We are collectively thrilled to share some exciting news: Qwak will be joining the JFrog family! Nearly four years ago, Qwak was founded with the vision to empower Machine Learning (ML) engineers to drive real impact with their ML-based products and achieve meaningful business results. Our mission has always been to accelerate, scale, and secure the delivery of ML applications.

In today’s digital landscape, IT operations face unique challenges and pressures unlike those of the past. Currently, the cost of a service failure for medium and large enterprises is estimated to exceed $100,000 per hour. At present high incident management costs, coupled with the impact on customer satisfaction, present significant challenges for enterprises. To resolve this challenge AI and ML assists in enhancing the overall management of incidents and reducing response times.

For 20 years, Ubuntu has been at the cutting edge of technology. Pioneers looking to innovate new technologies and ideas choose Ubuntu as the medium to do it, whether they’re building devices for space, deploying a fleet of robots or building up financial infrastructure. The rise of machine learning is no exception and has encouraged people to develop their models on Ubuntu at different scales.

I married into a family of geologists and rock and gem enthusiasts, and that bit of serendipity has added immensely to my life. Whenever we go on family hike excursions, I learn so much more about the landscape than I could have ever hoped to from my own educational path, and as a bonus my home gets adorned with tastefully and expertly chosen specimens from around the world.

If you haven’t already read part 1, click here to do that first. If you look at the screenshots, they’re actually quite simple to understand. Anyone can easily identify whether the OS booted successfully at first glance. Look at the following examples and you’ll see what I mean : So, rather than the existing deterministic method, which relied on indirect evidence, we opted to use machine learning and neural networks to analyze and classify screenshots like a human being.

Over the next three blogs, I want to explain how we used machine learning to increase Cove Continuity boot-check accuracy to 99%. Cove Continuity offers the ability to restore source (protected) servers/workstations to virtual machines (VMs) in Hyper-V, ESXi, or Azure. After a VM is restored, Cove performs a boot-check test to prove that the system was properly restored.

Data is at the heart of all machine learning (ML) initiatives – and bad actors know it. As AI continues to occupy the limelight of modern tech discourse, ML systems are becoming increasingly attractive targets for attack. With the Identity Theft Resource Center reporting a 72% spike in data breaches in 2023, it’s critical to take the proper precautions to ensure your ML projects don’t provide a back door to your data.