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McKelvey’s Chien-Ju Ho working with Art & Sciences’ Wouter Kool, DCDS PhD student Lauren Treiman to understand how human behavior changes in training AI
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The Guide to Understanding the Technologies Defining the Next Phase of Edge AI
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Texas A&M researchers are using AI to improve the management of disasters like hurricanes before, during and after the events.
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EPFL scientists have developed an AI-based technique to improve chemical analysis of nanomaterials, overcoming challenges of noisy data and mixed signals.
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TAGGED WITH machine learning
Training AI models is costly, forcing a trade-off between compressing large models or accepting weaker performance from smaller ones trained from scratch.
This new approach adapts to decide which robots should get the right of way at every moment, avoiding congestion and increasing throughput.
A team that included Chongzie Zhang from McKelvey Engineering developed a method that allows robots to teach other robots with different features to perform the same task.
New AI system lets robots work faster than their human teachers without sacrificing accuracy.
TAGGED WITH computer vision
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
Matroid builds no-code computer-vision detectors that can spot everything from microscopic material defects to real-time safety hazards on a factory floor.
In large-scale warehousing and distribution operations, conveyor belts are an essential infrastructure that must operate with near-zero downtime to ensure the timely delivery of products. The presence of loose or foreign items on a conveyor belt can pose a serious risk to these operations.
In this post, we'll walk through how to evaluate that progress using the same metrics our platform provides automatically, so you can build detectors that get smarter, sharper, and more reliable over time.
Latest Posts
McKelvey’s Chien-Ju Ho working with Art & Sciences’ Wouter Kool, DCDS PhD student Lauren Treiman to understand how human behavior changes in training AI
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Texas A&M researchers are using AI to improve the management of disasters like hurricanes before, during and after the events.
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EPFL scientists have developed an AI-based technique to improve chemical analysis of nanomaterials, overcoming challenges of noisy data and mixed signals.
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Learn about some of the trends driving the use of technology in agriculture.
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Columbia Engineering wins a new grant from the National Oceanic and Atmospheric Administration to develop AI-system for sustainable waterways and ocean health
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Research Facility 2.0 (RF 2.0) is an EU-funded research project aimed at making the operation of particle accelerators and other large-scale facilities more resource-efficient.
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In this episode of the “This is Our Mission” podcast, Sean Hehir interviews Dr. Eric Gallo, a Senior Principal at Accenture Labs. They discuss the advantages of neuromorphic technology and its impact on edge computing, as well as advancements in SpaceTech.
Moving Your ML Proof of Concept to Production Part 1: From Business Goals to ML Metrics
Researchers at Fraunhofer Institute have developed a free, online tool for testing the robustness of AI models
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The phrase “practice makes perfect” is usually reserved for humans, but it’s also a great maxim for robots newly deployed in unfamiliar environments.
EPFL researchers have published a programmable framework that overcomes a key computational bottleneck of optics-based artificial intelligence systems.
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Imagine an industrial plant where machines autonomously predict maintenance needs and optimize operations. Such efficiency is powered by IoT architecture. This guide breaks down the layers of IoT, from sensors collecting data to intelligent apps providing insights.
Researchers have developed a platform for the interactive evaluation of AI-powered chatbots such as ChatGPT.
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If self-driving vehicles can navigate this complex road challenge safely, the learnings could help advance the safety of automated driving in urban scenarios.
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The moonshot of many roboticists is cooking up the proper hardware and software combination so that a machine can learn “generalist” policies (the rules and strategies that guide robot behavior) that work everywhere, under all conditions.
