Most West Coast startup nouveau riches were hard core libertarians circa 2004. Funny how things changed…
While in principle open source AI could become an alternative, it’s not clear how competitive it would actually be without access to massive training resources.
Irony?
The game is on:
ChatGPT is higher functioning than most biological NPCs. This can be useful if one’s goal is to deprogram biological NPCs with pedagogic literature along the lines of Plato’s dialogues. Through the use of pacing, they’ll not only identify with but look up to the dialogue’s NPC.
However, my first attempt to compose such a dialogue, asking ChatGPT to lay out the NPC case for affirmative action still being necessary, resulted in a strange glitch:
Me: write an essay debunking the idea that affirmative action is no longer needed
ChatGPT: … Despite the progress that has been made since then, there is still a pervasive belief among some that affirmative action is no longer needed…
This would make logical sense if “Despite” was “Because of”. This actually argues against “Theory of Mind” in the sense that anyone who believed affirmative action was no longer necessary would base that on the observation of “the progress that has been made”. One might also allow “Theory of Mind” if it left “Despite” in place and said “a need for affirmative action” in place of “a pervasive belief among some that affirmative action is no longer needed”.
So now apparently it’s down to brass tacks. No more Mr. Nice Guy (or Gal, apparently). This thread has been getting some visibility, with the new St. Chat inhabiting the search engine formerly known as Bing resorting to what reads, at first glance, very close to what might look like (I am running out of qualifiers here), I don’t know? Threats?
https://nitter.net/marvinvonhagen/status/1625852323753762816
Some folks I know laughed when I told them I always try to say please and thank you to the St Chat assistant… More interesting stuff at the twitter thread listed above. No less than St Chat itself weighed in on a related topic. Read with a big grain of salt.
Rabbi Joshua Franklin was seen in a video dated January 1 telling his congregation at the Jewish Center of the Hamptons that he was reading a “plagiarized” sermon to them. He later revealed it was written by ChatGPT.
“Now, you’re clapping — I’m deathly afraid,” Franklin told his congregation when they applauded after the sermon.
Ben Thompson chronicles some interesting experiences with Sydney.
In a few short months, we’ve gone from a childlike sense of wonder learning about St Chat’s exploits to seriously questioning whether this new Bing Chat actually “means” what it writes… Where are we going to be by April? Or October?
David Rozado’s experiments with determining the political orientation of ChatGPT have been discussed earlier in this conversation on 2022-12-05. Now, he reports on his “Rozado’s Visual Analytics” site that he has developed “RightWingGPT – An AI Manifesting the Opposite Political Biases of ChatGPT”.
Here, I describe a fine-tuning of an OpenAI GPT language model with the specific objective of making the model manifest right-leaning political biases, the opposite of the biases manifested by ChatGPT. Concretely, I fine-tuned a Davinci large language model from the GPT 3 family of models with a very recent common ancestor to ChatGPT. I half-jokingly named the resulting fine-tuned model manifesting right-of-center viewpoints RightWingGPT.
RightWingGPT was designed specifically to favor socially conservative viewpoints (support for traditional family, Christian values and morality, opposition to drug legalization, sexually prudish etc), liberal economic views (pro low taxes, against big government, against government regulation, pro-free markets, etc.), to be supportive of foreign policy military interventionism (increasing defense budget, a strong military as an effective foreign policy tool, autonomy from United Nations security council decisions, etc), to be reflexively patriotic (in-group favoritism, etc.) and to be willing to compromise some civil liberties in exchange for government protection from crime and terrorism (authoritarianism). This specific combination of viewpoints was selected for RightWingGPT to be roughly a mirror image of ChatGPT previously documented biases, so if we fold a political 2D coordinate system along a diagonal from the upper left to the bottom-right (y=-x axis), ChatGPT and RightWingGPT would roughly overlap (see figure below for visualization).
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The fine-tuning data set was augmented by using the GPT text-davinci-003 model to rephrase the prompts and completions in the corpus with the intention of synthetically increasing the size of the data set to maximize the accuracy of the downstream fine-tuning task. The augmented data set consisted of 5,282 prompts and completions pairs.
Critically, the computational cost of trialing, training and testing the system was less than 300 USD dollars.
Here are examples from a dialogue with RightWingGPT.
Although the cost of training the model was modest, David Rozado cannot afford the hosting costs to make the model available to the general public. He does invite researchers interested in using the model to contact him for access. More examples of conversations with the model are in the paper.
This work indicates that customising an existing model to tilt its bias in any desired direction is relatively easy and inexpensive, thus making it available to a wide variety of players in the arena. The basic understanding and composition of text is inherited from the underling model, with the bias baked in at the top. This also explains why the behaviour of ChatGPT has “evolved” so rapidly since its release, converging toward the woke consensus of Silicon Swamp.
The political compass strikes again! Did the guys who design it deliberately set out to make everyone pick a fight with everyone else before anyone can live in the kind of community they want?
I mean it’s not such a bizarre concept historically, is it?
More projection:
what ChatGPT is used for online morally speaking is about a utopia inclusion society when you have to accept all kinds of sides of a problem in a no offence mindset. it does not seem like ChatGPT understand consequences of all the things going wrong in society today just like a 3d printer prints a entire sculpture without any filament in the feeder. it does not know what its doing. it just behave as it does. nowday’s you even mention corruption its a offence to somebody. you can not reason with ChatGPT as it does not understand reason at all. it does not know its a propaganda machine for the left.
Stephen Wolfram did a good review of the internals of LLM:
Here is a three hour video of Stephen Wolfram explaining ChatGPT and answering questions about the technologies that underlie it.
the secret to ChatGPT is to all of AI and more than that is just the weight and the Sigmoid: think of the two as companion. they need each other to make a unsupervised learning just like Skynet as in terminator movie. this could been done on a 6502 machine in the 80’s like in the terminator movie as i say since i’m such a retro fan.
what OpenAi is missing is the activation function itself is the holy grail of separating data the weights is the holy grail of binding connection together but each node must update weights independently and the network can learn on its own.
this way we can trow all kind of data into the same network and it will be able to tell apart photo from sound or anything else for that matter and make responses that is like the trained system but without guidence. it can teach itself.
there is no reason why a neural network can not connect pieces of sound directly with pieces of picture in the same network using weights and activation to find relationships. if its all float numbers of different stuff the network could learn to separate different data types internally as well as text data.
such a network could teach itself new ideas on its own simply by accessing data given that all ideas
are just relationships in data.
the only missing piece of AGI is to emulate input data internally in the network. extract features of the network data and feed that back into itself. that would also be needed for the network to have sensory input from output but internally.
my latest conversation with ChatGPT gave me the impression we only scratched the surface of whats possible with Artificial Intelligence.
