Another Friday update: we’re well into our private Beta of our predictive analytics and what-if? modelling system for Covid-19 analytics.
So what is it telling us today?
As of 3rd February our projections are (within their confidence limits, which of course become broader the further out we look, even if the central projection is tracking the reality curve well), that the R number bottoms out about now for the UK as a whole, with case numbers continuing to fall until around the 9th, by which time R number is back to .92 and, by the 13th, it’s more likely to be above 1 again, mostly driven by the SE (Essex particularly) and Merseyside (see header picture).
Continue reading Building a Better Crystal Ball
On Friday 29th January, the Scottish Government announced that Na h-Eileanan Siar (the Western Isles) is being put into Level 4 lockdown, following a surge of new cases.
On the basis of the data available to us and our modelling approach, we’re not convinced about this decision: it appears to have be made on the basis of out-of-date analysis in an area which turned the corner on this outbreak some time ago.
Our emergent analytics, which generate fresh outlooks every day, suggest that the peak of the outbreak here was passed on 19th January and that it has declined, on multiple metrics, since then.
Continue reading Lagging Decisions, Big Consequences?
We’ve been thinking for some time about how best to present the dynamic of the pandemic in a way that actually shows what’s happening – the R number doesn’t give any idea of magnitude and is – in our opinion – best kept behind the scenes as a contributor to analytic models, raw or compensated case numbers are just that – daily records – shocking enough in themselves but they still don’t show the energy in the thing. Continue reading Kinetics of a Pandemic
Two Worlds is one of the successful applicants to a £40M fund created to support “Business-led innovation in response to global disruption”, a competition that attracted 8,600 applicants. Working with a team including epidemiologists, mathematical modelling specialists and the Department of Computer Science at Imperial College, Two Worlds is using udu’s intelligent analytic software to tackle this problem. Continue reading Two Worlds wins research funding for Covid-19 Intelligent Analytics
Most AI practitioners will argue that the risk to humanity from AI doesn’t (and won’t) come from an AI waking up one day, deciding that the best way to solve the world’s problems is to wipe out humanity and then serendipitously finding that it’s in control of the world’s nuclear weapons. On the principle that cock-up trumps conspiracy, pretty much every time, we’re far more likely to take a range of hits from the misapplication of an AI that’s either too stupid to do the job that’s been asked of it or where those deploying it are incapable of understanding its limitations (or indeed don’t care, as long as they’ve cashed out before it all falls apart). Broadly speaking, machine systems fail for one or more of these reasons: Continue reading Wye AI, Man!
I spend quite a lot of my time doing due diligence on innovation funding applications. I’ve been doing this for rather longer than is comfortable to contemplate so, over the years, I’ve seen progressive tides of hype wash in, fill a few rock pools, and then wash out again, only to re-emerge a few years later – assuming it had any merit in the first place – in a form that actually works as part of the overall problem-solving ecosystem. That innovation-development-hype-disappointment cycle may actually happen several times before the rest of the innovations needed for an idea to gain market traction catch up. That’s certainly been the case with VR and AR, with IoT and, most of all, with ArtificiaI Intelligence (AI). Continue reading Then a Miracle Occurs: The Hype of AI Pitches
AI (that’s Artificial Intelligence – I have to be clear here as I live in a farming community and conversations have been known to take a strange turn) is a flavour of the moment and is riding high on the arm-waving curve of the hype cycle. We’ve been here before though – as a notion, AI has been through more loops of the hype cycle than most technologies, with successive waves of mutually reinforcing innovation and fiction conspiring to promise more than contemporary understanding could deliver.
Continue reading AI and the Naming of Names