When and Why AI Projects Fail (And How to Avoid It)

When and Why AI Projects Fail (And How to Avoid It)

Melody Ayeli, who reviews AI projects for Toyota’s CIO, shared insights on common AI failure points in a session at AI Summit in San Francisco.

Read More »
Azavea and CloudFactory: Partners on Quality Training Data and Social Impact

Azavea and CloudFactory: Partners on Quality Training Data and Social Impact

Azavea's mission is to create advanced geospatial technology and research for civic and social impact. They interviewed a handful of leading data labeling firms, and studiously ...

Read More »
3 Ingredients for Scaling Quality Data Labeling for Machine Learning

3 Ingredients for Scaling Quality Data Labeling for Machine Learning

Gartner predicts 85% of AI projects will fail. One of the leading reasons is low-quality data labeling. High-performing machine learning algorithms require high-quality data. ...

Read More »
How to Take the Security Risk Out of Outsourcing Your Data Labeling

How to Take the Security Risk Out of Outsourcing Your Data Labeling

When you have massive data to label for machine learning, it makes sense to outsource it. But what happens when your data is sensitive, protected, or private? Here’s a quick ...

Read More »
The One Thing You Need Before Starting Any AI Project

The One Thing You Need Before Starting Any AI Project

After a decade of data work, we’ve learned AI development requires a winning combination of people, technology, and processes. Don’t overlook one important step before beginning ...

Read More »
5 Strategic Steps for Choosing Your Data Labeling Tool

5 Strategic Steps for Choosing Your Data Labeling Tool

Your choices about tooling and workforce will be important factors in your success as you design, test, validate, and deploy any ML model.

Read More »
The 3 Hidden Costs of Crowdsourcing for Data Labeling

The 3 Hidden Costs of Crowdsourcing for Data Labeling

Crowdsourcing seems to offer a cheap option for training machine learning models, but it’s rarely as inexpensive as it seems. Here are some of the hidden costs of the crowd.

Read More »
The New AI Factory Model, Part I: How to Scale Quality Training Data [Transcript]

The New AI Factory Model, Part I: How to Scale Quality Training Data [Transcript]

AI training data operations are a lot like the assembly lines of yesterday’s factories. Data is your raw material, and you have to get it through multiple processing and review ...

Read More »
Scaling Quality Training Data: Best Practices for Your Data Production Line

Scaling Quality Training Data: Best Practices for Your Data Production Line

Your training data operations are like assembly lines: data is your raw material, and you have to get it through production steps to structure it for AI. You need skilled people ...

Read More »
Scaling Quality Training Data: The Hidden Costs of the Crowd

Scaling Quality Training Data: The Hidden Costs of the Crowd

Anonymous crowdsourcing is a common alternative to an in-house team for AI development. It can be a cheap option for training machine learning algorithms but it’s rarely as ...

Read More »