Blockchain is to be used for the first time to try to track cobalt’s journey from artisanal mines in Democratic Republic of Congo through to products used in smartphones and electric cars.
Blockchain technology is already used in the diamond industry. Gems are given a digital fingerprint that is then tracked by blockchain as gems are sold, giving a forgery-proof record of where the stones have come from.
The cobalt supply chain is far more complex but the developers of the pilot hope blockchain – a decentralized online database in the form of a distributed ledger – can at least track some of the stages that are a major worry for end users.
Carmakers such as Volkswagen are trying to secure long-term cobalt supplies to sustain electric car production, and they are asking suppliers to ensure no child labor was used in the supply chain.
If you follow AI you might have heard about the advent of the potentially revolutionary Capsule Networks.
Geoffrey Hinton is known as the father of “deep learning.” Back in the 50s the idea of deep neural networks began to surface and, in theory, could solve a vast amount of problems. However, nobody was able to figure out how to train them and people started to give up. Hinton didn’t give up and in 1986 showed that the idea of backpropagation could train these deep nets. However, it wasn’t until 5 years ago in 2012 that Hinton was able to demostrate his breakthrough, because of the lack of computational power of the time. This breakthrough set the stage for this decade’s progress in AI.
And now, on October 26, 2017, he has released a paper on a new groundbreaking concept, Capsule Networks (the research papers can be found here and here).
CapsNets were first introduced in 2011 by Geoffrey Hinton, et al., in a paper called Transforming Autoencoders, but it was only a few months ago, in November 2017, that Sara Sabour, Nicholas Frosst, and Geoffrey Hinton published a paper called Dynamic Routing between Capsules, where they introduced a CapsNet architecture that reached state-of-the-art performance on MNIST (the famous data set of handwritten digit images), and got considerably better results than CNNs on MultiMNIST (a variant with overlapping pairs of different digits).
Everyone talks about digital transformation. Almost none of them is aware that in 5 years quantum computers will probably have the potential for breaking private keys used for digital signatures.
The problem is that digital transformation relies on PKI cryptography mechanism. What will happen when someone rewrite and change original digital document and sign it again with original private key? Non-repudiation will not exist anymore.
In that time we will probably use another cryptography algorithms (quantum criptography), but for all older documents that were signed with PKI the authenticity will be repudiated.
Industry disruption — “a process whereby a smaller company with fewer resources is able to successfully challenge established incumbent businesses” — is reasonably predictable. Accenture Research develops an index that measures an industry’s current level of disruption as well as its susceptibility to future disruption. See Harvard Business Review article.
While quantum computers still exist only in the lab, they are seen as holding out great promise for the future. UNI NOVA introduces some approaches to quantum computing and describes the work that researchers at Basel University are conducting through a combination of theoretical ideas and ingenious experiments.