New technologies are emerging all the time, radically changing how technical industries do business. Technical innovation can often be the key to success, which is why it’s so important to stay ahead, look to the future, and embrace change.
Being in the know about the next big thing can be the difference between success and failure, so let’s look at some of the big innovators and disruptions making waves this year.
A building can only be designed according to the space that is available, and the ability to travel within that space. This has translated into vertical buildings, first with stairs, later with elevators: you start at the bottom and work your way up. However, now there is another way: along. Powered by magnetic levitation, or maglev, new sideways elevators allow for architects to create more visually engaging buildings.
Elevator shafts take up around 40% of a building’s core, meaning you are limited in the scope of what you can build around it. This system, called Multi, increases a buildings’ potential area by around 25%, freeing up space for innovation.
3-D printing systems have been around for a few years but are yet to take off in the way that many were expecting. With printing in materials other than plastic incurring heavy costs, the dream of instantly creating something from metal seemed to be doomed to remain just that: a dream. But now, progress is being made into printing with other materials, allowing for a vast array of different products to be designed and generated.
3D Printing has the potential to revolutionise manufacturing as we know it, speeding up the time it takes to create complex machines. The technology can create lighter, stronger parts, and complex shapes that aren’t possible with conventional metal fabrication methods. 3D Printing can also provide more precise control of the microstructure of metals. In 2017, researchers from the Lawrence Livermore National Laboratory announced they had developed a 3-D-printing method for creating stainless-steel parts twice as strong as traditionally-made parts.
This technology is currently being worked on by GE, who recently built a prototype jet engine, and refined it to peak efficiency, in just 12 weeks.
3. GANs (Generative Adversarial Networks) Will Let Computers Think
Technical researchers already use neural networks: systems modelled on the human brain. These are referred to as ‘generative’ networks, able to create new data or constructs on their own. Previously, results were lacking in certain areas, with the machine unable to fill in the gaps. Ian Goodfellow changed all that four years ago when he decided to pit two neural networks against each other, spawning the first GAN, or ‘generative adversarial network.’ One network attempts to discern accurate constructs from fake ones and the other attempts to generate fake ones more convincingly. They both learn from each other and then adapt. This technology gives machines an ability akin to imagination. One use is for computers to generate images from text descriptions alone.
GANs are prime examples of ‘unsupervised learning’ which may become more common as AI develops, impacting engineering and any sector which relies on computer-generated imagery.
Zk-SNARK (zero-knowledge succinct non-interactive argument of knowledge) is a cryptographic tool that may soon allow for almost complete anonymity on the internet, something that seems impossible to imagine today.
Zk-SNARK could reduce the amount of data stored online needed to identify individuals, and therefore limit what could be stolen or leaked in the event of a hack. It relies on something called a zero-knowledge proof, a concept which has been around since 1985: ‘a zero-knowledge protocol is a method by which one party (the prover) can prove to another party (the verifier) that something is true, without revealing any information apart from the fact that this specific statement is true.’ This is being utilized in blockchain in the form of Zk-SNARKs, a proof construction that allows for transactions to be registered as valid without any external information being involved.
Quantum computers might soon be able to help us design new materials, biological constructs, and molecules thanks to increasingly powerful simulations. IBM recently simulated the electronic structure of a molecule. This is exciting because current computers struggle to simulate molecular behavior due to their complexity. But stronger, smarter computers mean we can gain a deeper understanding of how molecules work and can begin to make adaptations to them. This could result in new protein strains that help fight disease, different materials that are more fuel-efficient, or even brand new sources of energy.
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