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You've probably heard about the amazing capabilities of some recent AI models, such as GPT, AI21, or BLOOM. Perhaps you use one of these models yourself. Either directly, or through another product like Wordtune, YouWrite, Jasper – or ChatGPT. It turns out that while these models are trained on language data, they can be used for other applications as well. In my latest article, you can read more about applications in materials discovery, cybersecurity, and even building management.

Applying large-scale language models outside language: Examples from materials discovery, cybersecurity, and building management

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The Next Byte

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The Next Byte Podcast is hosted by two young engineers - Daniel and Farbod - who select the most interesting tech/engineering cont...

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UltiMaker

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Since 2011, Ultimaker has built an open and easy-to-use solution of 3D prin...

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nTopology is a software company building the next generation of engineering...

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Located in Switzerland, EPFL is one of Europe’s most vibrant and cosmopolit...

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Latest Posts

You've probably heard about the amazing capabilities of some recent AI models, such as GPT, AI21, or BLOOM. Perhaps you use one of these models yourself. Either directly, or through another product like Wordtune, YouWrite, Jasper – or ChatGPT. It turns out that while these models are trained on language data, they can be used for other applications as well. In my latest article, you can read more about applications in materials discovery, cybersecurity, and even building management.

Applying large-scale language models outside language: Examples from materials discovery, cybersecurity, and building management

Engineers at Caltech have developed a method for 3-D printing pure and multicomponent metals, at a resolution that is, in some cases, an order of magnitude smaller than previously possible. The process, which uses water-based chemistry and 3-D printing, was described in a paper published in Nature on October 20.

New Process Allows 3-D Printing of Microscale Metallic Parts

For the first time, ETH Zurich researchers have been able to make a superconducting component from graphene that is quantum coherent and sensitive to magnetic fields. This step opens up interesting prospects for fundamental research.

A new quantum component made from graphene

ETH Zurich researchers have developed a structure that can switch between stable shapes as needed while being remarkably simple to produce. The key lies in a clever combination of base materials.

Stable in all kinds of shapes

While automated manufacturing is ubiquitous today, it was once a nascent field birthed by inventors such as Oliver Evans, who is credited with creating the first fully automated industrial process, in flour mill he built and gradually automated in the late 1700s.

Reprogrammable materials selectively self-assemble