I’m often asked if and when fully autonomous testing could become a reality. That’s a topic I love to discuss. But, before delving into that, let’s take a closer look at the two words that make up that term. Autonomous, meaning “without human intervention,” is pretty simple. Testing is more difficult because the investigative, inquisitive … continue reading
AI and machine learning saw several steps forward in 2020, from the first beta of GPT-3, stricter regulation of AI technologies and conversations around algorithmic bias, and strides in AI-assisted development and testing. GPT-3 is a neutral-network-developed language model created by OpenAI. It entered its first private beta in June this year, and OpenAI reported … continue reading
A couple of years ago, there was a lot of hype about using AI and machine learning (ML) in testing, but not a lot to show for it. Today, there are many options that deliver important benefits, not the least of which are reducing the time and costs associated with testing. However, a hands-on evaluation … continue reading
AI and machine learning (ML) are finding their way into more applications and use cases. The software testing vendors are increasingly offering “autonomous” capabilities to help customers become yet more efficient. Those capabilities are especially important for Agile and DevOps teams that need to deliver quality at speed. However, autonomous testing capabilities are relatively new, … continue reading
AI, machine learning, and related technologies are more popular than ever, but when it comes to automated testing, the hype outpaces the reality. While there are a few automated testing solutions that take advantage of AI and perhaps machine learning or deep learning, the level of chatter might lead one to believe that such tools … continue reading
