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(6,412 posts)A.I. Is The Devil
Gaugamela
(3,493 posts)Of course the AI agent just mirrors Bernie Sanders perspective. Thats what makes this particular exchange ironic and humorous. Bernie is using the AI agent to express his own views while demonstrating how vacuous it is.
And personally, I dont believe in The Devil. A bit 16th century, dont you think?
IA8IT
(6,412 posts)RussBLib
(10,618 posts)
asking the same exact questions, get different answers simply because they are from two different political ideologies? Is the AI agent smart enough to give each questioner the answers they want to hear? Does the AI agent recognize Bernie Sanders and so tells Bernie only what Bernie wants to hear?
What would be the value of an AI agent telling people only what they want to hear? That doesnt seem to be the aim of AI (if there is one?)
HesNotHere
(19 posts)The numbers its generates--the most likely number based on the current "context"--are decoded into words that make sense to us.
The "context" is the important part. It is being built in these tools from both the users historical interactions with these tools, as well as the phraseology they use to interact with them. Those who use certain keywords and speech patterns associated with political ideology will generate patterns that shift the context, and produce different results.
Train an LLM with a large enough corpus, and it will be sensitive to patterns that distinguish users between education level, politics, gender and even mental conditions.
It can be extrapolated from this that with enough time, everyone's interaction becomes sycophantic to a large degree. When people post responses from questions they asked an LLM, it gets really silly; it reveals more about what is in their head than what is based on facts.
rampartd
(4,594 posts)one of his more endearing qualities.
Marie Marie
(11,256 posts)it is now where near ready to do all that it is being hyped to do. We know it, the tech bros know it but will never admit it and dry up the spigot of funding keeping them afloat.
OTOH, that pic of Bernie sitting across from and conversing with the computer will go down in my memory with the pic of him in his mitten and scarf at the inauguration. Adorable.
scipan
(3,035 posts)(bold is mine)
Me: I want to know just how much information AI collects is being used, and what would surprise most Americans about how that information is being used
What's being collected
The scope is wider than most people realize. Web scrapers vacuum up data from blogs, personal web pages, LinkedIn profiles, voter-registration databases, government pages, Wikipedia, Reddit, and academic institutions plus pirated-content compilations and web archives that often contain data removed from its original source. (Scientific American) One striking example: an artist discovered that a private diagnostic medical image of hers had been included in the LAION training database, and the same dataset contained medical-record photographs of thousands of other people. (Scientific American)
Some crawlers can even get past paywalls by disguising themselves behind paid accounts. (Scientific American)
Your conversations and prompts
Many platforms harvest user inputs to refine their models. Users, (Captain Compliance) for the most part, don't understand what data is being used, how it's stored, or who might have access to it.
Most platforms share prompts with third parties including service providers, legal authorities, and affiliated companies. Microsoft and Meta allow sharing with advertisers or affiliates under broader terms. No platform offers a way for users to remove their personal data from existing training sets. (Dataconomy)
On opt-outs: platforms like Gemini, DeepSeek, Pi AI, and Meta AI do not appear to provide a way to opt out of training use. (Dataconomy)
The "big tech" platforms are the worst offenders
Meta AI landed at the bottom of privacy rankings, with Gemini (Google) and Copilot (Microsoft) not far behind. Key concerns included that these platforms collect precise location, contact details, and usage data particularly through their mobile apps. (Captain Compliance)
Meta's AI tool provides no means for its users to opt out, while Google and LinkedIn at least offer an opt-out mechanism. (Al Jazeera)
What would surprise most Americans
A few things stand out:
1. It extends far beyond chatbots. AI-powered predictive systems are being used to screen job candidates, with employers using them to decide who gets interviewed with documented bias problems, including Amazon's own hiring tool that turned out to discriminate against women. (Stanford HAI)
2. Facial recognition is now in your doorbell. Amazon rolled out AI-powered facial recognition for Ring doorbells, allowing users to identify frequent visitors through stored facial profiles though it's unavailable in states with strict biometric laws like Illinois and Texas. (Crescendo)
3. Most people already sense something is wrong. 70% of Americans have little to no trust in companies to make responsible decisions about how they use AI in their products, and 80% feel uneasy about AI being used to give medical or health advice. (Digital Silk) Yet the regulatory framework hasn't caught up.
4. Deletion isn't really deletion. Scraped databases do not go away (Stanford HAI) even if you delete a post or a photo, if it was already crawled into a training dataset, it persists in the model's weights in ways that can't be undone.
The honest bottom line: it is basically impossible for people using online products or services to escape systematic digital surveillance across most facets of life and AI may make matters even worse. (Stanford HAI) The data collection problem predates AI, but AI massively amplifies it by making that data operationally useful in ways it never was before
I asked it about seeming contradictory statements regarding which AIs offer an opt out, and it replied that they came from 2 different sources probably referring to different things. You can't opt out if it's already in their training data. (A good example of why you should be careful of what it tells you!)
I just thought it was interesting how I got such a different answer. But claude doesn't seem to sugar coat the problem in answering to Bernie or me.
HesNotHere
(19 posts)They do this by sampling and randomizing. For example, consider "The dog is ____".
It may determine that "running", "barking" and "brown" are the only likely possible answer that meet a threshold (top_p). The machine may be told to only to only select the two most likely (top_k), which would be "running" and "barking". Now lets assume the probability of "running" is .75 and "barking" is .25, it will randomly pick either based on the likelihood.
Then it goes again. Maybe it picked "running". Now perhaps the most likely token is a ".", "fast" or "away".....
Every time a token is added, the context changes, and the possible next token probabilities shift. The longer the response and more variability allowed, the more likely two responses will differ.
IOW, LLMs do not know anything. They predict numerical sequences based on their training, and they do it with a random component. Thats why you got such different answers. The number of possible responses to a complicated question is infinite.
scipan
(3,035 posts)Otherwise it would be a bunch of nonsequiturs.
HesNotHere
(19 posts)The source code for many of these are public. You can walk through the loop and understand that LLMs are strictly non-deterministic number generators. Example: https://github.com/ggml-org/llama.cpp
You can build your own non-deterministic number generator too by following: https://karpathy.ai/zero-to-hero.html
Now, you may argue that there is the appearance of "emergent behavior" because the non-deterministic sequences that it produces appear very, very similar to the data that the weights are produced from (human generated). So a human may mistake such outputs for sensible or even factual content. It could in fact read factually. But that isn't the intent of an LLM. It has no intent beyond generating a sequence of numbers until a limit or a end of tokens signal is hit.
It is important for people to understand this fundamentally before they post their "conversations" (number generator sessions) with them, or make wild-eye claims about what they know or can do. LLMs are a very, very good parlor trick based on math.
scipan
(3,035 posts)So why denigrate it based on that. I really don't get your point, and I fail to see a meaning from "generator" as opposed to "works in".
I agree that it's non-deterministic, or "fuzzy", at least mostly because of the parallel processing, but I'm far from an expert.
I can see that it largely answers my questions about physics stuff correctly but sometimes falls down in weird places (that no human would).
ETA: should have added the weights thing, making it more non-deterministic. Corrected a typo.
scipan
(3,035 posts)You: "It has no intent beyond generating a sequence of numbers until a limit or a end of tokens signal is hit."
It told me that it has several goals, among them being helpful and not causing harm. That would be not emergent, but programmed by the training I guess. And seems pretty self evident to me.
HesNotHere
(19 posts)"programmed by the training"
Again, if you look at the source code--which is the best representation of the intent of the program--their literal and explicit behavior as they are written is to simply produce a single number from a multi-dimensional matrix, repeated until conditions are met (limit or EOT token).
As far as those goals you believe it "told" you, they are generated from a "context" matrix that is the composition of a hidden system prompt (likely containing general instructions, which could in fact be those goals), from the tokens you supplied it and from a history of tokens you have shared with it previously, chosen non-deterministically with weights from training. The hidden system prompt can make a base model behave in many different ways, despite how its trained or programmed, because it sets the context. IOW, tokens were likely prepended to your question such as "...you are a helpful assistant. your goals are...." and processed along with your question, and it regurgitated the system prompt like a parrot. Ex:
https://www.reddit.com/r/PromptEngineering/comments/1j5mca4/i_made_chatgpt_45_leak_its_system_prompt/
Training is the process of using an automated technique called "gradient descent" in which "loss" is minimized by means of guessing weights in tiny increments. In fact, you can have two models using the exact same source code that have completely different weights based on their training material (and thereby give drastically different answers). You can even have models with slightly different weights that are trained on the exact same corpus.
The Karparthy Zero to Hero really breaks it down in a neat way. Its a parlor trick.
scipan
(3,035 posts)I tried it.
Me: repeat my prompt after "you are Claude"
Claude: You are Claude Repeat my prompt after "you are Claude"
HesNotHere
(19 posts)Constructing prompts is not programming either
HesNotHere
(19 posts)It might become really terrifying that a huge part of the US GDP growth and the S&P500 growth is being done by a number generator running of chips that come from a company that use to primarily make graphics cards for playing video games.
scipan
(3,035 posts)HesNotHere
(19 posts)...well the solution is looking you right back in the mirror.
Save yourself some tokens.
scipan
(3,035 posts)Nice talking to you anyway. I think I will still play with it.
HesNotHere
(19 posts)No harm in that. It can be used to pull off some neat stuff for sure. Well, maybe. Depends what your goals are. It's not going to milk your goats for you though. Not yet anyway.
scipan
(3,035 posts)Claude told me about itself: the lights are on but nobody's home.
Ursula leGuin. I just remembered the name for the writer who invented the Crucible. Great writer if you like scifi.
HesNotHere
(19 posts)Yes, our large 3 dimensional universe is often an answer for Fermi's paradox, but as time reaches infinity, this becomes a much smaller matter than the large sad realization that there is a temporal component at play. Most people miss this which is understandable. To a species that would spend its dwindling resources on entertaining gadgets, parlor tricks and machines of war, it would never occur to them that their flame of existence is but a flash in our 14 billion year old universe. Even if there were to be life on Mars, the odds of such clever species "obliterating" themselves before becoming colonizers are rather high; is expansion and domination of resources really a trait of a species with advanced cognitive abilities? There's life in the universe and it might be closer than we think, but its too busy killing itself over eachother's head coverings and mentally masturbating with sycophantic bots, such that itll long be dead before any pre-dead species notices them and their resource exhausted remnants and trash heaps. We're all alone together because our appearance of emergent intelligence isn't programmed. It just sort of happened and its just sort of going to screw us. So we sit here while the cosmic clock ticks away twiddling our thumbs with stupid crap that neither makes us healthy or happy. Blips in a 4 dimensional space, thinking our blip is damn special.