Mona's Blog

Illuminating hard things about AI/ML ops and production monitoring.

Celebrating our growth: Amazing customers, product milestones, and new branding

Picture of Yotam Oren
Yotam Oren Mar 24, 2021 10:18:38 PM
Celebrating our growth: Amazing customers, product milestones, and new branding

It’s hard to believe that it has been almost three months since we turned the page on 2020, filling our hearts with new hope for a better year to come. I am proud to share with you that Mona has come out strong from an unexpected and challenging year. As we take a moment to catch our breath and reflect on our recent accomplishments, I wanted to take a moment and share some updates with you.

Can you solve this $1B challenge with machine learning?

Zack Leiner, Jonathan Bennun Mar 18, 2021 4:45:09 PM
Can you solve this $1B challenge with machine learning?

We’ve just passed the middle of March. For folks worldwide, this means gearing up for autumn or spring festivities and traditions, religious and cultural celebrations like St. Patrick’s Day, as well as more humorous events like Pi Day. For sports fans in the U.S., March is the unofficial month of basketball, and it’s when basketball gets a little crazy. Here’s the story of how sports and basketball connect with passion, madness, analytics, machine learning, and a billion dollars (or potentially at least a few millions).

The best gifts for data scientists

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Jonathan Bennun Dec 15, 2020 12:50:00 PM
The best gifts for data scientists

Looking for a special gift for a data scientist or a data engineer at the office or in your life? You’ve come to the right place then. It’s just so hard to please them! We spent hours crunching data and running experiments with various gift ideas, narrowing the list to some of the best options so you won’t have to. Happy shopping!

Should you use the ML monitoring solution offered by your cloud provider?

Itai Bar Sinai Sep 14, 2020 6:30:00 AM
Should you use the ML monitoring solution offered by your cloud provider?

As AI systems become increasingly ubiquitous in many industries, the need to monitor these systems rises. AI systems, much more than traditional software, are hypersensitive to changes in their data inputs. Consequently, a new class of monitoring solutions has risen at the data and functional level (rather than the infrastructure of application levels). These solutions aim to detect the unique issues that are common in AI systems, namely concept drifts, biases, and more.