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2.21 MB
Extraction Summary
2
People
3
Organizations
1
Locations
0
Events
1
Relationships
5
Quotes
Document Information
Type:
Essay / scientific article / evidence document
File Size:
2.21 MB
Summary
This document is page 25 of a larger file produced by the House Oversight Committee (Bates stamp HOUSE_OVERSIGHT_016828). It contains an essay titled 'The Limitations of Opaque Learning Machines' by Judea Pearl, a UCLA professor. The text discusses the shortcomings of deep learning and AI opacity compared to causal reasoning and transparency. While the document is part of an Epstein-related release, the text itself is purely academic/scientific in nature, likely collected because Epstein cultivated relationships with prominent scientists and intellectuals.
People (2)
| Name | Role | Context |
|---|---|---|
| Judea Pearl | Author / Professor |
Professor of computer science and director of the Cognitive Systems Laboratory at UCLA; author of the essay.
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| Dana Mackenzie | Co-author |
Co-authored 'The Book of Why' with Judea Pearl.
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Organizations (3)
| Name | Type | Context |
|---|---|---|
| UCLA |
University where Judea Pearl is a professor.
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|
| Cognitive Systems Laboratory |
Laboratory at UCLA directed by Judea Pearl.
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| House Oversight Committee |
Source of the document (indicated by Bates stamp HOUSE_OVERSIGHT).
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Locations (1)
| Location | Context |
|---|---|
|
Academic institution location.
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Relationships (1)
His most recent book, co-authored with Dana Mackenzie, is The Book of Why...
Key Quotes (5)
"We are losing this transparency now, with the deep-learning style of machine learning."Source
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Quote #1
"It is fundamentally a curve-fitting exercise that adjusts weights in intermediate layers of a long input-output chain."Source
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Quote #2
"I find many users who say that it 'works well and we don’t know why.'"Source
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Quote #3
"If our robots will all be as opaque as AlphaGo, we won’t be able to hold a meaningful conversation with them, and that would be unfortunate."Source
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Quote #4
"Current machine-learning systems operate almost exclusively in a statistical, or model-blind, mode, which is analogous in many ways to fitting a function to a cloud of data points."Source
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Quote #5
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