rlt

IMHO our best hope is some benevolent grey hat or government organization unleashes a well-aligned AI botnet to patch everything it can find before the black hats do.

This a joke, right? RIGHT?!

There's an obvious tradeoff between range and "flight" time, but if you ask your favorite AI it will do some napkin math for you that shows a 4 cold gas thruster system with a 3 foot diameter COPV (at pressures attainable by an onboard compressor) could hover a ~4000 lbs vehicle for a few seconds.

Landed on it like 3 clicks in and immediately closed the page.

Came here to post this, though I do have concerns about what will happen when very cyber-capable models are small enough to form a self-replicating worm...

> At least, they do until they wear their tyres to the point they disintegrate while driving

I don't think anyone who knows tires wear out thinks Teslas have special tires that don't wear.

> A mechanically illiterate public coupled with effective marketing is a dangerous combo when they're flying around in 2 tonne boxes still filled with wear parts.

Good news: Teslas will tell you when you do need to do the little maintenance that is required, including worn tires.

I believe it's the only, or at least first, car that measures tire wear by comparing GPS distance traveled to wheel rotations, accounting for tire pressure.

They need brakes changed far less often due to regenerative braking.

No, and if you are you’re not familiar with how SpaceX operates.

Plus, VLEO (<400km) is only really economical at scale with Starship, or at least Falcon 9. Without SpaceX no one would be using it anyway.

Pretty sure the majority reaction to this article is not what the author expected. He should probably refrain from w̶h̶i̶n̶i̶n̶g̶ writing about his job publicly.

So... an even more intelligent LLM.

But it does beg the question, could Anthropic and OpenAI make a ton of money by using their best models to trade before giving them to the public? It would probably be a deeply unpopular move.

"As part of developing the secure digital negative, PCC computes a confidence score that assesses whether the image has the physical characteristics expected of raw output from our camera sensors. Before the developed reference image is signed, PCC sends the photo GUID, sensor ID, and this confidence score to a companion service, which records them and updates the running score associated with that sensor."

I wouldn't be surprised if it's also possible to detect the differences between a photo of a real scene and a photo of a monitor or printout displaying a photo of a real scene, given they have the raw sensor output.

Not sure if they're doing anything like that.

Sounds like a great use of AI.

Presumably some of the proofs will have applications beneficial to humans beyond impressing other mathematicians, and AI will surface them, or use them directly.

Kind of missing the point.