The paper "Objects that Sound" is available here: https://arxiv.org/abs/1712.06651 One-time payment links are available below.

NASA's Curiosity rover has snapped a spectacular 360-degree selfie of the Red Planet. The veteran explorer, which was launched to Mars 10 years ago, captured the image using a camera at the end of its robotic arm. It snapped 81 individual pictures to make up the panoramic view of its desolate surroundings. The Curiosity rover's Twitter account shared the images, writing: 'Stop! I took this 360-degree selfie using the Mars Hand Lens Imager at the end of my arm.' Landmarks featured in the selfie include a rock structure behind the rover known as'Greenheugh Pediment', while a hill to the right is'Rafael Navarro Mountain', named after a Curiosity team scientist who died earlier this year.

NASA's Curiosity rover has marked the 10th anniversary of its launch to Mars by sending back a spectacular'picture postcard' from the Red Planet. The robotic explorer snapped two black and white images of the Martian landscape which were then combined and had colour added to them to produce the remarkable composite. Curiosity, which launched to the Red Planet almost exactly 10 years ago on November 26, 2011, took the pictures from its most recent perch on the side of Mars' Mount Sharp. It captures a 360-degree view of its surroundings with its black-and-white navigation cameras each time it completes a drive, before beaming back the panorama to Earth. So inspired were the mission team by the beauty of the landscape, they combined two versions of the black-and-white images from different times of the day and added colours to create a rare postcard, NASA's Jet Propulsion Laboratory (JPL) said.

Onboard autonomy technologies such as planning and scheduling, identification of scientific targets, and content-based data summarization, will lead to exciting new space science missions. However, the challenge of operating missions with such onboard autonomous capabilities has not been studied to a level of detail sufficient for consideration in mission concepts. These autonomy capabilities will require changes to current operations processes, practices, and tools. We have developed a case study to assess the changes needed to enable operators and scientists to operate an autonomous spacecraft by facilitating a common model between the ground personnel and the onboard algorithms. We assess the new operations tools and workflows necessary to enable operators and scientists to convey their desired intent to the spacecraft, and to be able to reconstruct and explain the decisions made onboard and the state of the spacecraft. Mock-ups of these tools were used in a user study to understand the effectiveness of the processes and tools in enabling a shared framework of understanding, and in the ability of the operators and scientists to effectively achieve mission science objectives.

The paper "Game Engine Learning from Video" is available here: https://www.cc.gatech.edu/ We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Andrew Melnychuk, Brian Gilman, Dave Rushton-Smith, Dennis Abts, Eric Haddad, Esa Turkulainen, Evan Breznyik, Kaben Gabriel Nanlohy, Michael Albrecht, Michael Jensen, Michael Orenstein, Steef, Sunil Kim, Torsten Reil.

The fronds of the coconut tree swayed gently in the cooling breeze blowing from the sea. The turquoise blue waters of the shallow lagoon shimmered in the evening sunlight. Children played on the white sand. The whitewashed clinic building was set among a grove of coconut and mango trees. The clinic had a doctor's room with an old-fashioned high back revolving chair and a room where most procedures could be done.

A digital replica of Earth could help scientists better model the future of our planet and find solutions to problems wrought by climate change. The advanced model, dubbed Digital Twin Earth, is being developed by the European Space Agency (ESA) and its partners based on data and images from Earth-observation satellites and sensors on the ground. To run reliably, the project will require new advanced artificial intelligence algorithms and powerful supercomputers, which are currently being developed. ESA and its partners discussed their progress in the runup to the UN Climate Change Conference COP26, a two-week event that's currently taking place in Glasgow, Scotland. ESA launched the Digital Twin Earth project in 2020 and invited researchers and tech companies from across Europe to present their progress during an event called PhiWeek, which took place Oct. 11 to Oct. 15.

Many real-world problems require the combined application of multiple reasoning abilities employing suitable abstractions, commonsense knowledge, and creative synthesis of problem-solving strategies. To help advance AI systems towards such capabilities, we propose a new reasoning challenge, namely Fermi Problems (FPs), which are questions whose answers can only be approximately estimated because their precise computation is either impractical or impossible. For example, "How much would the sea level rise if all ice in the world melted?" FPs are commonly used in quizzes and interviews to bring out and evaluate the creative reasoning abilities of humans. To do the same for AI systems, we present two datasets: 1) A collection of 1k real-world FPs sourced from quizzes and olympiads; and 2) a bank of 10k synthetic FPs of intermediate complexity to serve as a sandbox for the harder real-world challenge. In addition to question answer pairs, the datasets contain detailed solutions in the form of an executable program and supporting facts, helping in supervision and evaluation of intermediate steps. We demonstrate that even extensively fine-tuned large scale language models perform poorly on these datasets, on average making estimates that are off by two orders of magnitude. Our contribution is thus the crystallization of several unsolved AI problems into a single, new challenge that we hope will spur further advances in building systems that can reason.

In 1996 Nasa and the White House made the explosive announcement that the rock contained traces of Martian bugs. The meteorite, catalogued as Allen Hills (ALH) 84001, crashed onto the frozen wastes of Antarctica 13,000 years ago and was recovered in 1984. Photographs were released showing elongated segmented objects that appeared strikingly lifelike.

Coupled dynamical systems are frequently observed in nature, but often not well understood in terms of their causal structure without additional domain knowledge about the system. Especially when analyzing observational time series data of dynamical systems where it is not possible to conduct controlled experiments, for example time series of climate variables, it can be challenging to determine how features causally influence each other. There are many techniques available to recover causal relationships from data, such as Granger causality, convergent cross mapping, and causal graph structure learning approaches such as PCMCI. Path signatures and their associated signed areas provide a new way to approach the analysis of causally linked dynamical systems, particularly in informing a model-free, data-driven approach to algorithmic causal discovery. With this paper, we explore the use of path signatures in causal discovery and propose the application of confidence sequences to analyze the significance of the magnitude of the signed area between two variables. These confidence sequence regions converge with greater sampling length, and in conjunction with analyzing pairwise signed areas across time-shifted versions of the time series, can help identify the presence of lag/lead causal relationships. This approach provides a new way to define the confidence of a causal link existing between two time series, and ultimately may provide a framework for hypothesis testing to define whether one time series causes another.