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This is about how a cyber security service provider built its log storage and analysis system (LSAS) and realized 3X data writing speed, 7X query execution speed, and visualized management. 

Log Storage and Analysis Platform

In this use case, the LSAS collects system logs from its enterprise users, scans them, and detects viruses. It also provides data management and file-tracking services. 

“There is a saying if we need to do a thing right, we need to do it right the first time, rather than doing things in a way that works now but breaks later :)."

Well, as per this saying, imagine if we are traveling in a forest and we come across a situation where we see there are two different ways to reach your destination, and we might think, well, if we go by either of them, we will reach our destination easily, but what we not know is which way is effective for us and according to our situation, let’s say.

Image Generation AI: Reshaping the Landscape of Creativity, Innovation and Policies

In recent years, the field of artificial intelligence has made astonishing progress and achieved remarkable milestones, and Image processing is one area that has been particularly transformative. With the advent of sophisticated AI models like DALL-E 2, Midjourney, and Imagen, the ability to create stunning and realistic images from mere text descriptions is no longer a distant dream. This groundbreaking technology is rapidly transforming various industries and redefining the boundaries of creativity.

Image Generated on Imagen on Vertex AI by Google using prompt

The rise of Generative Artificial Intelligence (GenAI) has introduced innovative services and cutting-edge tools to automate tasks, optimize processes, and speed up transactions. These benefits make it more enticing for businesses to deploy AI services for their expansion and growth strategies.

One important technological breakthrough that has made this growth possible is the conditional generative adversarial network (CGAN).

My most-used Gen AI trick is the summarization of web pages and documents. Combined with semantic search, summarization means I waste very little time searching for the words and ideas I need when I need them. Summarization has become so important that I now use it as I write to ensure that my key points show up in ML summaries. Unfortunately, it’s a double-edged sword: will reliance on deep learning lead to an embarrassing, expensive, or career-ending mistake because the summary missed something, or worse because the summary hallucinated? 

Fortunately, many years as a technology professional have taught me the value of risk management, and that is the topic of this article: identifying the risks of summarization and the (actually pretty easy) methods of mitigating the risks. 

In this tutorial, you'll learn how to publish images from an ESP32-CAM board to multiple browser clients using MQTT (Message Queuing Telemetry Transport). This setup will enable you to create a platform that functions similarly to a live video stream, viewable by an unlimited number of users.

Prerequisites

Before diving in, make sure you have completed the following prerequisite tutorials:

Thanks to the research team at DORA, we can access a model of technical and cultural capabilities to direct our continuous improvement activity.

The goal isn't to adopt every item like a checklist; it's not a maturity model. Instead, you can use it as a map to find practices and techniques to help you improve based on your current circumstances.

After conducting interviews with hundreds of engineers and engineering managers at Meta, Twitter, and other companies, I noticed common patterns in how candidates approached answering behavioral interview questions. While many candidates performed well on technical dimensions, they often struggled to articulate their work, accomplishments, and challenges in an interview setting, which led to rejections.

This article covers pointers on how to effectively use the widely known STAR format to answer behavioral questions. It addresses common pitfalls and provides illustrative examples to help candidates understand how to use the STAR format to communicate clearly and stand out. This is the framework that has helped me successfully clear Engineering leadership interviews at Databricks, Twitter, Airbnb, Plaid, Notion, Uber, and other companies.

Businesses often struggle to ensure smooth database connections during scaling and upgrades. Frustrations can surface from underused instances after scaling out, disruptions when scaling in, and potential disconnections during upgrades.

While connection pools and long-lived connections offer stability, they can cause issues in fluid environments where databases need to adapt quickly. This leads to increased overhead, wasted resources, and dissatisfied customers.