[ExI] thawing of ai winter?

[Dylan Distasio]

Hi Spike-

I believe they're referring to the thaw in the AI winter DUE to deep
learning's success in recent years (so the thaw has been going on for quite
some while, really at least a decade).  That said, I personally think we
may be ended up heading back into the winter.  As impressive as deep
learning has been for SOME applications, it remains brittle and we seem to
be hitting walls (i.e. it is becoming apparent that Level 5 driving cars
are going to be extremely difficult to release into the real world wild
with multiple complications, bad weather, etc. than people originally
predicted based on the limits of current algos).  I remain skeptical that
we'll see a true level 5 vehicle without a breakthrough in strong AI.

On Fri, Apr 17, 2020 at 11:46 AM spike jones via extropy-chat <
extropy-chat at lists.extropy.org> wrote:

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> Stanford weekly seminars are quite good.  I have half a mind to tune in to
> this discussion today.
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> https://hai.stanford.edu/events/hai-weekly-seminar-vinay-uday-prabhu-four-horsemen-ethical-malice-peer-reviewed-machine?utm_source=Stanford+University&utm_campaign=0f2d627924-EMAIL_CAMPAIGN_2020_03_13_10_26_COPY_01&utm_medium=email&utm_term=0_aaf04f4a4b-0f2d627924-199837799
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> This comment about thawing of the AI winter caught my attention.  What is
> that?  I didn’t realize we were in an AI winter.
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> AI hipsters, do offer an educational comment please.
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> spike
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> EVENT TODAY!
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> HAI Weekly Seminar with Vinay Uday Prabhu
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> On the Four Horsemen of Ethical Malice in Peer-Reviewed Machine Learning
> Literature
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> April 17, 2020
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> 11:00AM PDT
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>                 Add to Calendar
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> Speaker Bio: Vinay Prabhu is currently the Chief Scientist at UnifyID Inc,
> where he leads efforts towards architecting and deploying the
> state-of-the-art passive mobile biometrics solution by bringing together
> machine learning algorithms and smart-sensor data to model the human behind
> the device.
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> Abstract: The thawing of the AI winter and the subsequent deep learning
> revolution has been marked by large scale open-source-driven
> democratization efforts and a paper publishing frenzy. As we navigate
> through this massive corpus of technical literature, four categories of
> ethical transgressions come to fore: Dataset curation, Modeling, Problem
> definitions and sycophantic tech-journalism. In this talk, we will explore
> specific examples in each of these categories with a strong focus on
> computer vision. The goal of this talk is to not just demonstrate the
> widespread usage of these datasets and models, but to also elicit a
> commitment from the attending scholars to either not use these datasets or
> models, or to insert an ethical caveat in case of unavoidable usage…
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> _______________________________________________
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