The world of AI and machine learning is moving at breakneck speed, with new papers, models, benchmarks, and frameworks announced daily. If you have ever felt overwhelmed, behind, or simply exhausted trying to keep up, you are not alone. In this talk, we share our own journey grappling with AI fatigue, what it feels like, why it happens, and what we have learned about staying informed without burning out.

We will start by defining AI fatigue and reflecting on why it is such a pervasive experience in our community, from social media hype to the sheer pace of real innovation. We highlight some of the common pitfalls, like chasing every trend, consuming too much noise, or neglecting mental health, and show why these approaches are counterproductive.

Then, we focus on actionable strategies and habits that actually work. We share concrete tips and techniques we personally use to manage our learning and maintain our enthusiasm for the field, including:

• Crafting an intentional information diet with trusted sources
• Setting clear boundaries and time boxing your learning
• Building a personal knowledge base for long term retention
• Using summarization tools to cut through dense papers and blogs
• Practicing “JOMO,” the joy of missing out, by focusing on depth over breadth
• Learning in public by teaching, blogging, or pairing with others
• Designing small, achievable experiments to stay engaged and motivated

Finally, we will suggest how organizations and teams can help prevent fatigue at a structural level by fostering focus, psychological safety, and curiosity instead of always on urgency.

This talk is for anyone, from beginner to expert, who wants to stay relevant and curious about AI without losing sight of their well being. You will leave with a set of practical tools, a fresh perspective on learning in a chaotic environment, and hopefully the reassurance that it is okay to not know everything.