The way we do science is evolving. We are building to cope with the change.
The last decade has brought us into a world of cheap sensors, enormous datasets and commodity distributed computing. The AI revolution is well under way, with new models becoming ever more impressive. We also now live in a world where scientific collaborations happen across many time zones and institutions. A great amount of revolutionary research is coming from outside of academia. The old models of scholarship are struggling to keep up with these transformations. Teaching, funding, career progressions, even the notion of a research paper -- all is in flux.
New tools, methodologies and concepts are needed to ensure the scientific community can continue in its pursuit of knowledge. We created scie.nz to help meet this need, and have fun along the way. We are as excited about building expressive and powerful models as we are about the data infrastructure required to make ML work in practice.
We are animated by two convictions. Science can only fully benefit from new innovations in AI if researchers embrace modern software engineering practices. Just as important, data science needs to be, first and foremost, scientific and rigorous. This intersection of scientific curiosity and software craft is where we aim to do our work.