Marktechpost

JULY 19, 2023

The team has used the example of extracting the device classification attribute from FDA reports for medical devices to illustrate this. EVAPORATE has been evaluated on 16 sets of documents across a range of formats, topics, and attribute types.

Large Language Models 63

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Snorkel AI

MAY 18, 2023

Now in related work, we also performed similar kinds of audits for many other medical AI systems that were approved by the FDA. The FDA is the gold standard for approving medical-related interventions, drugs, and vaccines, including AI systems. So we looked at over 130 FDA-approved AI systems. Makes sense.

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Snorkel AI

MAY 18, 2023

Now in related work, we also performed similar kinds of audits for many other medical AI systems that were approved by the FDA. The FDA is the gold standard for approving medical-related interventions, drugs, and vaccines, including AI systems. So we looked at over 130 FDA-approved AI systems. Makes sense.

Machine Learning 52

Machine Learning AI AI Algorithm 52

AI Impacts

APRIL 11, 2023

Our researcher Jeffrey Heninger has recently finished some case studies on this topic, covering geoengineering, nuclear power, and human challenge trials. This document summarizes the lessons I think we can take from these case studies. 4 Scientific papers published on solar radiation management by year.

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AI Impacts

DECEMBER 22, 2022

Whereas customarily the tentative answer seems to be, ‘of course not’ and then the topic seems to be avoided for further thinking. (At Ok, so if we tentatively suppose that this topic is worth even thinking about, what do we think? Why not slow down AI? Why not consider it? Is slowing down AI a good idea at all?

AI 130

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Bugra Akyildiz

SEPTEMBER 4, 2023

In fact, these workflows are so unstandardized that the FDA (and other regulatory agencies) rely on companies asking for ML approval to define their own testing procedure. Too much work: Frankly, validation can be hard to orchestrate.

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Flipboard

AUGUST 1, 2023

Other stakeholders, though, want extensive new rulemaking and legislating on a variety of AI topics. Gary Marcus, an NYU professor and prominent voice on AI, urged Congress to specifically follow the FDA model as it ponders regulating AI , requiring pre-approval before deployment. Some, like Sens.

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