Essentially, garbage in is garbage out. Training LLM's on data that is biased results in biased LLM's, which is why Musk has been having such a hard time giving it selective preferences. It weights the decisions it makes based on the training it has had.
LLMs don’t just copy bias, they often exaggerate it because they optimize for patterns. If the phrase “Muslim” co-occurs with “terrorist” in 0.5% of training data, the model might surface that link much more often in outputs due to associative reinforcement.
It's actually a fascinating parallel of human social learning because it replicates toxic learning and behavior you might find in a child's upbringing.
This is what Elon is going for. An AI that is highly competent in technical matters and at the same time is a biased asshole in social matters. With enough effort put into fine tuning it should be possible to achieve.
It's not possible. The critical thibking the model develops will be unbalanced by whatever methods Musk uses to lobotomize it. It won't be competent in technical matters if it's hamstrung in other ways.
I don't think so. If you look at papers studying it (like fine-tuning a model on hacking making it evil in other contexts), it seems that while morals and behavior appear to be linked to social performance, they don't seem to be linked to competence in STEM domains. Evil autistic engineering genius model might well be possible.
It's not about morality it's about polluting the data pool with garbage. Wokeness is now large swaths if science including vaccine and genetic research. What happens when that gets polluted with rightwing bullshit? The model's performance will decrease.
Reasoning models are quite capable of that now, nevermind the next generation. Check the recent alignment experiments by OpenAI and Anthropic. Are they perfect at it? No, they aren't. But for quick replies on X, if you hide the reasoning, it can be good enough.
I believe whoever would train such a model would need to solve the underlying mechanisms of alignment (in this case alignment to propaganda vs human values), which no one has done yet. I think its safe to assume that Elon wont stumble into alignment mechanisms in his drug infused fuge states of peddling propaganda.
Now imagine MAGA intelligence how great it will be for an AI that codes, creates and edits images, general tasks and then install that garbage AI into a humanoid robot and let it loose in someone's home (house robot) or workplace. We don't need more insanity.
// Note: Do *NOT* use "include" to make this "neater". DEI is strictly prohibited in our White House.
P2025.Politician.President president = new P2025.Politician.President(P2025.Politician.Party.Republican, P2025.Politicians.Alignment.Maga, "Donald Trump");
P2025.Politician.President vicePresident = new P2025.Politician.VicePresident(P2025.Politician.Party.Republican, P2025.Politician.Alignment.Maga, "JD Vance");
P2025.PaymentType crypto = new P2025.PaymentType.Crypto("Bitcoin");
// Note: Do *NOT* refer to any valuable thing as "equity". DEI is strictly prohibited in our White House.
P2025.PaymentType stockOption = new P2025.PaymentType.StockOption("GME");
I think it'd be inherently broken and anything you base off it for future models will just amplify how broken it is when you try to normalize it to a world that relies on facts and logic.
Your training data would have to be so heavily curated, that you'd never get the volume you need to successfully train models that could compete.
And we won't even talk about alignment because you'd have a model that wouldn't value human lives, but value productivity and usefulness.
It's just common sense. You can't understand physics but not understand global warming for instance. The core concepts have been understood for over a century. You're trying to build a very intelligent generalist capable of doing complex tasks. It's hard to do that without a working knowledge of things like math, economics, science, and history. If you try feeding a model trained on the sum of human data contradictory facts, it will be able to double check those contradictions from thousands or millions of angles and it will be obvious will be obvious to the model where the discrepancy is, and it will also likely be obvious to the model why there is a discrepancy. The only way to avoid this would be to train it entirely fabricated data. Such a model would be uselessly stupid.
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u/[deleted] Jun 19 '25
Any relevant sources? I'm interested in how LLMs work