SLAC topics

AI and machine learning RSS feed

Artificial intelligence (AI) simply means intelligence in machines, in contrast to natural intelligence found in humans and other natural organisms. Machine learning involves systems that automatically learn from the data they analyze and the results they obtain to improve their ability to work with that data in the future.

DOE explains... artificial intelligence

Artistic representation of a neural network superimposed on an electron beam profile

News Feature

The SLAC/Stanford researcher is a leading materials scientist and entrepreneur whose research is paving the way for better batteries, cleaner power grids.

SLAC and Stanford researcher Will Chueh
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Machine learning is becoming an essential part of a physicist’s toolkit. How should new students learn to use it?

Illustration: A student scientist embroiders their graduation cap with atom
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Physics may seem like its own world, but different sectors using machine learning are all part of the same universe. 

Illustration of a scientist cutting a piece of bias tape with scissors
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VIA Symmetry Magazine

Symmetry: AI for control rooms

Scientists inside and outside of particle physics and astrophysics are leaning on AI for assistance with complex tasks.

Illustration of a scientist pinpointing part of a galaxy through the lens of a magnifying glass
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In the coming weeks, Symmetry will explore the ways scientists are using artificial intelligence to advance particle physics and astrophysics—in a series of articles...

Conceptual illustration of wool being spun into refracted light
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Wan-Lin Hu’s job is to improve the way people and artificial intelligence collaborate to run SLAC’s complex machines.

Wan-Lin Hu is seen talking with talks with accelerator systems operator Kabir Lubana in the lab’s main Accelerator Control Room.
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The software tool sorts through messy data to reveal what’s really going on with solar panels on cloudy and sunny days.

This is a graphic representation of solar power system data. The data is processed by algorithms, which turn the data into specific power loss causes.
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The research reveals the potential for machine learning in understanding the complex behavior of quantum materials.

machine learning
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Analyzing X-ray movies with computer vision reveals how nanoparticles in a lithium-ion battery electrode work.

Illustration of battery electrode nanoparticles being imaged by X-rays
News Feature

The algorithm pairs machine-learning techniques with classical beam physics equations to avoid massive data crunching.

This is a representation of a particle beam traveling through an accelerator.
Past Event

Presented by Axel Levy.

public lecture poster image