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Using Swift as a Backend Technology

Swift is a powerful open source programming language created by Apple in 2014 for the iOS, iPadOS, macOS, watchOS, and tvOS, known for its modern syntax, safety features and fast performance. Designed as a successor to Objective C, Swift has become a hugely popular choice for frontend and mobile app development, and it’s also shaping up to be an excellent choice for server-side development.

Six easy steps to adapt your App icons for Apple's new Dynamic Tinting Feature

At the latest WWDC, Apple unveiled an exciting new feature: dynamic tinting for app icons. This update calls for developers to adjust their app icons to support this functionality, ensuring a more visually consistent experience across iOS. This change is significant for maintaining a seamless user interface, allowing app icons to adapt to various system-wide themes, including dark mode, and providing a cohesive look throughout the operating system.

Risk Mitigation through Generative AI: Safeguarding Revenue against Fraud and Cybersecurity Threats

In today’s digital age, businesses face an ever-increasing array of risks, particularly fraud and cybersecurity threats. McKinsey states, “Cyberattacks will cause $10.5 trillion a year in damage by 2025.” That’s a 300% increase from 2015 levels. These risks can significantly impact a company’s bottom line, reputation, and customer trust.

Announcing AI-Powered API Test Generation in Katalon Studio

It's well known that creating API test cases can be time-consuming and repetitive. Manually adjusting web service requests and verification steps is not only tedious but also prone to errors, especially when dealing with complex systems. Today, we’re thrilled to announce a game-changing feature in Katalon Studio that will revolutionize your testing workflow: AI-powered API test generation from OpenAPI/Swagger specifications.

Running Apache Kafka at the Edge Requires Confluent's Enterprise-Grade Data Streaming Platform

Modern edge computing is transforming industries including manufacturing, healthcare, transportation, defense, retail, energy, and much more—pushing data management to far-reaching data sources to enable connected, low latency operations and enhanced decision making. These new use cases shift workloads to the left—requiring real-time data streaming and processing at the edge, right where the data is generated.

Databricks: Achieve performance and reliability with purpose-built AI

88% of Databricks users surveyed are turning to AI to improve bug-fixing effectiveness (Databricks). Why? Troubleshooting modern data stacks is typically a toilsome and manual process. The good news – data teams that use DataOps practices and tools will be 10 times more productive (Gartner). With this in mind, Unravel is hosting this live event to demonstrate how AI-enabled observability for Databricks’ Data Intelligence Platform helps you proactively achieve performance and reliability.

How to Scale RAG and Build More Accurate LLMs

This article was originally published on The New Stack on June 10, 2024. Retrieval augmented generation (RAG) has emerged as a leading pattern to combat hallucinations and other inaccuracies that affect large language model content generation. However, RAG needs the right data architecture around it to scale effectively and efficiently.

Enhance User Scalability and Response Time | Cigniti's Cloud Performance Testing Services

A prominent utility provider faced challenges with client-facing applications, requiring assessing system capabilities under significant loads. Accommodating 50,000 concurrent users within an infrastructure reliant on SQL and IIS, the need for a robust yet cost-effective load-generation setup became paramount.

Embedded Snowpark Container Services Set RelationalAI's Snowflake Native App on Path for Success

Despite the seemingly nonstop conversation surrounding AI, the data suggests that bringing AI into enterprises is still easier said than done. There’s so much potential and plenty of value to be captured — if you have the right models and tools. Implementing advanced AI today requires a solid data foundation as well as a set of solutions, each demanding its own tools and complex infrastructure.

Manage Resource Utilization and Allocation with ClearML

Written by Noam Wasersprung, Head of Product at ClearML Last month we released the Resource Allocation & Policy Management Center to help teams visualize their compute infrastructure and understand which users have access to what resources. This new feature makes it easy for administrators to visualize their resource policies for enabling workload prioritization across available resources.