Lifeboat Foundation

The popular idea that quantum physics implies everything is random and nothing is certain might be as far from the truth as it could possibly be.

DeepSouth should be operational in Spring 2024.

In a year packed with fascinating discoveries, biologists pushed the limits of synthetic life, probed how organisms keep time, and refined theories about consciousness and emotional health.

NVFi tackles the intricate challenge of comprehending and predicting the dynamics within 3D scenes evolving over time, a task critical for applications in augmented reality, gaming, and cinematography. While humans effortlessly grasp the physics and geometry of such scenes, existing computational models struggle to explicitly learn these properties from multi-view videos. The core issue lies in the inability of prevailing methods, including neural radiance fields and their derivatives, to extract and predict future motions based on learned physical rules. NVFi ambitiously aims to bridge this gap by incorporating disentangled velocity fields derived purely from multi-view video frames, a feat yet unexplored in prior frameworks.

The dynamic nature of 3D scenes poses a profound computational challenge. While recent advancements in neural radiance fields showcased exceptional abilities in interpolating views within observed time frames, they fall short in learning explicit physical characteristics such as object velocities. This limitation impedes their capability to foresee future motion patterns accurately. Current studies integrating physics into neural representations exhibit promise in reconstructing scene geometry, appearance, velocity, and viscosity fields. However, these learned physical properties are often intertwined with specific scene elements or necessitate supplementary foreground segmentation masks, limiting their transferability across scenes. NVFi’s pioneering ambition is to disentangle and comprehend the velocity fields within entire 3D scenes, fostering predictive capabilities extending beyond training observations.

Researchers from The Hong Kong Polytechnic University introduce a comprehensive framework NVFi encompassing three fundamental components. First, a keyframe dynamic radiance field facilitates the learning of time-dependent volume density and appearance for every point in 3D space. Second, an interframe velocity field captures time-dependent 3D velocities for each point. Finally, a joint optimization strategy involving both keyframe and interframe elements, augmented by physics-informed constraints, orchestrates the training process. This framework offers flexibility in adopting existing time-dependent NeRF architectures for dynamic radiance field modeling while employing relatively simple neural networks, such as MLPs, for the velocity field. The core innovation lies in the third component, where the joint optimization strategy and specific loss functions enable precise learning of disentangled velocity fields without additional object-specific information or masks.

Quantum computers could become more useful now researchers at Google have designed an algorithm that can translate complex physical problems into the language of quantum physics.

By Alex Wilkins

Growing old may come with more aches and pains attached, but new research suggests there’s a bigger picture to look at: by reaching our dotage, we might actually be helping the evolution of our species.

Once assumed to be an inevitable consequence of living in a rough-and-tumble world, aging is now considered something of a mystery. Some species barely age at all, for example. One of the big questions is whether aging is simply a by-product of biology, or something that comes with an evolutionary advantage.

The new research is based on a computer model developed by a team from the HUN-REN Centre for Ecological Research in Hungary which suggests old age can be positively selected for in the same way as other traits.

As tech firms race to build superintelligent AI systems, is all the hype around superhuman AI helpful, harmful, or even realistic?

Germany-based startup Zander Laboratories signed a contract worth €30 million ($32.9 million) to develop neurotechnological prototypes. Zander signed the contract with The German Agency for Innovation…

Over the weekend, North Korea tested two missiles, one of which is capable of reaching the United States, officials in South Korea and Japan said. Defense officials in both countries claimed that the rocket traveled more than 600 miles before landing in the ocean northwest of Tokyo.