Deep Tech × Applied AI

Platforms that bring computation into clinical workflows: brain-computer interfaces moving from research to therapeutic devices, agentic AI automating healthcare operations. Technology that compresses the distance between data and clinical decision-making.

Cell-cultured proteins, precision fermentation, and bio-based materials will be the future of how we "grow" food and build the world around us. As more of Earth begins to look like Mars, and we move into Space, I've found the GCC a good analog for humanity's interplanetary future. It helps that the GCC is investing aggressively to localize bio supply chains. Companies that can license or localize production for Middle East and APAC markets have a second growth vector most US VCs overlook.

Novel modalities and AI-native drug discovery that compress timelines and reduce capital intensity. It's been a graveyard, but we're now coming out of the hole. My deep expertise in Antimicrobial Resistance (AMR) keeps me grounded from both biosafety and pandemic-readiness perspectives.

The next bottleneck after energy and compute resolve will be the data crunch. As models scale, the quality, depth, diversity, and provenance of AI-ready training data becomes the binding constraint. I'm very interested in this generally, but also specifically in the bits-to-atoms world of biology and chemistry.

Frontier models are English and Chinese dominant, and we're just scratching the surface with text (and some images). The real human opportunity, and the economic one, is in making AI work for the rest of the world, in the modalities we naturally interact in as humans, like speech.

Aligning post-training and safety in AI will be a vast economic opportunity on the journey to make AI work for all, while ensuring bad actors are guarded against. You don't need to go far to see how important this is, so I won't harp on it more here.