For over a century, Goldman Sachs has been one of the most recognizable names in multinational investment banking and financial services. When they speak, the market listens. So what does Goldman Sachs have to say about APIs and AI when it comes to serving its clients and fueling business success? Kong had a chance to ask these questions to Rohan Deshpande, Managing Director at the company, at API Summit 2024.

The software testing market size was valued at USD 51.8 billion in 2023 and is projected to grow at a CAGR (Compound Annual Growth Rate) of over 7% between 2024 and 2032.

Part 1 of this two-part blog serves as the foundation, highlighting the critical role that quality engineering (QE) must play in addressing the business risks associated with the accelerating adoption of artificial intelligence or AI-powered software.

I'm pretty fast on my laptop keyboard, usually typing around 60 words per minute, sometimes even more, thanks to my mom. She signed me up for a typing course when I was 12 because she thought it would be useful for my career someday, years before I could get my hands on a real computer. It turns out she was right, and it's still a handy skill today. When I graduated from the typing course, my mom gifted me an Olivetti typewriter. It was amazing at the time!

If you're worried about the potential for heightened regulatory scrutiny in financial services, you're not alone. Business operations teams everywhere are focused on the end-to-end, client lifecycle management (CLM) process as they cope with ever-changing regulations governing how, when, and where client data can be stored and accessed. It's hard to stay compliant when customer data is spread across multiple operational silos.

Information extraction (IE) finds its roots in the early development of natural language processing (NLP) and artificial intelligence (AI), when the focus was still on rule-based systems that relied on hand-crafted linguistic instructions to extract specific information from text. Over time, organizations shifted to techniques like deep learning and recurrent neural networks (RNN) to improve the accuracy of information extraction systems.

Combining Artificial Intelligence and human intelligence in testing becameessential for delivering high-quality products quickly and efficiently. AI excels at automating repetitive tasks, analyzing vast datasets, and improving test coverage. Humans, on the other hand, bring creativity, critical thinking, and the ability to handle complex scenarios that machines can’t easily navigate. Together, they form a powerful synergy that enhances speed and accuracy in testing but also brings challenges..

Kubernetes has revolutionized how modern applications are built, deployed, and scaled. However, due to its complexity, managing a Kubernetes development environment can sometimes feel overwhelming for developers. Utilizing a cloud environment can simplify Kubernetes development by providing better scalability, manageability of dependencies, and a more consistent development experience across various cloud providers.

Many business processes involve communicating with external parties such as suppliers, logistics providers, insurance providers, and government institutions. Unlike internal communications, these inter-organizational communications usually have to follow various regulations and standards, and could introduce delays if one party doesn’t comply. Therefore, effective business-to-business (B2B) integrations are a key part of most digital transformation projects.

Continuous integration (CI) pipelines are an important part of building and deploying reliable software. Whether it's building a Docker image, running tests, or even just doing code linting, CI pipelines help you automate repetitive tasks and ship better code even faster. GitHub Actions lets you create pipelines to build containers, test source code, and publish software.