Covid-19 has shined a spotlight on many of the world’s networks, from the internet to international air travel. But the supply chains that crisscross the world—the ships and trucks and trains that link factories to ports and warehouses, bringing almost everything we buy many thousands of miles from where it’s produced to where it’s consumed—are facing more scrutiny than they ever have. “It’s fair to say that whatever you’re selling, you’ve got a problem right now,” says Jason Boyce, founder and CEO of Avenue7Media, a consulting firm that advises top Amazon sellers….
Magnus Rattray (IDSAI Director and ELLIS Health Programme Fellow) said: “The University of Manchester continues to grow as a centre of excellence for AI research and the new ELLIS unit will further strengthen this activity. Our new Chair in AI, Samuel Kaski, was recently awarded a Turing AI World-leading Researcher Fellowship with an ambitious programme of research on human-AI teams with applications to drug design, synthetic biology and digital twins.“Through the new ELLIS unit Manchester will be able to better link machine learning researchers…
In the DSC November 2 editorial, I posed a question I’ve wondered about for a while. Why is it so hard to create a shared-reality world, whether it’s called Virtual Reality, Artificial Reality, Extended Reality, Digital Twins, or any of a number of other terms? And for that matter, what does it matter to data scientists?
It turns out that the answer to the first question is actually highly relevant to data scientists. In order to share a virtual world, you need to have a common conceptual framework about how things are represented in that world.
This is not just a matter of saying that…
CRISPR, Quantum, Graphene, Smart Dust, Digital Twins, the Metaverse… You’ve heard about it all. Seen it all. Read it all. Or have you? Read the full story
With the rise in compute power over the past 10 years, we have seen a sharp increase in the number of simulations. Digital twins are one such example. They are virtual replicas of a physical object or process that can be simulated in a variety of scenarios.
One problem faced by digital twins is how they can combine potentially noisy empirical data with physics.
In 2021, researchers at the University of Sheffield developed a very simple digital twin framework called PhysiNet to solve this problem. PhysiNet combines deep learning with physics models to develop robust forecasts of device performance.
While digital twins do require significant development resources, they can be effective alternatives where physical tests are prohibitively expensive or dangerous.
An orrey or planetarium designed by George Adams showing relative positions of the planets in relation to the sun, 1799, https://www.loc.gov/pictures/item/2006691765.
Part I of II explored the concept of a metaverse or mirrorworld, and pointed out that even enthusiasts like Wired Co-Founder Kevin Kelly and Forbes contributor Charlie Fink believe that a mirrorworld–a dynamic “digital skin” that would usefully represent, monitor and shed insights on the interacting elements of our physical world–could well take 25 years or more to emerge.
Part I also concluded that the major obstacle to the creation and effective use of a metaverse or mirrorworld will be data (and knowledge, which is contextualized data with supporting relationship logic) management.
Austin, TX – (September 7, 2021) – AutoScheduler.AI, an innovative Warehouse Management System (WMS) accelerator, announces the addition of Andrew Gibson as Chief Technology Officer to lead the company’s software development efforts to the next level. Andrew is a supply chain industry expert, formerly with Nestle, and has deep expertise in mathematics, which is the cornerstone of artificial intelligence. AutoScheduler.AI smooths operations in a warehouse by integrating seamlessly with warehouse management systems, orchestrating activities across supply chain campuses, and adding value by improving OTIF, managing inventory, and creating dynamic schedules that change as conditions shift.
It’s Gartner Hype Cycle Day! This is roughly analogous to the Oscars for emerging technologies, in which the Gartner Group looks through their telescopes to see what could end up being the next big thing over the course of the next decade. The idea behind the hype cycle is an intriguing concept – emerging technologies seem to come out of nowhere, explode into prominence while the technology is still less than fully mature, then seemingly disappear for a while as the promise of the hype gives way to the reality of implementation and real-world problems. Once these are worked out, the technology in question gets adopted into the mainstream.
The hype cycle is frequently the source of investor bingo, where young startups pick a term that most closely reflects their business model, then pitch it to angel investors to provide supporting evidence that their product is worth investing in.