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More than 2,000 developers from around the world participated in our open source bot hackfest, which we hosted on HackerEarth from January 10 through March 2. The goal of the event was to work with our community to create open source chatbots that integrate with Mattermost to accelerate DevOps and DevSecOps workflows, and we received many amazing submissions! We gave away $10,000 in prizes, including $6,000 cash to our top contributors.

Open source software development can have a reputation for abrasive behavior. The search community is a clear counterexample for me, with a culture that emphasizes respect and acceptance. This culture played an important part in my own path to open source development. A little over six years ago, I was a wide-eyed software engineer settling into my first full-time job.

Hasura is an open source engine that connects to your databases & microservices and auto-generates a production-ready GraphQL backend. By using Hasura in conjunction with Qovery, you get a blazing fast, auto-scallable and extensible solution to quickly build your applications.

In part 1 we talked about the industrial applications and benefits that 5G and fast compute at the edge will bring to AI products. In part 2 we went deeper into how you can benefit from this new opportunity. In part 3 we focused on the key technical barriers that 5G and Edge compute remove for AI applications. In this part we will summarise the IoT use cases that can benefit from smart cell towers and how they will help businesses focus their efforts on their key differentiating advantage.

In part 1 we talked about the industrial applications and benefits that 5G and fast compute at the edge will bring to AI products. In part 2 we went deeper into how you can benefit from this new opportunity. In this part we will focus on the key technical barriers that 5G and Edge compute remove for AI applications.

In part 1 we talked about the industrial applications and benefits that 5G and fast compute at the edge will bring to AI products. In this part we will go deeper into how you can benefit from this new opportunity.

With Elasticsearch machine learning one can build regression and classification models for data analysis and inference. Accurate prediction models are often too complex to understand simply by looking at their definition. Using feature importance, introduced in Elastic Stack 7.6, we can now interpret and validate such models.