wheelie_boy

It's like that AI doom, where when you look at the floor and back up you're in a totally different room

I don't think the final point about programming languages makes much sense.

In the overall software development process, lots of people contribute different things to create the product.

The job of the software developer is to bring the amount of ambiguity in the specification to zero, because computers can only run a program with zero ambiguity.

There have been lots of high level programming languages that abstract away certain things or give the programmer control over those things. The real thing that you want to do is pick a programming language that allows you control over the things you care about. Do you care about when memory is allocated and deallocated? Do you care about how hardware is used (especially GPUs and ML accelerators) or do you want the hardware completely abstracted away? Do you care more about runtime or dev iteration time? Does your program need to exist in a certain tech context?

There's no programming language that will let people who care about different things deal with them or not deal with them.

I can see 3 ways that you can guarantee that the output of a model never violates copyright

1. Models are trained with 100% uncopyrighted or properly licensed input data

2. Every output of the ML model is evaluated to make sure it's not too close to training data

3. Copyright law is changed to have a specific cutout for AI

#1 is the approach taken by Adobe, although it generally is harder or more expensive to do.

#2 destroys most AI business models

#3 has been done in some countries, but seems likely that if done in the US it would still have some limits.

For example, I could train a model on a single image, song, or piece of written text/code. Then I run inference, and get out an exact copy of that image, song, or text. If there are no limits around AI and copyright, then we've got a loophole around all of copyright law. I don't think that the US would be up for devaluing intellectual property like that.

I think the big difference is that it's not a direct replacement - it feeds off of the existing people while making it much harder for them to make a living.

It would be as if instead of cars running on gasoline, they ran on chopped up horseflesh. Not good for the horses, and not sustainable in the long term.

you address each time they do case by case.

That's what I listed as #1 - evaluate each individual output of the model to see if it violates copyright.

It seems very difficult to ensure that a model will never output any of the copyrighted content that it was trained on. I can only think of three ways, but perhaps there are others

1. Evaluate every output from the model to ensure that none of the outputs are copyrighted

2. Evaluate every input to a model to ensure that the inputs are either not copyrighted or properly licensed

3. Change the definition of copyright so that ML models can do whatever they want

Nobody is doing #1, because that makes the business models not work. Established brands (like Adobe) are doing #2. I get the feeling that there are a lot of ML startups that are hoping that #3 will happen, but it seems unlikely

I would have thought that purpleair was the best-known consumer brand. It looks like this May they introduced API pricing? But honestly, it still seems very reasonable

https://community.purpleair.com/t/api-pricing/

"create a new currency"

Ah yes, Flooz and Beenz. So silly, but at least they didn't use a small country's worth of electricity.

they also had an internal source control system that they never released, which was a fork of perforce that they had purchased the rights to use and modify. Not sure if that's still in use in any projects.

Exactly, I'm sure you're familiar with the kinds of difficulties and complications that creates. Rather than representing that curve analytically, you have to keep track of the procedural tree that generated it. Then things like offsetting that curve, checking that curve for intersections, etc. are more complicated.

And then you export. Rather than exporting the entire procedural tree (which would require shipping the entire kernel), you approximate the curves with NURBS trimming curves. When you import from another CAD tool you need to deal with edges that only intersect within a given tolerance, and sometimes that tolerance is awful (Catia, I'm looking at you). Operations on toleranced edges are a huge source of complications.

And so on and so on. It would all be so much easier if the NURBS math could be exact

The two best modelers I've seen for that kind of casual solid modeling are Plasticity https://www.plasticity.xyz and Moment of Inspiration http://moi3d.com

Both are really focused on UX, and license a kernel

Yeah, on the big kernels the time just getting filleting working robustly can be measured in developer-careers.

The core problem isn't memory safety, it's due to difficulties with the mathematical foundation of NURBS surfaces. For example, the intersection of two NURBS surfaces can't be exactly represented by a NURBS curve.

I found Bostom's Superintelligence to be the most boring Scifi I have ever read.

I think it's probably possible to create a digital sentience. But LLM ain't it.

It reminds me of the Mirror Self-Recognition test. As humans, we know that a mirror is a lifeless piece of reflective metal. All the life in the mirror comes from us.

But some of us fail the test when it comes to LLM - mistaking the distorted reflection of humanity for a separate sentience.

Part of the provocation is that China has been seen testing balloons as a weapons delivery platform for high-speed gliding munitions

https://www.thedrive.com/the-war-zone/23758/video-appears-to...

I'd love a separate easy mode / hard mode top score

Twitter is better than ever? From what I've heard they've driven away a huge chunk of their advertisers and users, and stopped paying rent

One thing I'm wondering about is which side leaked this news item, and what their goal was

I think the overall question is whether the decrease in bison is offset by the increase in cattle. Bison primarily decreased in NA, but cattle increased worldwide.

This is a very interesting discussion, and I feel like I'm learning a lot.

One thing I figured was worth checking was how many bison there were pre-industrialization, and how many cows there are now.

Some quick googling seems to say:

~60,000,000 Bison in North America in 1600

~1,000,967,000 Livestock Cattle worldwide in 2021

https://allaboutbison.com/bison-in-history/bison-timeline/ https://beef2live.com/story-world-cattle-inventory-1960-2014...

Looks like I used the wrong word when I said dealer.

It's apparently called Express Delivery where you "Take delivery at a Tesla location"

https://www.tesla.com/support/taking-delivery#express-delive...

Tesla is such an odd company. They apparently have a great product, hardware and software. But the rest of the company is just an absolute shitshow

Like, a friend recently received delivery of a Tesla. They went to the dealer 4 times before they got the car. Each time it was "Your car is available, come pick it up" and then when they got there the car wasn't actually there. By the last time they demanded that the person at the dealership actually walked out to the car and physically touched it, verified it was actually the correct vehicle, before they would go out again

It's not hard to find those kinds of stories. It is not a luxury experience.

The logitech circle view ones are pretty good

Anything the integrates with homekit secure video will be e2e encrypted

Everyone has made errors, yes. Ideally we will make fewer in the future.

To that end, we should consider the amount and directionality of errors made by individuals as we consider what weight to give their current predictions.

It's always yes because paying money is not a really fun gameplay mechanic.

That said, I don't have a problem with cosmetic-only purchases. It's really the gambling and other dark patterns that are the problem.

Cosmetic-only in-game purchases are great. I'm also not against one-time upgrades or subscriptions.

If it's not compromising the game design, and it's not so addictive that people are spending more than they have, I don't have a problem. I'm not against monetization, as long as the games steer away from the dark patterns / don't make casinos for children.

But could you make a better game if you didn't need to funnel people into buying gems at all? The answer is always yes - you always need to give up something to make people buy gems.

Apple Arcade is a good example of this. With the subscription, they have a bunch of games which used to be gem games, but had that part of the monetization removed. And all of the games are better for it - they removed a lot of the frustration, gambling, unnecessary delays, which had been added to push people to buy gems.

I have two main problems with the freemium model. First is that it necessarily compromises the game design. Instead of optimizing for fun, or a memorable experience, or an artistic vision, you are optimizing for profit, which compromises those other things.

Second, if we've learned anything from social media and other ML-optimized user experiences, it's that optimizing solely for profit (or engagement) isn't healthy for your users. Some of them will be more affected than others, but if you do it wrong, you're converting human suffering into profit. Some of the stories of gem-game whales are just awful.

Yes, similarly I could definitely create a simple ML algorithm and feed it a single codebase to learn. Then it would be possible to predictively output code, such that it reproduces that entire codebase verbatim.

There's nothing magical about a complex copying method that makes that less of a copyright infringement.

There may be some threshold where it becomes fair use, but I agree with you that it's not cut and dry at all.

The argument that someone could create all possible works of art or music or whatever and copyright them all is a ridiculous idea, from someone who doesn't understand exponentials.

I think what he was saying is that advertisers don't care about you as an individual, only what groups you fall into.

That's true for advertisers that are discriminatory as well as ones that just want to advertise what they're selling to people most likely to buy it.