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, one where 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.
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
The picture above is ASCI Red, the world’s fastest supercomputer in 1999-2000. It was about the size of a large tennis court, sucked a couple of MW and cost around $55M (it went through various incarnations). And that’s not to mention the staff of acolytes and air-conditioned buildings required to make it work. Its delivered performance was about 2.4 TFlops (Thousand Billion Floating Point Operations per second), with a theoretical maximum of around 3.2TFlops, delivered by an array of nearly 10,000 processors, all chuntering away in parallel.
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.
Rewind: Sixteen years or so ago, I was interested in how we use software to help us solve the compound, iterative and ever-changing problems we face every day: juggling complex trip schedules, working out where we need to be and when to co-ordinate with our friends or colleagues and, of course, how we find out about stuff that we’d want if only we knew to ask for it. I’m still thinking about it.
Here’s a little history: in the early nineties, much of my consultancy work orbited (often eccentrically) around a binary model: the development of new technologies and helping clients to understand how those technologies could help their businesses and to work out how and when to jump in. It still does. Continue reading Hype, Reality and Expectation