From Data Collection to Adoption: How Humans Help Medical AI Come to Life

From Data Collection to Adoption: How Humans Help Medical AI Come to Life

From data collection to training and deploying working models, the development of medical AI comes with many important challenges and opportunities.

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Optimizing Decision Making by Combining Automation and People

Optimizing Decision Making by Combining Automation and People

An incremental design approach to automation and machine learning affords strategic opportunities for choosing to route exceptions to machines or people.

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4 Reasons You Should Outsource Data Entry

4 Reasons You Should Outsource Data Entry

Data entry is a crucial part of any digital transformation project. Sometimes it makes more sense to outsource than to burden your own team.

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Choosing a Data Labeling Service Part 2: Communication & Quality Control

Choosing a Data Labeling Service Part 2: Communication & Quality Control

How can you determine if a data labeling service will deliver quality work? How they communicate and handle quality control are key indicators.

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Choosing a Data Labeling Service Part 1: Hiring and Vetting

Choosing a Data Labeling Service Part 1: Hiring and Vetting

How can you determine if a data labeling service will deliver quality work? It starts with their vetting, hiring, and training processes.

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What Can We Learn From HR About AI Bias?

What Can We Learn From HR About AI Bias?

People have unconscious biases that affect hiring decisions. People also can hard-code their biases into an AI system. Humans in the loop can help.

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3 Ways Humans in the Loop Add Value to the AI Lifecycle

3 Ways Humans in the Loop Add Value to the AI Lifecycle

Humans play a critical role throughout the AI lifecycle, from data cleaning and labeling to quality control and automation monitoring.

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Accelerating ML Model Development with Human in the Loop

Accelerating ML Model Development with Human in the Loop

Developing ML models requires a lot of data and skilled people to work with it. Here’s our HITL approach for machine learning model development.

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From Meals to Video: Connecting a Remote, Global Workforce

From Meals to Video: Connecting a Remote, Global Workforce

Building and maintaining relationships while working remotely calls for creativity. We use pod socials to connect globally at CloudFactory.

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Five Great Books about AI and Machine Learning

Five Great Books about AI and Machine Learning

Whether you’re a seasoned pro or new to artificial intelligence, continued learning important. Here are a few of our favorite machine learning & AI books.

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Partnering to Achieve an Adaptive Workforce

Partnering to Achieve an Adaptive Workforce

Some organizations are winning in a pandemic by adapting to changing customer and market demands. We’ve provided adaptive workforces for a decade. Here’s what they look like.

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4 Essentials for the Data Labeling Pipeline

4 Essentials for the Data Labeling Pipeline

Supervised learning requires a lot of labeled data. Here’s what it takes to design a high-performance data labeling pipeline for machine learning.

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Boiling the Ocean: Processing the Data that Powers AI

Boiling the Ocean: Processing the Data that Powers AI

Even in uncertain times, you’re swimming in an ocean of data. If you’re using AI, how you process and use that data will determine the future of your business.

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Crowdsourced Workers vs. Managed Workers [Infographic]

Crowdsourced Workers vs. Managed Workers [Infographic]

Data scientists at Hivemind created 3 data labeling tasks and hired 2 teams to complete them. The differences in data accuracy, speed, and cost may surprise you.

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5 Qualities in Good Data Labeling Vendors [Infographic]

5 Qualities in Good Data Labeling Vendors [Infographic]

Not all outsourced data labeling partners are a good fit for every AI project. Here are 5 things you need to consider before, during, and after vendor evaluations.

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Top Benefits and Limitations of Auto Labeling

Top Benefits and Limitations of Auto Labeling

The data annotation. One emerging feature is automation, also known as pre-annotation or auto labeling. This article will focus on some of its benefits and drawbacks.

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