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Deploy realtime GraphQL APIs in minutes with Qovery and Hasura

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.

Edge AI in a 5G world - part 4: How your business can benefit from 'smart cell towers'

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.

Edge AI in a 5G world - part 3: Why 'smart cell towers' matter to AI

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.

Feature importance for data frame analytics with Elastic machine learning

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.

The DevOps guide to IoT projects

Traditional development methods do not scale into the IoT sphere. Strong inter-dependencies and blurred boundaries among components in the edge device stack result in fragmentation, slow updates, security issues, increased cost, and reduced reliability of platforms. This reality places a major strain on IoT players who need to contend with varying cycles and priorities in the development stack, limiting their flexibility to innovate and introduce changes into their products, both on the hardware and software sides.

Getting started with AI

From the smallest startups to the largest enterprises alike, organisations are using Artificial Intelligence and Machine Learning to make the best, fastest, most informed decisions to overcome their biggest business challenges. But with AI/ML complexity spanning infrastructure, operations, resources, modelling and compliance and security, while constantly innovating, many organizations are left unsure how to capture their data and get started on delivering AI technologies and methodologies.