Multi-agent interacting systems are prevalent in the world, from purely physical systems to complicated social dynamic systems. The interactions between entities / components can give rise to very complex behavior patterns at the level of both individuals and the multi-agent system as a whole. Since usually only the trajectories of individual entities are observed without any knowledge of the underlying interaction patterns, and there are usually multiple possible modalities for each agent with uncertainty, it is challenging to model their dynamics and forecast their future behaviors. We introduce a generic trajectory forecasting framework (named EvolveGraph) with explicit relational structure recognition and prediction via latent interaction graphs among multiple heterogeneous, interactive agents. Considering the uncertainty of future behaviors, the model is designed to provide multi-modal prediction hypotheses.

Vulnerable elephant populations are now being tracked from space using Earth-observation satellites and a type of artificial intelligence (AI) called machine learning. As part of an international project, researchers are using satellite images processed with computer algorithms, which are trained with more than 1,000 images of elephants to help spot the creatures. With machine learning, the algorithms can count elephants even on'complex geographical landscapes', such as those dotted with trees and shrubs. Researchers say this method is a promising new tool for surveying endangered wildlife and can detect animals with the same accuracy as humans. Elephants in woodland as seen from space.

The man who designed some of the world's most advanced dynamic robots was on a daunting mission: programming his creations to dance to the beat with a mix of fluid, explosive and expressive motions that are almost human. Almost a year and half of choreography, simulation, programming and upgrades that were capped by two days of filming to produce a video running at less than 3 minutes. The clip, showing robots dancing to the 1962 hit "Do You Love Me?" by The Contours, was an instant hit on social media, attracting more than 23 million views during the first week. It shows two of Boston Dynamics' humanoid Atlas research robots doing the twist, the mashed potato and other classic moves, joined by Spot, a doglike robot, and Handle, a wheeled robot designed for lifting and moving boxes in a warehouse or truck. Boston Dynamics founder and chairperson Marc Raibert says what the robot maker learned was far more valuable.

Google is giving users a new way to take charge over their privacy when using its smart speakers and displays. The new security feature, known as Guest Mode, keeps your personal data confidential while still allowing others to get the most out of Google Assistant--and it's already available on your Google smart speaker. Guest Mode is a new privacy feature for Google smart speakers that, when enabled, doesn't store assistant activity and audio recordings, or provide personalized results. The new feature, announced on Jan. 13, is ready for use on Google speakers and displays like the Google Nest Mini and Nest Hub Max. To turn it on, say, "Hey Google, turn on Guest Mode."

Otter, which uses AI to offer a low-cost transcription service, is bringing its smarts to Google Meet, letting users access live notes and captions. All a user needs to do is install a Chrome extension, which will open up a live notes panel which will record what is said while people are saying it. The company already offered a similar service to Zoom chats, but now offers an alternative to Google's baked-in live caption service. Otter's boast is that its interactive, editable transcripts are a great tool for collaboration when the meeting is finished. In the announcement, Otter says that tools like this make it easy to record meetings to avoid confusion later, but also help folks with accessibility requirements.

In a low-rise building overlooking a busy intersection in Beijing, Ji Rong Wen, a middle-aged scientist with thin-rimmed glasses and a mop of black hair, excitedly describes a project that could advance one of the hottest areas of artificial intelligence. Wen leads a team at the Beijing Academy of Artificial Intelligence (BAAI), a government-sponsored research lab that's testing a powerful new language algorithm--something similar to GPT-3, a program revealed in June by researchers at OpenAI that digests large amounts of text and can generate remarkably coherent, free-flowing language. "This is a big project," Wen says with a big grin. "It takes a lot of computing infrastructure and money." Wen, a professor at Renmin University in Beijing recruited to work part-time at BAAI, hopes to create an algorithm that is even cleverer than GPT-3. He plans to combine machine learning with databases of facts, and to feed the algorithm images and video as well as text, in hope of creating a richer understanding of the physical world--that the words cat and fur don't just often appear in the same sentence, but are associated with one another visually.

It's hard to focus on the nitty gritty of tech policy when the world is on fire. Take, for example, his fight against Big Tech in the name of "anti-conservative bias" (no, it doesn't exist), which resulted in an assault on Section 230. Experts say the true aim of those efforts was to undermine content moderation, and normalize the white supremacist attitudes that helped put people like Trump in power. Unfortunately, those allegations will have life for years to come as a form of "zombie Trumpism," as Berin Szoka, a senior fellow at the technology policy organization TechFreedom, put it. Trump may be gone from office and Twitter.

The mission of AI100 is to launch a study every five years, over the course of a century, to better track and anticipate how artificial intelligence propagates through society, and how it shapes different aspects of our lives. This IJCAI session brought together some of the people involved in the AI100 initiative to discuss their efforts and the direction of the project. The goals of the AI100 are "to support a longitudinal study of AI advances on people and society, centering on periodic studies of developments, trends, futures, and potential disruptions associated with the developments in machine intelligence, and formulating assessments, recommendations and guidance on proactive efforts". Working on the AI100 project are a standing committee and a study panel. The first study panel report, released in 2016, can be read in full here.

Western Australia has announced it will invest AU$1 million into nine initiatives that are aimed at reducing e-waste. The AU$1 million investment will come out of the state's AU$16.7 million New Industries Fund, and is expected to divert approximately 1,000 tonnes of e-waste annually from landfill. "The selected projects will support the recovery of high value material, while diverting materials which may have presented risks to human health and the environment if not disposed of appropriately," Environment Minister Stephen Dawson added. Among the grant recipients are Curtin University, the Commonwealth Scientific and Industrial Research Organisation (CSIRO), and Epichem, which are all set to receive AU$200,000 apiece for their respective projects. Curtin University will use the funds to create a mini plant for recycling and metal recovery from printed circuit boards and integrated circuits; CSIRO will develop "innovative biotechnology" for extracting precious and base metals from e-waste; and Epichem has agreed to test whether oxidative hydrothermal dissolution can break down e-waste to produce a range of useful chemicals.

Devices designed for improving customer marketing and sports performance are now being used in the fight against COVID-19 as companies deploy their technologies to meet new needs during the pandemic. Hitachi-LG Data Storage originally developed its 3D LiDAR People Counter sensor for retail stores to track shoppers' movements and analyse data in order to improve sales and customer satisfaction. The company, a joint venture between Japan's Hitachi and South Korea's LG Electronics, has now paired the application with a heat detection and camera app that takes customers' temperatures and checks if they are wearing a mask with a facial detection system. The technology monitors the number of people and their movements to reduce congestion and it estimates wait times at cash registers, to help reduce infection risks. It can also determine whether or not a customer has stopped by a specific area such as a required hand sanitizer station.