CloudFactory Blog

Realizing AI’s potential benefits - and mitigating its challenges - will require collaboration. As partnerships form and critical questions arise across the globe in government, ...

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 ...

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 ...

Given the challenges of hiring and managing a team to complete the arduous data work behind AI, many companies are turning to outside help.

AI innovators rely on external teams to structure data for ML algorithms. But scaling quality data requires the right people & processes in your tech stack.

AI is only as good as the data it's trained to analyze. CloudFactory CEO Mark Sears shares in Forbes about how AI bias can arise from people, tools, algorithms, and human ...

Our latest infographic takes a closer look at the data scientist, who extracts knowledge, insights, or solutions from big data.

Even before the Facebook–Cambridge Analytica story broke, the World Economic Forum proposed the need for a new era of data responsibility. Here’s how we can contribute to a world ...

CloudFactory CRO Mike Riegel spoke about machine learning innovation as a panelist for Google I/O Extended, part of a three-day global conference for developers.

We are sponsoring the “Best AI Startup” category for the fifth annual AIconics Awards, to be held June 12 at Kensington Palace.

Data cleansing is a growing priority for businesses around the globe. Here's how to build a foundation for clean-data success.

Our latest SlideShare provides details on your workforce options and shares best practices for choosing your AI workforce.

We look at the leading causes of dirty data, which research shows is the most common problem for people who work with data.

Explore the benefits of data, how businesses are using it, and three kinds of data challenges that companies frequently run into.

Why is artificial intelligence just now taking off? These three forces are fueling AI techniques to build real-life applications.

Some believe cloud robotics will be the future of AI and the next big disruptor in business.