部署，就需要不断进行评估和监控我们看到了一个未来，人工智能通过人类实时专业知识不断改进，推动科学突破，改善人类健康。

This funding will allow us to build toward that future, further scaling operations and accelerating product development to ensure healthcare and AI companies can get medical data annotated with the quality, speed, and scale they need.'.

这笔资金将使我们能够朝着这个未来发展，进一步扩大运营规模，加速产品开发，以确保医疗保健和人工智能公司能够获得他们所需的质量、速度和规模的医疗数据。”。

'AI is radically transforming the U.S. healthcare industry, creating both immense opportunities and risk. Unlike other solutions out in the market today, Centaur Labs has found a way to deliver the scalability, affordability and accuracy needed to power AI models for medical devices, diagnosis tools, chatbots, drug discovery, and more.

人工智能正在彻底改变美国医疗保健行业，创造巨大的机会和风险。与目前市场上的其他解决方案不同，半人马实验室已经找到了一种方法，可以提供为医疗设备、诊断工具、聊天机器人、药物发现等提供AI模型所需的可扩展性、可负担性和准确性。

We're thrilled to support Erik and the Centaur Labs team as they unlock the next wave of AI-powered health innovation,' said SignalFire Partner Yuanling Yuan..

。。

Today, the company collaborates with AI leaders from startups to enterprises, with customers reporting up to 20X ROI from annotation speed improvement and the thousands of hours saved in data annotation tasks. Clients span the healthcare ecosystem and include industry leaders such as Massachusetts General Hospital, Memorial Sloan Kettering, Eight Sleep, Scibite from Elsevier, Activ Surgical, and Medtronic among others..

。客户遍布医疗保健生态系统，包括行业领导者，如马萨诸塞州总医院、纪念斯隆·凯特琳、八睡眠、爱思唯尔的Scibite、Activ Surgical和美敦力等。。

For example, Centaur Labs recently collaborated with Eight Sleep to advance the company's snore detection algorithm by crowd annotating complex spectrograms and chest vibration waveforms to enable Eight Sleep's Snore Detection model, boosting the model accuracy from 70% to 93%. John Maidens, Machine Learning Lead at Eight Sleep said, 'The Centaur Labs platform helped us deliver this snoring model quickly.

例如，半人马实验室最近与八睡眠公司合作，通过对复杂频谱图和胸部振动波形进行人群注释来改进公司的鼾声检测算法，从而实现八睡眠公司的鼾声检测模型，将模型精度从70%提高到93%。八睡眠时机器学习负责人约翰·梅德斯（JohnMaidens）说，“半人马实验室平台帮助我们快速交付了这种打鼾模型。

We went from conception to in front of customers in under a year, which is very quick for a biosignal AI.'.

我们在不到一年的时间里从概念到客户面前，这对于生物信号人工智能来说是非常迅速的。”。

Launch of on-demand model monitoring, powered by experts at scale

启动按需模型监控，由规模专家提供支持

Alongside the funding announcement, Centaur Labs will be alpha launching its on-demand data labeling platform. This new offering promises to deliver the fastest data labeling in the industry, with capabilities to serve urgent use cases in hours instead of weeks.

在资金宣布的同时，半人马实验室将推出其按需数据标记平台。这一新产品有望提供业界最快的数据标签，能够在数小时而不是数周内为紧急用例提供服务。

This launch is in response to the growing need for AI teams to integrate Centaur Labs 'annotations into their data pipeline, and see a label turnaround on a daily or hourly basis for use cases like model monitoring. The on demand labeling platform will derisk healthcare AI in production and allow AI teams to identify opportunities to improve and catch high-priority failures before they have a negative impact.

此次发布是为了应对人工智能团队日益增长的需求，即将半人马实验室的注释集成到他们的数据管道中，并看到每天或每小时的标签周转，以用于模型监控等用例。按需标签平台将嘲笑生产中的医疗保健人工智能，并允许人工智能团队在产生负面影响之前发现改进和捕捉高优先级故障的机会。

AI teams can load simple instructions and a single piece of data that - with the push of a button - is broadcast to Centaur's entire network of annotators and receives 20-30 annotator reads in less than 30 minutes versus days..

人工智能团队可以加载简单的指令和一段数据，只需按下一个按钮，就可以将其广播到半人马座的整个注释器网络，并在不到30分钟的时间内（而不是几天内）接收20-30条注释器读数。。

About Centaur Labs

关于半人马实验室

Centaur Labs annotates medical and scientific data at scale, helping AI developers to build, monitor, and validate their models. We offer a secure, HIPAA compliant annotation platform that supports annotation of multiple data types, as well as annotation services from our network of subject matter experts who provide millions of annotations weekly.

半人马实验室大规模注释医学和科学数据，帮助人工智能开发人员构建、监控和验证他们的模型。我们提供了一个安全、符合HIPAA的注释平台，支持多种数据类型的注释，以及我们每周提供数百万注释的主题专家网络的注释服务。

Our platform leverages competition and performance-based incentives to ensure annotator skill and motivation, and intelligently combines the opinions of multiple people to generate the highest quality annotations. In addition, Centaur Labs partners closely with researchers at leading institutions all over the world to advance the field of AI in the medical and life sciences and has been published in publications such as Nature Digital Medicine..

我们的平台利用竞争和基于绩效的激励机制来确保注释者的技能和动机，并智能地结合多个人的意见来生成最高质量的注释。此外，半人马实验室与世界各地领先机构的研究人员密切合作，推动人工智能在医学和生命科学领域的发展，并已在《自然数字医学》等出版物上发表。。

For more information, visit Centaur Labs or follow us on Twitter and LinkedIn.Contact:

有关更多信息，请访问半人马实验室或在Twitter和LinkedIn上关注我们。联系人：

Ali Devaney

阿里·德瓦尼

Director of Product and Brand Marketing

产品和品牌营销总监

ali@centaurlabs.com

ali@centaurlabs.com