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> This isn't how it works. As the models are improved, they learn more about reality largely on their own. AI models aren't complete blackboxes to the people w

> This isn't how it works. As the models are improved, they learn more about reality largely on their own. AI models aren't complete blackboxes to the people who develop them: there is careful thought behind the architecture, dataset selection and model evaluation. Assuming that you can take an existing model and simply throw more compute at it will automatically result in higher fidelity illumination modeling takes almost religious levels of faith. If moar hardware is all you need, Nvidia would have the best models in every category right now. Perhaps someone ought to write the sequel to Fred Brooks' book amd name it "The Mythical GPU-Cluster-Month". FWIW, Google has AI-based illumination adjustment in Google Photos where one can add virtual lights - so specialized models for lighting already exist. However, I'm very cynical about a generic mixed model incidentally gaining those capabilities without specific training for it. When dealing with exponential requirements (training data, training time, GPUs, model weight size), you'll run out of resources in short order.

devbent 2y ago
> If moar hardware is all you need, Nvidia would have the best models in every category right now. Nvidia is making boatloads of money right now selling GPUs to companies that think they will be making boatloads of money in the future. Nvidia has the better end of things at this very moment in time.
bastawhiz 2y ago
What you're refuting isn't what I said. I'm making the point that nobody is encoding all of the individual features of the human form and reality into their models through code or model design. You build a model by making it capable of observing details and then letting it observe the details of your training data. Nobody is spending time getting the reflections in the eyeballs working well, that comes as an emergent property of a model that's able to identify and replicate that. That doesn't mean it's a black box, it means that it's built in a general way so the researchers don't need to care about every facet of reality.
dragonwriter 2y ago
> Assuming that you can take an existing model and simply throw more compute at it will automatically result in higher fidelity illumination modeling takes almost religious levels of faith. Seems an odd response to a poster who said “as the models are improved...”; the way the models are improved isn't just additional training to existing models, its updated model architectures.

devbent 2y ago

> If moar hardware is all you need, Nvidia would have the best models in every category right now. Nvidia is making boatloads of money right now selling GPUs to companies that think they will be making boatloads of money in the future. Nvidia has the better end of things at this very moment in time.

bastawhiz 2y ago

What you're refuting isn't what I said. I'm making the point that nobody is encoding all of the individual features of the human form and reality into their models through code or model design. You build a model by making it capable of observing details and then letting it observe the details of your training data. Nobody is spending time getting the reflections in the eyeballs working well, that comes as an emergent property of a model that's able to identify and replicate that. That doesn't mean it's a black box, it means that it's built in a general way so the researchers don't need to care about every facet of reality.

dragonwriter 2y ago

> Assuming that you can take an existing model and simply throw more compute at it will automatically result in higher fidelity illumination modeling takes almost religious levels of faith. Seems an odd response to a poster who said “as the models are improved...”; the way the models are improved isn't just additional training to existing models, its updated model architectures.