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Computer Vision

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In this episode, we talk about about how an ant inspired robotics platform could be the future of swarm robotics due to its simple, affordable, flexible, and scalable nature.

Engineers Wiki. Most Asked Questions.

This article explores TPU vs GPU differences in architecture, performance, energy efficiency, cost, and practical implementation, helping engineers and designers choose the right accelerator for AI workloads today!

ORGANIZATIONS. SHAPING THE INDUSTRY.

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EPFL

University

Located in Switzerland, EPFL is one of Europe’s most vibrant and cosmopolitan science and technology institutions. EPFL is Europe...

56 Posts

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Photoneo

Industrial Automation

Photoneo develops industrial 3D vision, robotic intelligence software, and ...

54 Posts

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High Tech Campus Eindhoven

High Tech

High Tech Campus Eindhoven is Europe's smartest square km and has the ultim...

49 Posts

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Xsens

Appliances, Electrical, and Electronics Manufacturing

Xsens digitizes movement.

47 Posts

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ETH Zurich

University for science and technology

Freedom and individual responsibility, entrepreneurial spirit and open-​min...

43 Posts

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

Digital transformation and the Industrial Internet of Things (IIoT) continue to impact industry at all levels. While it's seen its earliest adoption in large-scale manufacturing and transport, it's spreading rapidly into other sectors.

What Is Intelligent Supply Chain Management?

Last year, MIT researchers announced that they had built “liquid” neural networks, inspired by the brains of small species: a class of flexible, robust machine learning models that learn on the job and can adapt to changing conditions, for real-world safety-critical tasks, like driving and flying.

Solving brain dynamics gives rise to flexible machine learning models