How late do you think Apple can come to that party and still wind up winning in the end?

Having piles of money when everyone else is lighting it on fire and a brand that would require quite the mistake to ruin gives you a long runway.

Is anyone really profiting from AI yet? I know Google basically saved their search monopoly but any one else?

> How late do you think Apple can come to that party and still wind up winning in the end?

In my view Apple is positioning themselves (once more) to win without the need of competing on fair grounds. They are late to this party, but their biggest asset is the control over the data and spending of their users.

The users WANT to use those services, and Apple is not ready to offer anything. But as long as they can be the "broker" between the user and such services (and most of all the deciding party!), they can sell the consumption of their entire userbase for revenue-share to the service-providers.

Their biggest risk (beside of stock-market impacts) is, that Apple users start to engage directly with such services without Apple being an intermediary party (using a browser or another device).

So their highest priority will be to keep the user entertained so they can continue profiting from their consumption until they themselves have arrived at the party.

Once they have arrived, they will start diverting profitable AI-tasks from 3rd parties back to their own services, leaving unprofitable ones to the then-integrated 3rd party providers

> Is anyone really profiting from AI yet?

...Nvidia? Did you just step out of a cryogenic chamber from 2008?

The datacenter business is booming right now, cutting-edge and efficient hardware is needed more than ever. Nvidia and Apple are the only two companies in the world with the design chops and TSMC inroads to address that market. Nvidia's fully committed and making money hand over fist; Apple is putting 2nm silicon in the iPad Pro and asking fucking consumers to pay $1,500 for it. Do you not see the issue with this business model?

People will say Apple can't crack the datacenter market, I say bullshit. Apple drafted OpenCL. Every dollar Nvidia makes is money Apple pissed away on trinkets like smartwatches and TikTok tablets.

I would be very surprised if it was publicly available.

Yeah, there's no way anyone would ask or it'd get approved for public release. Not because it's necessarily controlled information (though suspect it probably is), but what would be the point? Things get released to the public only when there is a particular need to tell the public something and everything else defaults to sitting on some janky ass SharePoint site until everyone forgets about it.

FOIA is a law for a reason

Given these blustering charlatans' track record with security, I would be very surprised if it was NOT publicly leaked, sitting somewhere on an open cloud server, put there by some petulant incel child who calls himself Big Balls.

Is the demand there at the price point and reliability levels that are currently possible?

That’s a very uncharitable interpretation of what they wrote, and goes outside of how what they wrote is supposed to be interpreted.

The researchers are not claiming that cognitive ability changes would definitely take longer than 21 days to appear, they’re suggesting that that is the next thing to test.

I would also encourage people to look at Podman desktop which has pretty good support from Red Hat.

https://podman-desktop.io/

Computer vision based SLAM definitely has use cases and you can definitely make money applying it at the right companies to the right set of problems. Building a whole career around a single technique, any technique, probably is probably not gonna work. You need to be broader than that.

I’ve worked on plenty of problems where all you need is to find what pixels are a specific color. While I’m sure a NN could be setup for that, why make things harder than they have to be?

Why harder? My point is, by using some DL framework, you would make this simpler. You don't need to have a big NN for that, or even any NN at all, and could still use some DL framework, and I would assume this is still easier and probably faster. E.g. finding what pixels are a specific color, this would be sth like:

    torch.all(image == torch.tensor([255,0,0]), dim=-1).nonzero()

To get all pixel pairs (x,y) where the color is red (255,0,0) of the image of shape (width,height,channels).

How do you generate the torch vector to do this? Often it's OpenCV!

torchvision.io.read_image?

This is like answering "the grocery store" when asked where food comes from.

I’ve found C# pleasant to write in, and I get a bad feeling every time I deal with npm. On the other hand the library support for React is just so much better so I put up with it.

EDIT: I’m not a web dev, the web is just the most consistent UI platform for supporting mobile and some desktop we have now so that definitely influences my opinion.

I looked before I started using Let’s Encrypt for some internal stuff and there really isn’t a way to use name constraints in a practical way with modern web browsers at this point. If you’re not using a browser, things get a lot easier, but for browsers you sort of got to suck up that you can’t really avoid the “big” internet.

There is a way, I've recently generated my own CA with domain name constraint, trusted it, and used it cross sign my company's self signed CA. It works like a charm.

I don’t think it’s really the opposite opinion.

To pick on the game of Go as an example, the insight from the Bitter Lesson is the best method to use for Go is probably going to be the most broad method that abuses the magic of brute force the most, compared to a method that really encodes the best existing strategies of Go.

I think what OP is referring to and what I’ve observed is that in some fields you have to have a certain amount of expertise to just understand the rules of the game, and there are a lot of applications where someone approaching a problem with the goal of applying ML can’t quite get over the hump of understanding all the rules.