Generative AI

In this blog post, we will delve into the journey from the inception of ChatGPT to the emergence of the open-source community and its impact on the ongoing generative AI technology race.

Since the release of ChatGPT by OpenAI, the tech industry has been in a frenzy, playing catch up and assessing the business impacts of AI chatbots.

Copilot has become a major buzzword when it comes to the new functions and features based on Generative AI technologies. These large language models practically spell out the steps to accomplish a task in the manner requested by a user.

GIGO is the idea that, no matter how well written and definitive a computer program or algorithm is, if you feed it bad data the resulting output will be "bad"--i.e., have no useful meaning or, at worst, misleading meaning.

This blog explores the power of customized GPT, prompt engineering, leveraging embeddings, and fascinating use cases.

Is Generative AI A Dud?, NPC Streaming, Deadly AI Recipes and a Deepfake 6.9 Joke By Anne Hathaway

We all know there have been discussions on using Generative AI and the pros and cons this new chapter of technology gives. I want to share how Generative AI may assist QA test engineers in their everyday work.

Can ChatGPT help to test a webpage? Can Chat GPT 4 help us with testing? Could it DO the testing for us?

AI and ML are household terms already. Over the last decade, the proximity of common people to those terms has seen on a steady incline.

Take a look at our most read and shared blog posts from June 2023.

In this second part of the playbook, we focus on system tests for model integration & monitoring and expand on human in the loop — where the system learns from human input to provide a better and safer user experience.

In the first part of our LLM testing playbook we will introduce the concept of a human centered framework that should govern the entire test process for generative AI solutions.