The United States is investing $500 billion into AI infrastructure, aiming to lead the global AI race. This initiative, backed by OpenAI, SoftBank, and Oracle, focuses on building data centers, chips, and scalable systems. But here's the catch: APIs are the key to making this investment work. APIs are the backbone of this effort, and their success will determine whether this $500 billion gamble pays off.

“AI is amazing at guessing quickly, but it fundamentally can’t reason.” That is a quote from someone I know very well, circa 2022. I wonder what the thought process was; the reasoning that went into that statement. Luckily I don’t have to guess, because that person was me. I made that statement in response to the first rounds of LLMs (GPT3, 3.5, PALM2 etc). It remained a firm conviction of mine through the release of GPT-4o and Anthropic’s latest Claude models.

In today’s interconnected digital world, software development and testing often hinge on APIs and dependent systems. These systems are the backbone of modern applications, but they can also create bottlenecks when they’re unavailable, costly, or challenging to work with. Tricentis API Simulation eliminates these barriers, enabling teams to accelerate development, reduce costs, and deliver high-quality software with confidence.

At Tricentis, we’re committed to making test management smarter, more efficient, and customizable. With the latest release of Tricentis Test Management (TTM) for Jira, we’re introducing new features to enhance your test execution efficiency and provide greater control and visibility. Key updates include unified global and requirement execution progress reporting, greater AI customization across projects, and enhanced test review and execution.

Modern data infrastructure demands tools that scale effortlessly to handle growing volumes and complexity. Trino, an open-source distributed SQL query engine, has emerged as a game-changer for high-speed analytics across diverse environments. Its distributed architecture empowers organizations to query massive datasets across databases, data lakes, and cloud platforms with speed and reliability.

Efficiency is critical in achieving successful releases. Manual updates to test plans, unclear test coverage, and poor traceability lead to delays, missed defects, and wasted resources.

At a high level, API endpoints are like middlemen that let different pieces of software talk to one another. They deal with HTTP requests and move data around — and are therefore essential for today's connected Simple enough. But for those making web APIs, it's necessary to have a deep understanding of how they work and what they do.

Gen AI applications can bring invaluable business value across multiple use cases and verticals. But sometimes it can be beneficial to experience different types of applications that can be created and operationalized with LLMs. Better understanding the potential value can help: In this blog post, we’ve curated the top gen AI demos of AI applications that can be developed with open-source MLRun. Each of these demos can be adapted to a number of industries and customized to specific needs.

Knowing how well your application is performing is just as important as ensuring it doesn’t crash. But what defines “good performance?” How do you know if your app is hitting the mark or falling behind? With SmartBear Insight Hub, you can now use performance targets to set and track specific benchmarks for your application’s performance metrics.

Real-time data has become an essential asset for today’s businesses, and the Asia-Pacific market is no exception. Across competitive industries like finance, travel, and more, data streams and event-driven architectures have become table stakes for leading organizations in the region.