Stephen Hawking - big data key to 'some of the most important scientific advances in human history'

Speaking at the launch of the Cantab Capital Institute for the Mathematics of Information (CCIMI) last night (10 November), Professor Hawking said: “In a dazzlingly complex world, you have to be able to discern the meaning in the mess. We are, in a figurative and literal sense, awash with what we call data… What we’re only now fully realising is twofold: the sheer quantity of data in any given domain; and the tools we need to make use of the information encoded in it.

“The power of information… only comes from the sophistication of the insights which that information lends itself to. The purpose of using information, in this context, is to drive new insight. For example, I may have taken great pleasure in talking to you about hairy black holes, as I did earlier this year, but the question is: just how hairy are they? What are the implications of the knowledge I believe I have now gained?

“There is another question, and this is really where this Institute comes into its own: what new mathematical tools do I need to open up new fields of insight? This is the heart of the Cantab Capital Institute: to drive forward the development of insight, and so enrich a multitude of fields of relevance to us all.”

Pointing to new insights data analysis has brought in fields from finance to genomics and education, Professor Hawking also praised the work of Institute Director Dr Carola Schönlieb in advancing medical imaging, adding, “the prize of a better-equipped doctor and a healthier patient is strong motivation – beyond the obvious satisfaction of pushing the boundaries of mathematics.”

He also echoed comments he made on artificial intelligence earlier in the year, saying: "“it is imperative we get machine learning right – progress here may represent some of the most important scientific advances in human history.”

The comments came at the launch of the Institute, which sits within the University of Cambridge’s renowned Faculty of Mathematics.

With an emphasis on working across disciplines, world leading academics on information science at the Institute will work with economists and social scientists to advance risk analysis in financial markets and the internet, while collaborations with physicists and engineers will explore software and hardware development security, as well as imaging and structured data processing. Work with biomedical scientists will concentrate on data science in healthcare and biology.

The Institute is a collaboration between the Departments of Applied Mathematics and Theoretical Physics (DAMTP) and Pure Mathematics and Mathematical Statistics (DPMMS), established through philanthropic support of £5m from Cantab Capital Partners, a multi-billion dollar systematic hedge fund manager based in Cambridge.

It accommodates research activity on fundamental mathematical problems and methodology for understanding, analysing, processing and simulating data. Data science research performed in the Institute is on the highest international level, aiming to extract relevant information from large- and high-dimensional data with a predictable certainty.

The advance of data science and the solutions to big data questions heavily rely on fundamental mathematical techniques and in particular, their intra-disciplinary engagement. This is at the heart of the Institute, involving mathematical expertise ranging from statistics, applied and computational analysis, to topology and discrete geometry – all with the common goal of advancing data science questions.

With five PhD students, and a large growing faculty, the Institute is working on a number of projects, covering topics from biological transportation networks, to image analysis, to electron tomography. Their work will have a range of applications across a variety of industry sectors and academic disciplines.

Professor Hawking finished by praising the Institute’s development of a semantic search engine for mathematical literature, saying: “In our efforts to drive forward insight from information, we recognise that mathematicians could do with a little organising themselves.”