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@laura_garcia shared a post, 48 minutes ago

Software Developer, RELIANOID

Retailers invest millions in digital experiences…

but what happens when the checkout stops working? A recent outage affecting the online services of Tesco has once again sparked an important discussion: how resilient are modern retail platforms? Customers reported failures during some of the most critical moments of the shopping journey: - Checkout..

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@hamzmu shared a link, 9 hours ago

Fellow, Rootly

On-Call Burnout: What Incident Data Doesn’t Show

Incident dashboards measure system health, but rarely show the workload and strain engineers face when responding to alerts. Incident load isn’t only about the number of incidents, but the patterns surrounding them. In this article we explore these patterns and introduce On-Call Health, an open-source tool that analyzes engineering signals to surface early burnout trends, highlighting why incident volume alone isn’t enough and why after-hours interruptions, workload stacking, and long-term trends matter.

https___dev-to-uploads.s3.amazonaws.com_uploads_articles_nv7wk3k0nzlublr1nm43

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GPT (Generative Pre-trained Transformer) is a deep learning model developed by OpenAI that has been pre-trained on massive amounts of text data using unsupervised learning techniques. GPT is designed to generate human-like text in response to prompts, and it is capable of performing a variety of natural language processing tasks, including language translation, summarization, and question-answering. The model is based on the transformer architecture, which allows it to handle long-range dependencies and generate coherent, fluent text. GPT has been used in a wide range of applications, including chatbots, language translation, and content generation.

GPT is a family of language models that have been trained on large amounts of text data using a technique called unsupervised learning. The model is pre-trained on a diverse range of text sources, including books, articles, and web pages, which allows it to capture a broad range of language patterns and styles. Once trained, GPT can be fine-tuned on specific tasks, such as language translation or question-answering, by providing it with task-specific data.

One of the key features of GPT is its ability to generate coherent and fluent text that is indistinguishable from human-generated text. This is achieved by training the model to predict the next word in a sentence given the previous words. GPT also uses a technique called attention, which allows it to focus on relevant parts of the input text when generating a response.

GPT has become increasingly popular in recent years, particularly in the field of natural language processing. The model has been used in a wide range of applications, including chatbots, content generation, and language translation. GPT has also been used to create AI-generated stories, poetry, and even music.