Valohai Blog

What started as a fun side project for our developer Magda turned out to be a proud addition to the platform. Valohai can now estimate the carbon emissions of cloud instances. Yay!

Almost any programming language in the world is more powerful than the command line. Why would you even bother doing anything on it? Don't be fooled: the modern command line is rocking like never before!

Suppose you find your projects to be in the gray area between the extremes of delayed and real-time inference where you can go with either one, ask yourself if you can delay. And if you can, you should!

There's a new wave of automation being enabled by the combination of machine learning and smart devices. With the complexity of use cases and amount of devices increasing, we'll have to adopt MLOps practices designed for IoT and edge.

Machine learning comes with new types of risk. We need to minimize the risk by addressing how we develop these algorithms and also how we apply these algorithms in the real world. In this article, we'll look at three ways of mitigating the latter – i.e. output risk.

Mike Del Balso is a familiar name to most in the machine learning community. He's one of the pioneers in the MLOps space and has laid the foundations for operational machine learning at Uber, Google, and most recently, Tecton.

Syngenta is a leading provider of agricultural science and technology focused on seed and crop protection products aiming to improve global food security by enabling millions of farmers to make better use of available resources.

Algorithms have become faster, fancier, and more complex in the past couple of years. Still, they haven't gained as much complexity as the systems around algorithms. In this article, we'll discuss three examples of systems complexity.

Docker isolates the software from all other things on the same system. A program running inside a "spacesuit" generally has no idea it is wearing one and is unaffected by anything happening outside.

People, Processes and Platforms are the foundation for every company looking to be an early-mover in machine learning. Leaders should focus on developing in tandem because unsupported team members will be ineffective and platforms alone can't provide value.

Dependency management is the act of managing all the external pieces that your project relies on. It has the risk profile of a sewage system. When it works, you don't even know it's there, but when it fails, it becomes very painful and almost impossible to ignore.

We're excited to announce Antti Karjalainen to our advisory board. He's the founder of Robocorp, a leader in developer-first RPA. To Valohai, Antti brings his unique perspective on the developer tooling space and go-to-market strategy.

A recent report by Harvard Business Review revealed that the pandemic accelerated the adoption of AI and data-driven innovation. In this article, we set out to explore the top AI trends and predict what we'll see pop in 2022.

Product management is as massive a topic as machine learning so let's start with a fundamental question. When is it worthwhile to develop an AI product? A helpful tool most PMs have seen for this is the Sweet Spot for Innovation that IDEO popularized.

Sometimes it is hard to combine the world of experimenting and the more dev-oriented world of data science with robust pipelines and modular work. This example combines Weights and Biases experiments with Valohai's production pipelines.