Building Machines That Better Understand Human Goals
First published Dec. 7, 2020, on MIT Computer Science & Artificial Intelligence Lab (CSAIL) news.
First published Dec. 7, 2020, on MIT Computer Science & Artificial Intelligence Lab (CSAIL) news.
A team of Lawrence Livermore National Laboratory (LLNL) scientists has simulated the droplet-ejection process in an emerging metal 3D-printing technique called “liquid metal jetting” (LMJ), a critical aspect to the c
This story was originally published by Knowable Magazine.
Advanced metal alloys are essential in key parts of modern life, from cars to satellites, from construction materials to electronics.
The ongoing global Covid-19 pandemic has forced companies of all types to rapidly update policies and procedures governing how they share information in response to a world that is constantly changing around them.
Digital applications in manufacturing are not only becoming increasingly accepted; they are expected. However, for smaller manufacturers, the process of making this switch can be daunting.
The benefits of simulation-based training are indisputable and innumerable. Given its power and efficacy, this methodology is used in sectors beyond aerospace and military, where it gained its initial foothold.
When the words “artificial intelligence” (AI) come to mind, your first thoughts may be of super-smart computers, or robots that perform tasks without needing any help from humans.
Covid-19 has dealt most businesses a heavy blow, but the pandemic has at least one under-acknowledged upside.
If you were to contact a group of recycling professionals, as one recent survey did, and ask them to list all the ways that consume
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