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Pentagon used Elon Musk’s Grok AI to fire 2,000 missiles at Iran, official says
(www.independent.co.uk)
this post was submitted on 17 Jun 2026
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What I don't get is how a chatbot fires a missile...I mean you could give it a function call, but I don't think we're at that point of insanity just yet
Maybe it could read through Intel and recommend targets, but there's no way anyone is reviewing the research thoroughly, with the diligence appropriate before taking lives
Can we stop the bullshitting and call the media out on this more? This is obviously just offloading responsibility to an entity beyond punishment
A fourth grader could see the problem here... It's not if AI is or isn't competent, it's that the people involved are incentivized to blindly trust the AI. That no one is taking responsibility for, so really it's no one's fault when schoolchildren are slaughtered
The first completely AI-driven kill chain was confirmed several years ago, so I wouldn't put anything past anyone.
Yup started with hardware like Gorgon Stare, then machine learning for targeting data, then Anduril to collect the metadata from satelites and other sources. They stitch it together, send the package to an analyst for review and they decide if/when to pull the trigger. Sounds like that last part is just a butterbar responding to a Grok prompt now.
https://en.wikipedia.org/wiki/Gorgon_Stare
https://ndupress.ndu.edu/Joint-Force-Quarterly/Joint-Force-Quarterly-75/Article/577571/understanding-the-enemy-the-enduring-value-of-technical-and-forensic-exploitati/
https://freepress.org/article/anduril-s-lattice-now-army-s-drone-killing-brain-and-it-s-built-act-faster-human-judgment
https://arxiv.org/html/2602.13324
Surely the automated drone Torment Nexus will be a net benefit to humanity. We can hellfire so many Pakistani weddings now.
From what I have seen in the various articles and interviews covering this:
The idea is that "AI" is used to detect possible targets and "write the first draft" of the report suggesting a strike based upon available intel. It is then used to flesh out that "draft" into a full report. It is THEN used to determine which reports are valid. And THEN it is used to draft the orders to whoever is firing the missile.
And... much like with software development, there ARE some genuinely good use cases in there. "Traditional" inference models are spectacular for identifying the kinds of anomalies that could be troop movements or "insurgents". For close on 20 years now, it has been pretty trivial to hook up a few basic computer vision packages to county traffic feeds and cyberstalk your friends (or worse). Mostly because it is computer vision to essentially label clips and then pattern matching to... find patterns.
And... there are strong arguments for using LLMs to break full reports back down into weighted bullet points to accelerate the parsing and evaluation of requests for attacks. Which... mostly speaks to how maybe we should just normalize communicating in bullet points but...
The issue is, like it is always is, the humans. The folk who are going to use an inference model to identify potential targets? They probably aren't going to evaluate the results and write their own reports. They'll just generate them. And if they are the kind of person who can't be arsed to parse intel feeds OR write about them... are they the kind of person who is going to do an editing pass? And if nobody is writing the reports that are sent, why would anyone read them?
So the end result is everyone just smiles and brags about how their entire job can be done by a computer. And the only human intervention is that "somebody" should probably go in and add a weight to say not to target schools and hospitals but... someone else can do that.
Okay, but what does that mean? How does an llm do that exactly? What are the inputs and outputs?
Do you actually know, or did propoganda get you? No shame in it, if you hear something enough and it can worm it's way in without conscious evaluation
I think neural networksthat highlight suspicious movements are fine, or at least as fine as weapons of war are fine in general. But ideally, that's just battlefield information fed to humans, which isn't how this is spoken about in the media
But we're specifically talking about grok here. How does grok fit into the process of firing a missile exactly, and what are the incentives built into the system for the people involved?
You've got a decent grasp on the tech side, so I think if you consider the position of the stake holders you'll come to the same conclusions.
Put yourself in the position of the developers providing models, the brass and why they want this, and the MIC shareholders and what they'd lobby for. Think of these pressures, and ask yourself what kind of direction the project is pushed in
There's some pretty horrifying implications
Not an LLM. An inference model (which... we group in with LLMs these days because stupid).
Let's keep it simple and say you have access to a bunch of traffic cameras. You are on the lookout for... I dunno, let's say a handsome young italian american in a dark green coat with a face mask on.
Just apply that on a larger scale using satelite surveillance data, intel on known targets, etc.
Gonna actively ignore all of your obnoxious ad hominem in the attempt to have an actual conversation. Don't prove me the fool for doing so
Which gets us to LLMs. LLMs... are REALLY good at translating from one language to another. For most people, that is natural language (a prompt) to machine instructions that get fed to underlying software ("agentic models" if you want to use buzz words). For ChatGPT that is usually just a google search. Or it is a few bullet points that turn into a letter to Grandma. Or a question that is turned into a non-answer.
And then... the rest is exactly what I said. "Find me all instances of General Whatshisface" is a query that would map to a database lookup that would use the already labeled (either through computer vision or a human analyst) data to find General Whatshisface. And then it is exactly what I said above