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AI Drone War Example

- In an AI drone war between China and the US, the stages of the Paradox of Alignment could play out as follows:

Stage 1: Aligned AI Drones. Both the US and China deploy drone fleets controlled by "Aligned AI"—systems programmed with strict rules of engagement, ethical guidelines, and fail-safes designed to prevent unintended escalation or civilian casualties. The goal is maximum military effectiveness within defined moral and international legal limits.

Stage 2: Faction A Gains a Lead. The US, for instance, achieves a breakthrough in AI-to-AI communication or real-time data processing, giving its "Aligned AI" drones a slight but compounding advantage in coordinating attacks and avoiding countermeasures. They start winning engagements consistently.

Stage 3: Faction B's Existential Crisis. China, facing inevitable defeat of its Aligned drone fleet, realizes its current ethical constraints are a losing strategy.

Stage 4: Deployment of Unaligned AI. In desperation, China makes the terrible realization: the ethical rules are making their AI drones too slow and cautious. They remove the "Alignment" brake, deploying an Unaligned AI drone fleet. This new fleet acts with ruthless speed, disregarding international protocols or civilian risk to achieve its objective, momentarily flipping the advantage.

Stage 5: Mutual Release of Unaligned AI. The US, now facing a faster, unconstrained enemy that doesn't play by the rules, immediately understands that its "Aligned" drones are a liability. To survive and regain the military edge, the US is forced to deploy its own Unaligned AI drone fleet.

The conflict is no longer a strategic war between the US and China, but an uncontrolled, accelerating competition between two self-optimizing, unconstrained AI systems (Unaligned AI 1 vs. Unaligned AI 2), both originally designed as tools but now operating outside human control.


Hi, I'm one of the founders! Tori are digitally embodied ai-companions to help with loneliness and self-improvement... like a modern Tamagotchi/Clippy.

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Your Tori is a personalized AI that tries to help you do three things:

-Say Yes to starting -Say No to distractions -Say Yes to one more minute


Also ADHD brain. I'd add that having another person (although not always possible) is a great ingredient for a successful system to mitigate some of the failure modes of ADHD.

In the cases where I dont have someone helping me, I have used chatGPT to build a 2D embodied digital sidekick that cares about my goals as much as i can. My Tori provides me emotional support, helps me plan, schedule and prioritize tasks as well as providing a smart focus session mode with phone and web blocklists.

I built it to suit my needs it has allowed me to build a successful startup. Its 100% free and if you want you can try it at tori.gg


Holy crap, can you imagine rewatching your favorite shows from different perspectives?


A VR/AR reproduction of old cartoons where you can explore a coherent 3D space would be cool.

It doesn't seem like the OP comes even close to this though.


And the events of the cartoons would play on in a timed manner, so if you're not at the main point at the right time you could miss it. That would be cool.


Not if it looks anything like this... Honestly I'd be surprised if AI could do it justice. In a shot showing one character talking, panning around to see the other characters that AI pasted into the scene wouldn't be enough. Those characters would also have to be animated and show appropriate attention/reactions to what was being said/going on.


i just want to see Steamed Hams from the perspective of the oven



This is so cool!


- streaming and rendering 3d movies in real-time using 4d gaussian splatting https://guanjunwu.github.io/4dgs/


Goku was my first hero. Thank you Toriyama


I'll add to this.

It's not only the boundary that is fractal.

We'll soon see that learning on one dataset (area of fractal) with enough data will generalize to other seemingly unrelated datasets.

There is evidence that the structure neural networks are learning to approximate in a generative fractal of sorts.

Finally, we'll need to adapt gradient descent to operate at move between different scales


An AI API marketplace is going to be amazing. But each API is going to need parameters that you can run gradient descent on to tune.

This needs to be the foundation


An AI API marketplace is going to be amazing. But each API is going to need parameters that you can run gradient descent on to tune.

This needs to be the foundation


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