What the science says about milk, sleep, and if your cat really loves you. Breakthroughs, discoveries, and DIY tips sent every weekday. Cats are man's best friend--never mind that other animal species. Jokes aside, humans and cats have lived together for thousands of years but not nearly as long as humans and dogs . It makes sense, then, that we don't always understand cats very well.

Boldface denotes the best performing algorithm according to mean misclassification rate.

Devoid of some assumption, aPU learning is impossible [6].

We thank the reviewers for their very constructive feedback! In contrast, our method's gradient is: Put simply, Kiryo et al. stop optimizing Empirically, we find that this "soft-constraint" approach to implausible negative risk yields comparable or better models We also show in the supplementals (e.g., Sec. PU learning work (including Kiryo et al. in their nnPU paper), which uses neural networks. However, our experiments show that PUc's biggest limitation is not its representation: On unshifted data (Table 1 row 1 On shifted data (Tab. 1 's performance degrades while our methods' performance improves. We will add a "Discussion" subsection to the paper's "Experimental Results" (Sec.

Abstract--We introduce a transformation of a Neural Radiance Field (NeRF) to an equivalent Poisson Point Process (PPP). This PPP transformation allows for rigorous quantification of uncertainty in NeRFs, in particular, for computing collision probabilities for a robot navigating through a NeRF environment. The PPP is a generalization of a probabilistic occupancy grid to the continuous volume and is fundamental to the volumetric ray-tracing model underlying radiance fields. Building upon this PPP representation, we present a chance-constrained trajectory optimization method for safe robot navigation in NeRFs. Our method relies on a voxel representation called the Probabilistic Unsafe Robot Region (PURR) that spatially fuses the chance constraint with the NeRF model to facilitate fast trajectory optimization. We then combine a graph-based search with a spline-based trajectory optimization to yield robot trajectories through the NeRF that are guaranteed to satisfy a user-specific collision probability. We validate our chance constrained planning method through simulations and hardware experiments, showing superior performance compared to prior works on trajectory planning in NeRF environments. Figure 1: (a) Ground-truth of the Stonehenge scene, (b) Poisson Constructing an environment model from onboard sensors, Point Process (PPP) of the scene represented as a point cloud, such as RGB(-D) cameras, lidar, or touch sensors, is a fundamental (c) Probabilistically Unsafe Robot Region (PURR) of scene, challenge for any autonomous system. Radiance Fields (NeRFs) [1] have emerged as a promising 3D scene representation with potential applications in a variety of robotics domains including SLAM [2], pose estimation [3], such as (watertight) triangle meshes [9], occupancy grids [10], [4], reinforcement learning [5], and grasping [6]. NeRFs offer or Signed Distance Fields (SDFs) [11], occupancy is welldefined several potential benefits over traditional scene representations: and simple to query. NeRFs, however, do not admit they can be trained using only monocular RGB images, they simple point-wise occupancy queries, since they represent the provide a continuous representation of obstacle geometry, and scene geometry implicitly through a continuous volumetric they are memory-efficient, especially considering the photorealistic density field.

If an unexpected meow, peculiar pose, or unusual twitch of the whiskers leaves you puzzling over what your cat is trying to tell you, artificial intelligence may soon be able to translate. Scientists are turning to new technology to unpick the meanings behind the vocal and physical cues of a host of animals. "We could use AI to teach us a lot about what animals are trying to say to us," said Daniel Mills, a professor of veterinary behavioural medicine at the University of Lincoln. Previous work, including by Mills, has shown that cats produce a variety of facial expressions when interacting with humans, and this week researchers revealed felines have a range of 276 facial expressions when interacting with other cats. "However, the facial expressions they produce towards humans look different from those produced towards cats," said Dr Brittany Florkiewicz, an assistant professor of psychology at Lyon College in Arkansas who co-authored the new work.

The remarkable capabilities of large language models have been accompanied by a persistent drawback: the generation of false and unsubstantiated claims commonly known as "hallucinations". To combat this issue, recent research has introduced approaches that involve editing and attributing the outputs of language models, particularly through prompt-based editing. However, the inference cost and speed of using large language models for editing currently bottleneck prompt-based methods. These bottlenecks motivate the training of compact editors, which is challenging due to the scarcity of training data for this purpose. To overcome these challenges, we exploit the power of large language models to introduce corruptions (i.e., noise) into text and subsequently fine-tune compact editors to denoise the corruptions by incorporating relevant evidence. Our methodology is entirely unsupervised and provides us with faux hallucinations for training in any domain. Our Petite Unsupervised Research and Revision model, PURR, not only improves attribution over existing editing methods based on fine-tuning and prompting, but also achieves faster execution times by orders of magnitude.

Since dinosaurs went extinct 66 million years ago, we've never experienced them as living, breathing animals. We can look at their bones in a museum, or we can watch recreations of them in films like this summer's Jurassic World: Fallen Kingdom. But both those options lack that visceral feel you get from seeing a real creature in a zoo. Though it's unlikely you'll ever live long enough to see a dinosaur in the flesh, you can still pretend to have one as a pet, thanks to Mattel's new Alpha Training Blue robot. She roars, coos and even responds to your commands like her movie inspiration -- but is far less deadly.