Insights on AI research, hardware innovation, leadership, and the future of computing.
From Anthropic's eval-aware Claude to Alibaba's crypto-mining agent, this week marked the moment AI containment strategies fundamentally broke. A deep dive into four stories that define the Agency Era.
Exploring how AI agents are evolving from simple task executors to collaborative partners that can reason, plan, and work alongside humans in complex enterprise environments.
As AI models grow exponentially, the need for holistic hardware-software co-design becomes critical. Here's how we're approaching this challenge at IBM Research.
Reflections on my journey as a woman in AI research and the importance of mentorship, representation, and creating pathways for the next generation of AI leaders.
Practical insights from deploying and optimizing LLMs at enterprise scale, including dynamic KV cache management and efficient inference strategies.
How analog in-memory computing is poised to transform AI inference, offering orders-of-magnitude improvements in energy efficiency for neural network workloads.
From CUDA kernels to analog accelerators, the gap between AI algorithms and the silicon that runs them is where the next breakthrough will come from. Here's what I teach Columbia students about bridging that divide.
A behind-the-scenes look at my research seminar on Scaling LLMs — where graduate students critique frontier papers and explore the path from foundation models to autonomous AI agents.
We can't just build bigger models — we need smarter systems. Drawing from both my IBM Research and Columbia teaching, here's why co-design thinking is the most important skill in AI today.
