Category Archives: Machine Intelligence

Waiting for the Fat Lady

The UK government has just announced that it isn’t going to make a decision on further relaxing Covid-19 restrictions for another two weeks, just as many people were, quite reasonably hoping that the fat lady was, if not in full song, at least warming up for her aria.

Flippancy aside, let’s be clear: delaying a decision like that is utter nonsense, at multiple levels: whether it’s driven by the use of lagging data, the continuing failure to adopt and use effective forecasting (ours or anyone else's), the pursuit of political dogma, or any combination of these, they're once again delaying decision making until it's too late.

Worse, they seem to be relying on the success of the vaccination program to try to pull a largely fictional rabbit out of their hat - the hat that comes with a large label saying, "Wishful Thinking". But now for the data and analysis… Continue reading Waiting for the Fat Lady

Intelligent Reality & Astrosat form Consortium for NatureScot’s Better Land Information 

Musselburgh based Earth Observation (EO) specialists Astrosat have teamed up with Scotland and Germany-based Machine Intelligence experts Intelligent Reality, for a NatureScot project to provide Better Targeted Information for Land Managers and Developers on protected sites in Scotland. The partnership has been selected from a field of 24 tech companies to develop the product under a challenge funded through the UK wide GovTech Catalyst Challenge.  Continue reading Intelligent Reality & Astrosat form Consortium for NatureScot’s Better Land Information 

Scotland Rising

So, Scotland is on the rise again. Unfortunately, this is in respect of Covid-19: of the four UK nations, it currently has the highest R Number (1.25 as of the 19th May), versus Northern Ireland's 1.05, England's 1.02 and Wales's 1.04. The UK as a whole is sitting at 1.05.

2021-05-21 Scotl<script srcset=
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We are however still faced with the situation of governments (in this case, the Scottish Government) making decisions late, and based on data that's a week or more old, and not apparently using any form of validated forecasting to inform timely decision making.

In case you're new to our blog, we've developed a Covid-19 targeted version of our emergent forecasting system and, in this case,  have been forecasting the rise in cases on all but four days since the beginning of May.

Disclaimer: we're not calling out the Scottish Government here over the governments of other parts of the UK: it's just that this is our patch and it's easier to compare the 32 Scottish Local Authorities than the 214 for the whole UK. In our more cynical moments, we think about creating a 'Political Wishful Thinking vs Actual Data' index, but it's a league table that would probably show little variation over time. Continue reading Scotland Rising

Early Warning Onwards

The UK government stated yesterday (13 May) that rising case numbers in the Bolton area were a cause for concern, and that very many of these cases were of the so-called ‘Indian’ variant (B.1.617.2 being the designated variant of concern, with B.1.617.1 and B.1.617.3 under investigation). Here, raw data for case numbers has been available for weeks, with  organisations such as the Sanger Institute also providing a very informative breakdown by sequenced  variants.

Our analytics platform had identified Bolton and other areas as potential concerns more than two weeks ago and had flagged a correlation between these hot spots and the ethnic balance of the local population, such that, even in the absence of cross-border travel data, of the emerging variants or the situation in India, we were able to provide early warning of emerging problems.

Which very much begs the question as to why the UK government only raised this yesterday, and why travel restrictions from India were only imposed long after the pandemic reached critical mass there. Continue reading Early Warning Onwards

The Last Unknown?

A remaining big unknown in the pandemic is not whether vaccines reduce serious symptoms, hospital admissions and deaths – they do – but whether and to what degree vaccines reduce the ability of those vaccinated to infect others, whilst not being symptomatic themselves. As we've noted before, initial data on post-vaccination infectivity was somewhat contradictory, so we don't yet build the impact of vaccination on infectivity into our forecasting.

Continue reading The Last Unknown?

Intelligent Reality at EIE2021

We are pleased to announced that our new company, Intelligent Reality, has been accepted into EIE’s 2021 cohort, which showcases the most innovative, data-driven tech companies from Scotland, the UK and beyond. EIE's (Engage, Invest, Exploit) annual conference features the the most promising high-growth companies who are seeking funding, from seed to series A.

Over the last 18 months we have successfully developed both our generic platform and environmental and geospatial applications, with an SBRI-funded R&D programme for Scottish Natural Heritage (now NatureScot) and, latterly, with three rounds of funding from InnovateUK. These have led to the successful development of inferential tools for exploratory, analytic and predictive modelling of the Covid-19 pandemic, as well as enhancing our core platform.

We have not only developed our analytic and predictive pipeline, but have further developed our relationship with udu, the revolutionary, discovery-based data intelligence platform, itself co-founded by Two Worlds.

With academic and industrial partners, we have also explored real time applications in precision agriculture and pollution monitoring.

Intelligent Reality,  with staff in Scotland and Germany, has been formed to exploit the successful outcomes of Two Worlds' incubation of its adaptive, self-organising approach to data analytics, providing insight and predictive intelligence for real world applications in dynamic environments.

EIE, which is run by the Bayes Centre at Edinburgh University in partnership with the DDI (Data-Driven Innovation) initiative, is a year-round programme highlighted by a day of pitching to investors from across the globe. EIE21 takes place on 10 June.

Damned (Official) Statistics…

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 wins research funding for Covid-19 Intelligent Analytics

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

Wye AI, Man!

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 stupid1 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!

Then a Miracle Occurs: The Hype of AI Pitches

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