Systems | Development | Analytics | API | Testing

Across the industry, organizations are attempting to find ways to implement generative AI in their business and operations. But doing so requires significant engineering, quality data and overcoming risks. In this blog post, we show all the elements and practices you need to to take to productize LLMs and generative AI. You can watch the full talk this blog post is based on, which took place at ODSC West 2023, here.

The rise of AI and LLMs in our world is revolutionizing the applications we’re building and the customer experiences we’re delivering. This is one of the pivotal moments in our industry where we cross over an intersection in our technology evolution to enter a new journey with a paradigm shift. Past intersections were the rise of mobile, the rise of the cloud, and the rise of microservices, among others. Some people may even say that AI is as revolutionary as the birth of the internet.

The goal of any mobile product is to create an app experience that’s innovative and new. But you must accomplish specific, necessary steps between crafting a clear vision for your app and creating a mobile application. As explained in our step-by-step mobile application testing process, it’s imperative to understand and resolve any requirement contradictions before finalizing the development phase.

Microservices architecture has gained significant traction due to its ability to break down monolithic applications into smaller, independently deployable services. However, the benefits have often been lop-sided. While backend developers have realized numerous advantages, frontend adoption has been held back by tight coupling, slow development cycles and scalability issues. Microfrontends have emerged as a solution to these challenges by applying microservices principles to the frontend.

Recently at re:Invent, Amazon unveiled S3 Express One Zone for AWS. Express Zone for S3 responds to the demand for faster analytical query speeds, with the convenience of centrally storing all of your application telemetry data in cloud object storage. In the past, for data-intensive applications, data access speeds were slower than desired.

Looking for a managed PostgreSQL database with a free tier? We've got you covered. In this article, we'll explore the top PostgreSQL databases with free tiers to use for your applications in 2024. These free-tier options are perfect for side projects, MVPs, and learning how to use cloud databases. All these database solutions integrate with Koyeb, enabling you to seamlessly connect databases hosted by third-party providers to your applications running on the Koyeb platform.

Generative AI was undoubtedly the most important data moment of 2023, and created a level of excitement for our industry that will certainly continue to be felt in 2024. As we welcome the new year, I am thrilled to share that Qlik is hitting the ground running on that front: today we are announcing the acquisition of groundbreaking technology from Kyndi, an innovator in natural language processing, search, and generative AI.

Integrating Artificial Intelligence (AI) in software testing is a major advancement in software development, enhancing efficiency and accuracy while handling complex scenarios. This technological leap introduces significant ethical challenges, such as concerns over data misuse and the need for algorithmic transparency. Understanding and addressing these issues is crucial for fostering responsible innovation in AI.