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Five worthy reads: The future of tech is clean

Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. In this edition, we are exploring the emerging market for climate technology, exploring their significance, and addressing why a successful path forward lies in embracing clean, green, and planet-friendly solutions for both startups and established companies. Let’s dive right in.

ML for software engineers ft. Gideon Mendels of Comet ML

In this episode, Rob explores the fascinating crossroads of machine learning and software engineering with Gideon Mendels, the co-founder and CEO of Comet ML. Gideon navigates the often ambiguous world of training ML models, focusing on building a common language between software engineers and data science teams. Gain valuable insights into fostering mutual understanding between these two disciplines and aligning the possibilities of ML with organizational needs in this thought-provoking episode.

New Features: AI-assisted postmortems, ilert Terraform updates, and expanded ChatOps capabilities

In incident management, staying ahead of the curve is crucial, and that's what we're doing with our latest suite of features designed to streamline your workflow and enhance your response capabilities. Furthermore, you have provided numerous excellent suggestions during this period. We value your feedback and invite you to reach out to us at support@ilert.com to share your experiences with ilert.

Introducing the Functional Source License: Freedom without Free-riding

Sentry started life in 2008 as an unlicensed, 71-line Django plugin. The next year we began publishing it under BSD-3, and ten years later we switched to the Business Source License (BSL or BUSL). Last year we purchased Codecov, and a few months ago we published it under BSL/BUSL as well. That led to some vigorous debate because of our use of the term “Open Source” to describe Codecov, from which emerged this helpful suggestion from Adam Jacob, co-founder of Chef.

Managing Apple Devices in N-central is Now Better Than Ever

It’s not uncommon to find with remote monitoring and management solutions that the functionality they offer around Apple device management lies a very distant second to that offered for Windows devices. N-central has long been a leading RMM solution, and it too has had its deficiencies when it comes to Apple device management.

Does Tracealyzer fit into my project?

Every developer wants universally applicable tools for their embedded development. However, hardware (processor type) and software (RTOS) architecture can limit the choice, making it a decision for the second-best rather than the best tool – even if you are in the mainstream. This is one of the reasons why Software Development Kits (SDKs) are becoming increasingly popular – even more so if they are easy to use and deploy.

GenAI in customer experience: Powering the future today

ChatGPT captured our collective imagination when it burst into the mainstream last year, setting off a hype cycle that hasn’t abated. The enterprise is where generative AI (GenAI) will become more than tech’s newest shiny object. GenAI is transforming the way we work, unlocking new efficiencies, driving productivity, and creating employee and customer experiences we never could have imagined. ServiceNow is at the forefront of this transformation.

AI Explainer: What Are Neural Networks?

In a previous blog post, which was a glossary of terms related to artificial intelligence, I included this brief definition of "neural networks": Let’s go a bit deeper on that. Neural networks are a class of artificial intelligence (AI) and machine learning models inspired by the structure and functioning of the human brain. They are a subset of AI techniques that have gained significant popularity due to their ability to learn and make decisions from data.

Find your perfect movie with ClickHouse, vector search, Hugging Face API, and Next.js

Get an introduction to machine learning using Aiven services and the Hugging Face API to recommend movies based on Wikipedia synopses. We'll build a project that uses vector search to find the perfect movie based on user input. We'll use ClickHouse®, a fast open-source column-oriented database, which already supports built-in vector comparison capabilities. To visualize our results, we'll rely on Next.js and to we'll get vector embeddings using some free tools and a HuggingFace model.