In the Media
How Synthetic Data Is Boosting AI at Scale
Obtaining the right data is considered the most critical and challenging aspect of developing robust AI systems. However, collecting and labeling vast datasets with millions of elements sourced from the real world is time-consuming and expensive. As a result, those training ML models have started to rely heavily on synthetic data, or data that is artificially generated rather than produced by real-world events.
Read ArticleIs AI a Silver Bullet for our Climate Problems?
Alp developed a brand-new course at Columbia University that explores the intersection of Machine Learning and Climate. Here is what he learned (and taught).
Read ArticleAvoiding the Dangers of Generative AI
Generative AI is generating a lot of interest from both the public and investors. But they are overlooking a fundamental risk.
Read ArticleManufacturing Enters New Year Amid Uncertainty
There are still significant challenges—as well as myriad opportunities—ahead in 2023 and beyond.
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The Future of Manufacturing Technology in 2023

Berk Birand on 2023 Manufacturing Predictions

5 Ways to Improve the Industrial Industry’s Labor Shortage

Big Data Industry Predictions for 2023

Factories Grow Greener, Leaner With the Right AI Software

Digitalization Is More Effective Than Carbon Offsets

How Manufacturers Can Navigate the Supply Chain Crisis

3 Ways the Economic Downturn Will Impact the Supply Chain

How AI Can Aid the Food Industry – And Workers

5 Minutes With Berk Birand, Co-Founder and CEO of Fero Labs

3 Ways Software Can Reduce Carbon Emissions

Artificial Intelligence/Machine Learning Reduces Mistakes and Waste

Startups Apply Artificial Intelligence to Supply Chain Disruptions

18 Ways Supply Chain Digital Twins Streamline Logistics

World Earth Day: How Manufacturers Can Reach Net Zero
