Today is Day 3 of Launch Week, and we are excited to announce not just one, but two new regions are generally available to deploy your low-latency AI workloads, full stack applications, APIs, and databases globally! Join us in welcoming Paris and Tokyo to the Koyeb platform and to a growing list of global locations where you can deploy your applications! As of today GA locations now include: Paris , Tokyo , Washington, D.C. , Singapore , and Frankfurt.

According to recent survey data from Cloudera, 88% of companies are already utilizing AI for the tasks of enhancing efficiency in IT processes, improving customer support with chatbots, and leveraging analytics for better decision-making. More and more enterprises are leveraging pre-trained models for various applications, from natural language processing to computer vision. For that reason, Cloudera is evaluating a new line of business: Cloudera Integrated Data and AI Exchange (InDaiX).

As the frenzied hype around generative AI cools off and as we get into the year of ideation, earlier adopters of AI are starting to see the results of initial experimentation. And these conversations are increasingly shifting to a more problem-oriented mentality. A lot of people were understandably swept up in the excitement of all that AI can do, only to find that some use cases were too risky or that those problems could be solved with traditional methods that were less costly.

It’s Day 2 of our Launch Week, and we’re excited to unveil our new networking stack! If you're following us, you know that we're obsessed with performance: we want fast deployments and a speedy network once your apps are live. Long story short: while working on optimizing deployments speed, we hit limitations with our old stack, we decided to revamp everything and built a new networking stack for the platform.

With all of the excitement around Arm’s high performance processors, which are optimized for AI, our team wanted to test how easily ClearML would work with GPUs paired with Arm-based CPU compute when compared to GPUs combined with x86 chips.