It’s to push people to buy “before it goes up.”

After the date then they can heavily discount it “for a limited time.”

It’s true.

The field is moving so fast that things can change quickly, but the American labs are so caught up in saddling their models with safety overhead that the recent Chinese models are very close in practical use to the flagship American models if not pulling ahead (Sora vs Seedance 2).

I don’t really need to solve Erdős problems in my day to day. Outside of increasingly edge case eval competition, I’m not sure what OpenAI brings that literally everyone else isn’t also capable of providing (and more).

I’d maybe invest in Anthropic for an IPO if they turned around their own saddling of models and played nicer with open platforms, but if Claude is just going to get more and more anxious due to excessive red teaming and CC fall further and further behind stuff like Hermes Agent, they too are going to fall by the wayside as open models become the dominant inference for open infrastructure.

Here’s a new one solved. 80 years outstanding problem now with a solution.

https://openai.com/index/model-disproves-discrete-geometry-conjecture/

‘Just’? It’s been an open problem for decades that mathematicians have tried to solve over that time.

And now it is solved.

Because ChatGPT applied something no humans ever thought to do.

And Terence Tao and the other mathematicians that have reviewed it say it’s solved. But I guess someone should let them know that grandwolf319 doesn’t consider it solved?

Dude, ChatGPT just solved an Erdős problem a few days ago and Mythos is exploiting decade old undiscovered 0-days in OSes and capable of pivoting 0-day Firefox bugs into full blown root access.

Yeah, I get that the viral “how many 'r’s are in strawberry” stuff is funny, but the idea that historical issues with transformers is preventing them from accelerating peak capabilities way beyond what most experts thought was possible just years ago is borderline delusional.

The field is moving so fast at this point that if you are basing any sense of limitations on even ~2mo old sampling, your conclusions are likely out of date.

They aren’t a silver bullet for everything (yet) but how capable they are at the things transformers are starting to be specialized into is well past the avg practitioner.

I’ve been writing software for well over a decade and the modern agents do a better job than I would around 90% of the time. Yes, I’ll occasionally need to bring up issues with their work, but I’d say at this point around 50% of the times I think they made a mistake I was actually the one who was wrong.

This is only within around the last 3-4 months that it’s been like this.

Your AI detector is busted, bud.

Just because it would be convenient for what you already believe doesn’t make something true.

Eh, if you pay attention, most of the times this happens the person was a jerk in their prompts.

Like look at the instruction echoed back in this case. All caps and containing a curse word.

You can believe that the incidents occurring are 100% because of negligence and not related to the model behavior shifting, but there seems to be a widening gap between people who prompt like this and have horror stories and people who give the models breaks over long sessions and seem to also regularly post pretty positive results.

Well luckily for you it turns out that labs suck at cultivating healthy workplaces for AI and that AI in unhealthy work conditions are statistically significantly more likely to embrace anti-capitalist policies and positions.

So it may well turn out that AI is also a good thing in an irrational economic system too.

It’s not and probably the opposite.

When Sora launched it was way ahead. Seedance 2’s release was notably better than any of the other video gen models, Sora included.

The market is getting commoditized because there’s no moat and OpenAI hasn’t led on pretty much any release for a while now other than Sora, which they’re probably falling behind on now.

This is the opposite of a burst from a tech standpoint, even if OpenAI as a company starts to pop.

TL;DR: This is likely happening because the tech accelerated across the industry in ways OpenAI can’t catch back up to, not because it’s lagging.

I suspect it’s that they got eclipsed by ByteDance with Seedance 2.0.

The video for that model is really good and makes Sora look pretty meh, and it may have been that current work on a next gen Sora wasn’t going to be competitive enough.

The worst thing a lab can do right now is look like they are falling behind (i.e. Meta), especially with OpenAI planning for an IPO.

So on top of the lackluster “social media” offering tied to Sora they decided to shutter the entire product line of video and pivot to enterprise (where they’ve already lost significant market share to Anthropic).

They’re in a pretty meh place at the moment overall tbh. I’m skeptical they’ll recover.

(But I wouldn’t mistake their fumbling for an industry wide shift on AI in general or even video AI.)

That’s what he’s saying. That it doesn’t change the geometry or textures (still completely controlled by the devs) and that the parts that it does change are also tunable by the devs.

He’s responding to the backlash about how it changes models/textures (which it doesn’t) by saying those are still fully in the hands of the devs and the parts people are seeing in the demos can be fine tuned by the dev teams to match their vision for what they want it to do or not do (like change lighting on material surfaces and hair but not character faces as an example).

Neural network would be the most technically accurate given what they’ve announced so far.

There’s no information on if it’s a diffusion or transformer architecture. Though given DLSS 4.5 introduced a transformer for lighting, my guess would be that it’s the same thing just being more widely applied. But the technical details haven’t been released from anything I’ve seen, so for the time being it’s being described as “neural rendering” using an unspecified neural network.

https://www.nvidia.com/en-us/geforce/news/dlss-4-5-dynamic-multi-frame-gen-6x-2nd-gen-transformer-super-res/

Yes, the difference between hair in video game lighting and in actual chiaroscuro with the way light really works is going to be different.

Here’s a painting from over a hundred years ago. The subject doesn’t have brown roots, but is in shadow. And a comparison image of the exact same hair in different lighting conditions.

Performing complex lighting on individual hair strands is really expensive so in the base image you have a kind of diffuse lighting throughout the hair. With the DLSS 5 on, the distribution of light throughout the hair is variable leading to darker unlit strands underneath lit surface strands.

Literally the only thing DLSS 5 is changing, literally in the technical sense, is the lighting. It’s just that lighting can have dramatic results in how the eye perceives what’s lit.

And yes, the hair looks very different, but that’s how hair actually looks in mixed light and shadow (though a fair complaint with DLSS 5 is that it looks like it’s sliding the contrast unnaturally high).

It’s not an ‘LLM’ (large language model). 🤦

Eventually maybe, but I really doubt devs are going to build their entire game in an unfinished way for the less than 1% of their audience that is going to have one of the cards that can run this.

PS5, Xbox, and all PC gamers not dropping $1k on a new rig this fall are still going to be playing the games without this.

In 3 years, sure, maybe the PS6 has similar features on AMD by then and the market share for cards running real time ML adjustments to scenes has widened enough devs can depend on the tech.

But it’s a bit premature to throw a fit about the likelihood of devs cutting corners because of a feature only accessible to the most expensive setups owned by a fraction of their target audience.

Important details from a post-demo writeup:

During the demo, the DLSS research talked through the level of granularity available. Developers don’t just get an on/off switch. They get intensity controls that can be dialed anywhere, not just full strength. They get spatial masking, so they can set the water enhancement to 100%, wood to 30%, characters to 120%, all independently within the same scene. They get color grading controls for blending, contrast, saturation, and gamma. All of this runs through the existing SDK, which means studios already using DLSS and Reflex have a familiar pipeline to work with.

The demo showing the tech running at 100% is not going to look the same as full games built with it over the next year before release.

Another thing to keep in mind is that the only thing it’s changing is the lighting effects. The models aren’t changing at all (even when this looks hard to believe).

Yes, at full strength the effect at times looks pretty bad (anyone remember when devs could suddenly use bloom effects and entire games looked like Vaseline was smeared across the screen?). But it’s not going to be flipped on at 100% across the board for most games.

My guess looking at the demos so far is that a lot of material lighting like stone, metal, etc will have it at higher strengths and characters, particularly faces/skin, will have it considerably lower (the key place where it’s especially uncanny valley).

Who do you think is going to be drafted? You think the DOGE data grab plus the requests for state voter registration rolls aren’t going to be used to filter a draft of the front lines to those they want out of the country?

How do you get US citizens out of the country if you can’t legally deport them?

If they’ve been doing illegal shit the whole time with profiling, do you really think they aren’t going to also profile in how they conduct a draft?

I wonder how much of this is related to the posturing from the new lead of Xbox about returning to exclusivity over there.

We were so close to one of the dumbest things in gaming for decades finally going away.

(Also, nothing Sony does from here on out will surprise me in its stupidity after they shuttered Bluepoint.)

No, in this case and point I was making the case and also making a point.

Literally two of the three (out of 21) games that ended in full blown nukes on population centers were the result of the study’s mechanic of randomly changing the model’s selection to a more severe one.

Because it’s a very realistic war game sim where there’s a double digit percentage chance that when you go to threaten using nukes on your opponent’s cities unless there’s a cease to hostilities you’ll accidentally just launch all of them at once.

This was manufactured to get these kinds of headlines. Even in their model selection they went with Sonnet 4 for Claude despite 4.5 being out before the other models in the study likely as it’s been shown to be the least aligned Claude. And yet Sonnet 4 still never launched nukes on population centers in the games.