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Deep-Learning technology helps industrial engineers with continuous improvement, line balancing, and optimizing manual labor.
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Deep-Learning technology helps industrial engineers with continuous improvement, line balancing, and optimizing manual labor.
Featured
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.
Featured
EPFL researchers have teamed up with Dartfish and the Lausanne Hockey Club to push the boundaries of sports-performance analysis by applying computer vision and machine-learning technology to action on the ice.
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!
TPU vs GPU: Comprehensive Technical Comparison
By Umar Waseem.
14 minutes read.
NPU vs GPU: Understanding the Key Differences and Use Cases
By Ravi Rao.
13 minutes read.
RAG vs Fine-Tuning: Differences, Benefits, and Use Cases Explained
By Ravi Rao.
18 minutes read.
LLM Training: Mastering the Art of Language Model Development
By Ravi Rao.
30 minutes read.
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ORGANIZATIONS. SHAPING THE INDUSTRY.
High Tech Campus Eindhoven
High Tech
High Tech Campus Eindhoven is Europe's smartest square km and has the ultim...
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ETH Zurich
University for science and technology
Freedom and individual responsibility, entrepreneurial spirit and open-min...
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TAGGED WITH machine learning
Nakahira received a Young Investigator Award from the Japan Science and Technology Agency for developing a machine that builds autonomous systems.
Princeton researchers have developed a new tool to speed the discovery of advanced materials known as metal organic frameworks, or MOFs.
EPFL roboticists have shown that when a modular robot shares power, sensing, and communication resources among its individual units, it is significantly more resistant to failure than traditional robotic systems, where the breakdown of one element often means a loss of functionality.
MIT researchers' DiffSyn model offers recipes for synthesizing new materials, enabling faster experimentation and a shorter journey from hypothesis to use.
TAGGED WITH motion capture systems
Latest Posts
Deep-Learning technology helps industrial engineers with continuous improvement, line balancing, and optimizing manual labor.
2 minutes read
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.
5 minutes read
EPFL researchers have teamed up with Dartfish and the Lausanne Hockey Club to push the boundaries of sports-performance analysis by applying computer vision and machine-learning technology to action on the ice.
3 minutes read
with Xsens MVN Animate
5 minutes read
#10 of our Voice of Innovation fireside chat series: Robotics and AI reporter Rachel Gordon speaks to Daniel Situnayake, a founder, engineer, and teacher, on what it means to run sophisticated machine learning algorithms on small devices at the edge of a network.
In this episode, we talk about how perfectly tuning the curiosity of an AI results in more efficient and robust models.
Producing chirality, a property found throughout nature, through large-scale self-assembly could lead to applications in sensing, machine perception and more.
4 minutes read
Datacation is a startup in a technology area so advanced it can't even be called 'next-generation'. Perhaps 'next next gen' because so far we don't know all the possible business applications of machine learning and AI, nor do we know the limits.
7 minutes read
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.
Axl Chen is the founder and CEO of Surplex, a new full-body tracking technology company aiming to change the gaming industry and professional sports.
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.
Article #5 of the "Why Edge?" Series Moving Computer Vision to the Edge offers advantages in security and latency.
Curiosity drives artificial intelligence to explore the world, now in boundless use cases — autonomous navigation, robotic decision-making, optimizing health outcomes, and more.
Matroid's deep-learning system comprising of 3D-CNN helps to automatically detect Glaucoma from a single raw Optical Coherence Tomography (OCT) scan. The results are close to human doctors across heterogeneous datasets and scanning environments.
ML at the edge is the main target in many IoT applications today. Learn why it is important to build energy-efficient embedded devices, and how to achieve it using cutting-edge technologies.
