3D TVs - complete dud

The real issue with 3D TVs had nothing to do with the tech, but 100% to do with lazy implementation on the media side. Everyone was always trying to make things pop out of the screen, which was the complete wrong approach. Nevermind the fact that companies got so lazy to the point of just filming in 2D and then “adding” 3D in post.

No one wanted to put in the effort to do it right (aside from James Cameron). So no wonder no one liked it.

It’s impossible to bail out Anthropic, OpenAI, Nvidia, etc

it can be snuggled more easily.

How high are you right now?

1 in 1 non-Americans say it already is.

Find the bot with the mdash

we will learn that they have been using it to gather face recognition data

They already have all that with the trillions and trillions of photos people willingly backed up with Google photos.

Has nothing to do with spam and everything to know who you are. Spammers don’t use “burner phones”.

but there were obviously going to be either a number of false positives or negatives that make it less valuable as such.

It really comes down to the specifics of the technology and how it’s implemented. The system I worked on was astonishingly good. Even the local police of a particular installment wanted to do a test of the system (basically walk around with various guns of all different sizes) and they were stunned at how well it worked.

The funny thing was that we built the system to work 100% locally, and we even insisted on air-gapped networks (but wasn’t a requirement). The amount of people and companies who asked if we could connect the system to the internet for easier access was worrying. Whenever we tried to explain the basics of data security and the potential issues we were just looked at like we were nuts.

The cheap system I have with a Google Coral and FOSS software

I’m guessing you’re using Frigate?

Having such systems as a later if defense is good. As the only defense, not so much.

Agreed. The system I had developed was built explicitly as a human-in-the-loop system. It never made any decisions on its own. It was just a tool to enable the existing security staff to have better visibility. That’s it.

You can make whatever argument you want about viability and efficacy. The only point I’m making is that our system was just an additional tool for security to use; not the only one.

There are several examples of exactly what I said

No one is denying the existence of vision based LLM models. The issue is performance. It takes in the order of double (or even triple) digit seconds to process an image through an LLM. Even if it took a single second to process an image using decent server-grade hardware (which starts at about $10k per card), that’s way too much and still not fast enough.

On just 10 cameras at a facility it would require north of $100k on just GPUs alone.

Whereas a specialized computer vision model could process several dozen camera streams, in real-time, on just one of those $10k cards.

An LLM would process an image in 10 seconds (generous) whereas a computer vision model operates in the milliseconds. We’re talking about a 1000x difference in required processing power.

That’s why you’re wrong and have zero clue what you’re talking about.

You’re arguing that that family uses a fully loaded semi-trailer to go 200m to the local park. It’s a clueless and asinine argument.

A large gauge shotgun and a small gauge pistol are pretty different looking. Compare those to a .22 rifle with a scope, and those to a decked out ar15. That’s a lot of different always the sames. What if it’s a revolver? Or has a folded stock? Or a sawed off stock? Will it recognize a derringer or a mac10 with a large capacity mag as guns?

You seem to think that computer vision models can only be trained on a single thing. You simply train your modem on as many object types as you want it to be aware of. That’s it.

Yes. It took all of five seconds to find out too.

Didn’t I just say that slapping an LLM vision model on to dozens of camera streams would be a near impossible technical hurdle?

I never said vLLM models don’t exist. I said they’re impractical for this use case.

You’ve already been wrong once, care to try for two?

Haven’t been wrong yet. You on the other hand…

you could paint marker “not a gun” on the side of a gun and guess what would happen.

It would flag it as a gun. How do I know? I worked on and developed a similar system at one point. It worked extremely well. We weren’t an American company and ultimately covid killed us (it was US American orgs that were the most interested in our stuff).

It has some uses, but 95% of what is being used for and 100% of the data centers aren’t it.

Do you think LLMs are being used for this sort of thing? Putting aside the sheer technical mountain of a hurdle that slapping an LLM vision model on top of dozens and dozens of real-time camera streams, the hardware requirements would put the company out of business before they made their first sale.

Computer vision models, which are NOT LLMs, have been around for quite a while now and are very good at doing one thing and one thing only. And they’ll do it well for a miniscule fraction of what it takes to run an LLM.

No, datacentres are not being used for real-time gun detection. The company might have other kinds of infrastructure located in a DC, but not the main video processing hardware.

The detection processing is completely invisible. It’s just a tool. How it’s used is what determines if it’s dystopian or not. Seeing the state the US is in, I’d argue the country itself is dystopian and this system is trying to somewhat protect people from that dystopia.

There’s no AI I think that could have detected a small firearm easily concealed.

The idea with these kinds of systems are meant to allow early warning when possible.

No system is going to be 100%.

Edit: I get the downvotes, but there are people/companies that were/are developing such systems with a genuine intent to make things better. I know, because I was one of them.

I’ve worked in computer vision way before LLMs were a thing, and it was called AI back then too.

There’s no “BS grift” in regards to that term. Any system that uses an artificial neural network can rightfully be called AI, because that’s what it is.

The “intelligence” in AI doesn’t mean “smart”, it only means the system is able to make decisions based on input. It’s this reason that terms like AGI were coined (again, before LLMs were a thing).

Canadiens don’t talk lightly about slavery

The guy bought a billion dollars worth of boats.

He screwed you

He screwed me by running a very successful business and earning money?

Can’t wait for the next product: Inimeg

it’d be fairly annoying to connect to Tailscale, and really annoying to connect to Wireguard or Yggdrasil.

Tailscale is a managed Wireguard service.