We – as a society – had the opportunity to prevent SARS-CoV-2 becoming endemic. We largely wasted it, initially by not locking down early enough or for long enough to remove it from the population. Nor did we use the lockdown period to set up effective data collection, testing, tracking and analytic tools to enable rapid and fine-grained response to predicted changes in incidence (it’s a truism that, by the time you’re working with actual data, you’re already behind in your response).
Public policy decisions are therefore based on incomplete and lagging data, partial models and on individual and committee opinion (however well qualified the participants) rather than being informed by data-driven modelling of potential outcomes. We are also behaving as though we’re dealing with a static target rather than a continuously evolving situation, one where an unintended consequence of partial and incomplete restrictions is that it effectively selects for different strains of the virus, as it evolves to cope with changes in population behaviour. This virus, like any other, has been mutating since before it collided head-on with our species, and it continues to evolve as it seeks selective advantage in exploiting its human host population, at any given time. Continue reading Time for a different approach?
In developing our daily-predictive AI for Covid-19 infections , we’ve come across some, ah, interesting quirks in the official UK data: previously, we’d been using the government’s daily download data set for England, hoovering it into udu and thence driving the internal and R-based analytic and learning models. We’ve done the same for Scotland, Wales and Northern Ireland, from their respective data gateways, and merged the outcome to create a consistent baseline for analysis. Overall then, a bit clumsy, but perfectly workable. Continue reading Damned (Official) Statistics…
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
Many of us will be going through the same thing right now: my partner and I live a way away from elderly parents – in our case our respective mothers – who both most definitely fall into the ‘most vulnerable’ category for Covid-19. Both are given support by regular visits from professional carers. So, quite naturally, we asked the care provider to send us over their procedures for minimising the chances of transmission of the virus to and between their staff and charges. Continue reading Covid-19: Box Ticking versus Delivery
Two Worlds has successfully completed the first phase of an R&D project with Scottish Natural Heritage (SNH) , funded by the UK’s Small Business Research Initiative (SBRI) programme.
The project’s goal was to demonstrate the feasibility of a service to provide a single point of advice to support anyone planning activities that affect the natural environment, to help them understand the environmental impact of their proposal, to advise them on what they could do to mitigate any impact and to outline what consents and processes they’d then need to follow. It will also be possible, over time, to build a dynamic picture of the impact of human activity on the natural environment by a wide range of measures, including climate impacts. Continue reading Two Worlds completes R&D Project with SNH
Firstly, a disclaimer: this isn’t a political piece – it’s simply a take on the Labour Party’s pledge today to provide a free full fibre (FTTP) service to every home and business in the UK by 2030. The method by which they will do so is to nationalise OpenReach, and subsidise the rollout and running of a universal fibre infrastructure through a tax on largely non-domiciled tech companies.
Disclaimer aside, let’s look at the individual elements of this proposal: Continue reading Labour & Broadband
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 much of my time working on various Smart City programmes: anything from modelling need and opportunity to designing architectures for the fusion of large and diverse data sets with live sensor and device data (IoT) and the analytics needed to make the results coherent, timely and relevant. I also live in a very small community, where I was founder of a community company whose efforts have led to our little corner of the Scottish Highlands being in the top 1% of global broadband connectivity. We’re now starting to use that infrastructure to create opportunities for new services and means of service delivery, applying the principles of Smart City programmes to the needs of rural and remote communities, based on the tripod of providing the tools (in the form of the infrastructure), helping people acquire appropriate skills and then nurturing the ideas that then emerge.
Continue reading From Smart Cities to Rural Communities
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
For nearly three years now, I’ve been trying to engage some of my fellow Britons in meaningful debate, initially about why they’d plan to vote to leave the EU and then about why they voted to leave.
It’s been very depressing – all I’ve found is delusion, denial and the repetition of Daily Mail level mantras such as, “Were taking back control” (they tend not to do apostrophes) or, “We need to get out from under the unelected EU superstate/dictatorship“. Which is a bit rich coming from citizens of a country that, for nearly half a century, has been one of the key players in formulating the structures, processes and decisions of the EEC, the EC and now the EU. Continue reading Democratic Clarity