laura hanu
I enjoy pushing the boundaries of AI systems while working to understand their behaviour and harness their potential safely to expand what’s possible.
I’m currently post-training computer use agents and designing their training and evaluation systems at Salesforce, which I joined through its acquisition of Convergence.
Previously, as Unitary’s first employee, I led multimodal model research for harmful content detection and created Detoxify. Before that, I researched adversarial robustness at the University of Oxford and developed computer vision systems for detecting sight-threatening diseases at Visulytix.
highlights
- joined Convergence to work on web-browsing agents; the company was acquired by Salesforce shortly afterwards
- created and led development of Detoxify, an open-source toxicity-detection library with over 12M Hugging Face downloads and 500 citations, featured in Scientific American
- built and deployed multimodal AI systems for harmful content detection at Unitary, processing over 10M videos a day
- published research on video-text retrieval using comments with Oxford’s VGG group (ECCV 2022), supported by an 18-month Innovate UK grant we won at Unitary
- researched adversarial robustness during a stint at the University of Oxford, leading to an ECCV 2020 workshop paper
- our Visulytix AI models help bring eye care to communities around the world through Orbis's flying eye hospital
- talks and outreach: the Royal Society’s school experiments series with Brian Cox and a PyTorch Lightning community talk on Detoxify
- wrote a series on multi-node ML: setting up an HPC cluster and using Slurm
questions i'm interested in
- how can we teach AI agents to develop better research taste?
- how can agents improve through their own experience?
- what does it take to make agents reliable and aligned over long horizons?
- what important problems become solvable as AI gets smarter and cheaper?