CIO
DECEMBER 6, 2023
We collect lots of sensor data on machine performance, vibration data, temperature data, chemical data, and we like to have performative combinations of those datasets,” Dickson says. 2, machine learning/AI (31%), the packaging company has three use cases in proof of concept. As for No.
CIO
NOVEMBER 9, 2023
This section of the executive order also includes vagaries such as “The Departments of Energy and Homeland Security will also address AI systems’ threats to critical infrastructure, as well as chemical, biological, radiological, nuclear, and cybersecurity risks.” Thus, additional clarity around reporting of deep R&D is needed.
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TechCrunch
MARCH 17, 2021
“Our program is our diligence,” Bronson tells me. Stembionix : With personal stem cell banking in mind, Stembionix is developing a “mailable bioreactor system” that would allow for the transporting of stem cells without the freezing/thawing that complicates things and can negatively impact viability.
Capgemini
APRIL 20, 2022
Well, Capgemini and the Norwegian Institute of Marine Research have taken on the challenge to use machine learning and AI to read, analyze and interpret vast amounts of data collected hundreds of meters below sea level, thus gaining a better understanding of events and inner workings of the ocean’s mechanisms. So what’s the solution?
John Snow Labs
MAY 10, 2023
Converting the data into a structured format so the health systems can classify patients and summarize their condition on arrival. Allowing physicians to extract critical insights rather than wasting time in reviewing complex EHRs. This tool makes chart review of narrative text notes from EHRs easier.
John Snow Labs
JUNE 1, 2023
Clinical NLP Clinical NLP systems have several requirements such as: Entity Extraction – Clinical Natural Language Processing engines surface relevant clinical concepts including acronyms, shorthand, and jargon from unstructured clinical data. the clinical NLP system should be able to detect it.
Altexsoft
OCTOBER 22, 2021
In this post, we’ll explain what deep learning is, how it works, how it’s different from traditional machine learning, and what areas it can be applied within. Get ready because you’re about to go deep into deep learning. What is deep learning? Artificial intelligence vs machine learning vs deep learning.
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