MIT CSAIL researchers mixed GenAI plus a physics simulation engine to refine robotic models. The result: a machine that out-jumped a robotic made by human beings. Examine whole story →
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This significant dataset of underwater photos presents the inspiration for teaching LOBSTgER’s generative AI models. The images span numerous angles, lights circumstances, and animal behaviors, causing a visible archive that is both of those artistically striking and biologically precise.
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“Perhaps the most complicated aspect of currently being a machine-Finding out researcher in recent times will be the seemingly limitless quantity of papers that seem on a yearly basis. On this context, papers that unify and join present algorithms are of good worth, nonetheless They can be exceptionally uncommon.
This integrative tactic would make LOBSTgER the two a investigate more info Resource as well as a creative experiment — one which reflects MIT’s extensive-standing custom of interdisciplinary innovation.
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Picture synthesis through reverse diffusion: This shorter video displays the de-noising trajectory from Gaussian latent sound to photorealistic output applying LOBSTgER’s unconditional designs. Iterative de-noising involves one,000 ahead passes through the qualified neural community.
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