As can be inferred from their name, foundation models are the foundation upon which developers build AI applications for tasks like language translation, text summarization, sentiment analysis and more. Models such as OpenAI's GPT, Google's Gemini, Meta’s Llama and Anthropic’s Claude, are pre-trained on vast amounts of text data and have the capability to understand and generate human-like language.

Now-a-days the data needs to be shared across different systems and platforms. One of the most common formats for this data exchange is JSON (JavaScript Object Notation). Understanding how to properly handle special characters in JSON is crucial for ensuring data integrity. In this blog, we’ll explore JSON escape and unescape, explain their importance. So let’s get started!

Data management is one of today's most critical business function. Without a solid grasp of what data management entails, organizations can't use data effectively. So, businesses look to ETL developers and data engineers for everything from data processing and management basics to regulatory compliance and the overall processes that help businesses use data to steer organizational decisions.

New apps and products enter the market daily, each undergoing rigorous testing before release. As automated processes advance across various industries, software development is no exception. Many quality assurance (QA) teams heavily invest in automation to handle most of their tests. This ensures repeatable tests are efficiently executed while quality assurance professionals focus on other tasks. With all these advancements, one might wonder: Is manual testing still important? The answer is yes!

In the world of computer science and data transmission, encoding and decoding are fundamental concepts. One of the most commonly used encoding schemes is Base64. This encoding method is widely used in various applications, from email encoding and web data transfer to encoding binary data for storage. So let’s explore more in detail about Base64 decoding, exploring its purpose, how it works, with some practical real life examples.

Is there a formula or approach to estimate how much you should spend on your quality engineering (QE) efforts? Our CEO, Steve Semelsberger, is frequently asked that question in discussions with other leaders. In part II of his quality engineering for CEOs series, Steve guides us through various scenarios and offers a unique approach to calculating your QE spend based on your specific business needs. Read the article now! If you missed part I, you can catch up on it here.

According to Statista, the market for legacy modernization tools might reach $36.86 billion by 2027. This growth signifies an increasing demand for modernization in organizations worldwide. However, the journey towards modernization isn’t always successful. In fact, nearly three out of four organizations fail to modernize legacy systems effectively. The best legacy modernization tools can help your organization overcome these challenges.