2024-06-14 –, E105 (capacity 70)
As AI becomes increasingly integrated into our daily lives, implementing robust testing practices is crucial to ensure these systems function as expected.
In this talk, we will examine the challenges of testing AI-powered applications and discuss ways to understand AI systems better, instead of viewing them as black boxes.
Using practical, real word examples, we will explore the unique challenges posed by AI, such as clarity, fairness and robustness and how these factors impact testing strategies. Additionally, we will examine the role of data in AI systems and highlight best practices for ensuring data quality and accuracy.
This talk is ideal for developers, testers, data scientists, and anyone involved in the development of AI-driven applications. Attendees will gain valuable insights into effectively testing AI solutions, enabling them to build trust and mitigate risks in these systems.
Hello, I'm Mohit Gaur, a Software Quality Engineer on the Platform Engineering team at Red Hat.
I'm a lifelong learner, constantly experimenting with new tools and contributing to open-source projects. Sharing knowledge and empowering others to embrace technology's potential fuels my fire. Beyond coding, I find inspiration in brainstorming sessions and stimulating discussions.
So, whether you're looking for a quality engineer, a fellow traveler on the digital frontier, or simply a sounding board for your latest ideas, feel free to connect! My thirst for collaboration and conversation never runs dry.