Month: March 2025

Recently, our development team faced a new challenge: one of our partners was implementing an access control system using a single-board computer from Forlinx. To meet the existing time constraints for face recognition operations, we decided to port our models to the NPU. What we can say after porting is that the NPU is generally a reliable way to put heavy processing on an edge device. So, our partner needed to detect faces in a video stream and provide 1:1 matching (face verification). To better understand what this means, let's recall the basic face recognition pipeline diagram.

Among the numerous AI products launched at the AWS re:Invent 2024 conference, Amazon S3 Tables might have seemed inconspicuous. However, for database professionals, the emergence of S3 Tables signifies that the era of modular data analytics has arrived. S3 Tables are a special type of S3 Bucket with built-in support for Apache Iceberg. They stand alongside the previously introduced General Purpose Bucket and Directory Bucket, collectively referred to as Table Bucket. This means you can now create a table bucket as easily as you would create a standard S3 Bucket.

In a closely connected world, the Internet of Things (IoT) is already a familiar brand for people. However, the use of such many devices is likely to increase the risk of attack. This is why good patch management is so important. It implies the execution of a set of procedures for acquiring, installing, and supporting operating systems and other software.  In this blog, the issues and opportunities concerning patch management in the IoT are considered. It is illustrated how such a possibility of patch management can minimize risks. 

Remix is a full-stack, open-source web framework that was developed by the creators of the popular React Router library. It focuses on features such as server-side rendering and efficient data loading, and it emphasizes developer experience. Ryan Florence is a co-creator of React Remix and in this episode he speaks with Josh Goldberg about the The post React Remix with Ryan Florence appeared first on Software Engineering Daily.

The exponential growth of data in recent years has improved how businesses operate and make decisions. From small start-ups to large enterprises, organizations across industries are leveraging data to gain competitive advantages, optimize operations, and drive innovation. However, with this data surge comes the challenge of efficiently storing, processing, and retrieving vast amounts of information. While traditional solutions like SQLite and MySQL have their place, modern data platforms like DuckDB, Snowflake, and Databricks are reshaping the landscape of data processing.

When running a process in Salesforce, the first question you should ask is whether to execute it synchronously or asynchronously. If the task can be delayed and doesn't require an immediate result, it's always beneficial to leverage Salesforce's asynchronous processes, as they offer significant advantages to your technical architecture. What Is Asynchronous Processing? Asynchronous processes run in their own thread, allowing the task to complete without keeping the user waiting. Here are the key benefits:

The extract, transform, and load (ETL) process is at the heart of modern data pipelines; it helps migrate and process large amounts of data for analytics, AI apps, and BI (business intelligence) for organizations. Conventional ETL used to be explicitly rule-based, which required tons of manual configurations to handle different data formats.  However, with recent trends of large language models (LLMs), we are starting to see the dawn of transformative AI-driven ETL for data extraction and integration.