, Titanium [2nd Floor]
In an era where new AI models, benchmarks, and frameworks emerge daily, many of us feel caught in a relentless cycle of catching up, what is called "AI fatigue". This talk dives into the causes and consequences of that fatigue, from information overload and social media hype to the constant pressure to stay relevant. Drawing on personal experience and community insights, we explore why chasing every new paper or trend often leads to burnout rather than mastery.
More importantly, we share practical, evidence-backed strategies to stay informed without losing balance: curating a focused “information diet,” setting clear boundaries, using summarization tools intelligently, maintaining a personal knowledge base, and embracing “JOMO”—the joy of missing out. We also discuss how organizations can combat fatigue structurally by promoting focus, curiosity, and psychological safety.
This session is for anyone, from beginners to seasoned professionals, seeking to rediscover genuine curiosity in AI while preserving mental well-being. Attendees will leave with concrete tools, actionable habits, and a renewed sense that it is not only acceptable but healthy to not know everything.
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.
Senior R&D Engineer at Ansys with a PhD in computational science from RWTH Aachen University. Work in the area of simulations, machine learning and AI safety.
Jeyashree Krishnan is a Senior Machine Learning Engineer at Siemens AG. Her work focuses on building and operationalizing scalable machine learning services, with an emphasis on foundation models and time series forecasting. She is also a Visiting Researcher at the Center for Computational Life Sciences, RWTH Aachen University.