Assuming this means AMD wants to jumpstart competition with NV on a model/simulation ecosystem (which NV has been doing for ~a decade). Probably has at least something to do with NV acquiring HF.
I'm not sure how much things like Omniverse are used, but NV has put out some really interesting stuff in the space (like for example ARTY for a somewhat recent example).
Overall it seems like a financial vote of confidence for "world models" (whatever that means, I still don't know). But it could also mean the death of the interesting things WL was doing with Marble + Atlas. It's hard to read PR.
Honestly, I think this 'billion' number is also just the ball park for companies you need to pay if you want to buy them.
OpenRouter was sold for 7.5 Billion.
Lets just accept, that these people don't evaluate a company by value but by magic market "what is a sum someone needs to pay for buying a company and what company is somehow worth it to actually buy for this type of money but more in a sense of adding this to your portfolio"
AMD grew their revenue 50% last quarter from the year prior, for 11.5B in revenue. If this team can help continue that or grow that then yes - the amount of money involved here is insane.
I don't know about the training, but in terms of the the 'a lot of data', probably one of the inputs would be something like the geospatial data that Niantic has collected from all of the world's Ingress and Pokemon Go players, correlated with other more basic mapping data and things like google street view type camera data.
> Neoclouds want to do neolab things and now chipmakers want to do neolab things
We don't know what the right integrations are. Is it the chipmakers with the toolmakers? The front-end makers with the model designers? That's the current set-up. But there might be another industrial configuration that is superior.
AMD is still struggling to establish itself in AI. That makes it a worthy competitor. Its agglomeration of talent and resources is probably, knowing little else, good.
AMD has made ~5-10 acquisitions over the last few years and not all of them would qualify as "world class ML researcher". That's my point - they're on a shopping spree.
AMD has acquired "AI stuff" for several billions at this point, yet somehow, doing "AI stuff" on their GPU/NPU stack still seems to be troublesome. Well, that is what I read from others anyway. Inference with llama.cpp on AMD GPUs pretty much just works.
Who says that? I’m having a blast with rocm powering my R9700. Been able to run all models on day 0 at comparable speeds to Nvidia with similar memory bandwidth. Software is no longer the main bottleneck for AMD.
just use torch/vllm/sglang/llama.cpp and the rest of the ecosystem, most have decent support for AMD, it's not that different from CUDA once you get it working (and it is much easier now than it used to)
Really, it's just the Python frameworks on AMD consumer GPUs that suck. AMD datacenter GPUs seem to work with them well enough, and llama.cpp crushes it for the rest of us.
The repeating story - There are X number of people in the tech and finance world that form a close network. It is the incestuous coming together of those that enable all of them to become a multi billionaire through acquisitions and IPOs. New people join this list on a regular basis by building something that create FOMO amongst the already billionaires and they indoctrinate those into the group using retail investor money.
that's how it's always worked brother - at least, SV gave a whole bunch of new players a way to make their money in a much more meritocratic way than what existed previously.
I hesitate to recast the discussion in a negative tone, but this doesn't sound right on technical terms.
Is World Labs' Atlas genuinely novel? Their demos do not seem to be better than the existing state of the art.
Fei Fei Li has been criticized even in the ImageNet days as a shower than a doer. Her roadshow past two years extolling "world model" in vague terms didn't show much insight, and her company's demo seems to merely rehash what has been available in the field for years. If you haven't seen the current SoTA in Gaussian splats, then World Labs' demos may seem cool, but they are mostly standard in the field now. If someone is more familiar with the inner workings of World Labs, I am happy to be corrected (but inner details wouldn't change the fact that demos are no better than SoTA).
I really had high hopes for World Labs, but I am quite saddened to realize that perhaps all this was just a financial maneuver and the detractors were right from the beginning.
source: I used to be in the downstream field: Gaussian spats for robotics. The exact field that World Labs' is supposed to help.
> has been criticized even in the ImageNet days as a shower than a doer
When has the world ever rewarded doers? It has almost always rewarded the showers. If it rewarded the doers:
* CTOs would be regarded more highly than CEOs
* A few key Apple engineers would be more well known than Steve Jobs
* Nikola Tesla would be more famous than Edison
> this was just a financial maneuver
I mean, if you could have a couple billion dollars now OR possibly $0 when OpenAI/Anthropic's models can eventually do what yours can do, I wouldn't blame you for taking the former.
I think the model is legit but not worth 8 billion dollars, nor is there much secret sauce. I'm at a series C company and I think we're pretty confident we have the resources to reproduce it internally.
You say the world doesn't reward the doers but CTOs and a few key Apple engineers were/are rewarded with heavy bags of money. They don't get the media features because the company has to pay the media to feature Steve Jobs telling us he's just a cool hippie, actually, and not a ruthless psychopath. Doing the same for the CTO serves no marketing purpose for Apple.
As for Nikola Tesla, he spent a lot of his money on things that didn't work out, like the unfinished Wardenclyffe Tower.
None of the examples you shared is the world not "rewarding" them compared to people who are not those things.
I don't think they published details but the Atlas model is a feed forward neural network, and not Gaussian splat based model. Unlike GS it works from a few images.
Gaussian splatting is the rendering technique of projecting the gaussians into the 2D viewport. How you obtain the gaussians in the first place is a different question (feed forward prediction vs. iterative gradient descent fitting).
I get the feeling that people still think World Labs is all in on splats? I agree the original splat demos are not competitive relative to the SOTA for splats. But Atlas (https://www.worldlabs.ai/blog/atlas) is more of a generative model than a splat-oriented model. They are essentially trying to combine many useful capabilities into one omni-modal generative model. For instance, native camera pose conditioning is not a capability most video models have, and it also seems to have some SLAM/VGGT like capabilities (see blog).
Essentially, this is the first true "omni-model" that can be conditioned on anything (text, pose, depth, video) and give you any output (pose, depth, video, splats). You could argue that they are not SOTA right now relative to a traditional multi-stage pipelines, but this unified pipeline is much more amenable to scale.
which if you know why fei fei is famous, perfectly lines up. she was the first to turn from better algs to diverse data for training, even for super specific image classifiers. what is this, but an attempt to, like humans, make anything we can experience training data and thus a native "language" of the model.
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[ 15.3 ms ] story [ 72.4 ms ] threadI'm not sure how much things like Omniverse are used, but NV has put out some really interesting stuff in the space (like for example ARTY for a somewhat recent example).
Overall it seems like a financial vote of confidence for "world models" (whatever that means, I still don't know). But it could also mean the death of the interesting things WL was doing with Marble + Atlas. It's hard to read PR.
Think it's a good match
OpenRouter was sold for 7.5 Billion.
Lets just accept, that these people don't evaluate a company by value but by magic market "what is a sum someone needs to pay for buying a company and what company is somehow worth it to actually buy for this type of money but more in a sense of adding this to your portfolio"
https://www.google.com/search?client=firefox-b-d&q=pokemon+g...
Neoclouds want to do neolab things and now chipmakers want to do neolab things
We don't know what the right integrations are. Is it the chipmakers with the toolmakers? The front-end makers with the model designers? That's the current set-up. But there might be another industrial configuration that is superior.
AMD is still struggling to establish itself in AI. That makes it a worthy competitor. Its agglomeration of talent and resources is probably, knowing little else, good.
I was also shocked by how quickly AMD acquired Talaas. AMD may be preparing for the next way (ultra fast inference, and embodied AI inference)
I don't know anything.
Things like training a Vision/RL/LM, downloading and running LMs, etc.
I'm curious how much the recent AI 3D modeling trend (Astra post-trained to use Blender) would have impacted this.
World Labs' entire tech stack becomes potentially obsolete when anyone can prompt GPT/Claude to create a simulation-ready 3D model from a photograph.
Is World Labs' Atlas genuinely novel? Their demos do not seem to be better than the existing state of the art.
Fei Fei Li has been criticized even in the ImageNet days as a shower than a doer. Her roadshow past two years extolling "world model" in vague terms didn't show much insight, and her company's demo seems to merely rehash what has been available in the field for years. If you haven't seen the current SoTA in Gaussian splats, then World Labs' demos may seem cool, but they are mostly standard in the field now. If someone is more familiar with the inner workings of World Labs, I am happy to be corrected (but inner details wouldn't change the fact that demos are no better than SoTA).
I really had high hopes for World Labs, but I am quite saddened to realize that perhaps all this was just a financial maneuver and the detractors were right from the beginning.
source: I used to be in the downstream field: Gaussian spats for robotics. The exact field that World Labs' is supposed to help.
> has been criticized even in the ImageNet days as a shower than a doer
When has the world ever rewarded doers? It has almost always rewarded the showers. If it rewarded the doers:
* CTOs would be regarded more highly than CEOs
* A few key Apple engineers would be more well known than Steve Jobs
* Nikola Tesla would be more famous than Edison
> this was just a financial maneuver
I mean, if you could have a couple billion dollars now OR possibly $0 when OpenAI/Anthropic's models can eventually do what yours can do, I wouldn't blame you for taking the former.
As for Nikola Tesla, he spent a lot of his money on things that didn't work out, like the unfinished Wardenclyffe Tower.
None of the examples you shared is the world not "rewarding" them compared to people who are not those things.
The showers usually pluck them out and show them, and look like constant success to the public.
AMD has made a lot of acquihires in the last few years. this ain't one of em.
Essentially, this is the first true "omni-model" that can be conditioned on anything (text, pose, depth, video) and give you any output (pose, depth, video, splats). You could argue that they are not SOTA right now relative to a traditional multi-stage pipelines, but this unified pipeline is much more amenable to scale.