When I bought back my company about 25 years ago, the mantra for
programmers was “Google the error message!” Now ChatGPT will write
some of the code for you. The job of programming still requires a lot of
knowledge and experience since using ChatGPT-generated code without
quality checking is far from failsafe.
—Barry
On 1 Mar 2023, at 11:04, Marcus Daniels wrote:
I have seen doctors run internet searches in front of me. If a LLM
is given all the medical journals, biology textbooks, and hospital
records for training, that could be a useful resource for society.
-----Original Message-----
From: Friam <friam-boun...@redfish.com> On Behalf Of Santafe
Sent: Wednesday, March 1, 2023 4:45 AM
To: The Friday Morning Applied Complexity Coffee Group
<friam@redfish.com>
Subject: Re: [FRIAM] Magic Harry Potter mirrors or more?
This is fun. Will have to watch it when I have time.
Is there a large active genre just now combining ChatGPT wiht
deepfakes, to generate video of whomeever-saying-whatever?
I was thinking a couple of years ago about what direction in big-AI
would be the most distructive, in requiring extra cognitive load to
check what was coming in through every sense channel all the time.
Certainly, as much as we must live by habit, because doing everything
through the prefrontal cortex all the time is exhausting (go to a
strange country, wake up in the middle of the night, where are the
lightswitches in this country and how do they work?), there clearly
are whole sensory modalities that we have just taken for granted as
long as we could. I have assumed that the audiovisual channel of
watching a person say something was near the top of that list.
Clearly a few years ago, deepfakes suddenly took laziness off the
table for that channel. The one help was that human-generated
nonsense still takes human time, on which there is some limit.
But if we have machine-generated nonsense, delivered through
machine-generated rendering, we can put whole servers onto it
full-time. Sort of like bitcoin mining. Burn a lot of irreplaceable
carbon fuel to generate something of no value and some significant
social cost.
So I assume there is some component of the society that is bored and
already doing this (?)
Eric
On Feb 28, 2023, at 9:10 PM, Gillian Densmore
<gil.densm...@gmail.com> wrote:
This john oliver piece might either amus, and or mortify you.
https://www.youtube.com/watch?v=Sqa8Zo2XWc4&ab_channel=LastWeekTonight
On Tue, Feb 28, 2023 at 4:00 PM Gillian Densmore
<gil.densm...@gmail.com> wrote:
On Tue, Feb 28, 2023 at 2:06 PM Jochen Fromm <j...@cas-group.net>
wrote:
The "Transformer" movies are like the "Resident evil" movies based on
a similar idea: we take a simple, almost primitive story such as
"cars that can transform into alien robots" or "a bloody fight
against a zombie apocalypse" and throw lots of money at it.
But maybe deep learning and large language models are the same: we
take a simple idea (gradient descent learning for deep neural
networks) and throw lots of money (and data) at it. In this sense
transformer is a perfect name of the architecture, isn't it?
-J.
😁😍🖖👍🤔
-------- Original message --------
From: Gillian Densmore <gil.densm...@gmail.com>
Date: 2/28/23 1:47 AM (GMT+01:00)
To: The Friday Morning Applied Complexity Coffee Group
<friam@redfish.com>
Subject: Re: [FRIAM] Magic Harry Potter mirrors or more?
Transformer architecture works because it's cybertronian technology.
And is so advanced as to be almost magic.
On Mon, Feb 27, 2023 at 3:51 PM Jochen Fromm <j...@cas-group.net>
wrote:
Terrence Sejnowski argues that the new AI super chatbots are like a
magic Harry Potter mirror that tells the user what he wants to hear:
"When people discover the mirror, it seems to provide truth and
understanding. But it does not. It shows the deep-seated desires of
anyone who stares into it". ChatGPT, LaMDA, LLaMA and other large
language models would "take in our words and reflect them back to
us".
https://www.nytimes.com/2023/02/26/technology/ai-chatbot-information-t
ruth.html
It is true that large language models have absorbed unimaginably huge
amount of texts, but what if our prefrontal cortex in the brain works
in the same way?
https://direct.mit.edu/neco/article/35/3/309/114731/Large-Language-Mod
els-and-the-Reverse-Turing-Test
I think it is possible that the "transformer" architecture is so
successful because it is - like the cortical columns in the neocortex
- a modular solution for the problem what comes next in an
unpredictable world https://en.wikipedia.org/wiki/Cortical_column
-J.
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