Our first responders have used established wireless modes of communication to address emergencies for the past two decades. Robots are now joining the effort. As we continue to augment public safety agencies around the world with semiautonomous technologies, do we fully understand how this shift invites additional risk? Robots are increasingly used to safeguard communities. The Department of Homeland Security's Science & Technology Directorate, for example, is working closely with the Department of Customs and Border Protection (CBP) to develop technologies meant to safeguard our national borders.

We introduce an unsupervised clustering algorithm to improve training efficiency and accuracy in predicting energies using molecular-orbital-based machine learning (MOB-ML). This work determines clusters via the Gaussian mixture model (GMM) in an entirely automatic manner and simplifies an earlier supervised clustering approach [J. Chem. Theory Comput., 15, 6668 (2019)] by eliminating both the necessity for user-specified parameters and the training of an additional classifier. Unsupervised clustering results from GMM have the advantage of accurately reproducing chemically intuitive groupings of frontier molecular orbitals and having improved performance with an increasing number of training examples. The resulting clusters from supervised or unsupervised clustering is further combined with scalable Gaussian process regression (GPR) or linear regression (LR) to learn molecular energies accurately by generating a local regression model in each cluster. Among all four combinations of regressors and clustering methods, GMM combined with scalable exact Gaussian process regression (GMM/GPR) is the most efficient training protocol for MOB-ML. The numerical tests of molecular energy learning on thermalized datasets of drug-like molecules demonstrate the improved accuracy, transferability, and learning efficiency of GMM/GPR over not only other training protocols for MOB-ML, i.e., supervised regression-clustering combined with GPR(RC/GPR) and GPR without clustering. GMM/GPR also provide the best molecular energy predictions compared with the ones from literature on the same benchmark datasets. With a lower scaling, GMM/GPR has a 10.4-fold speedup in wall-clock training time compared with scalable exact GPR with a training size of 6500 QM7b-T molecules.

Recurrent neural networks have seen widespread use in modeling dynamical systems in varied domains such as weather prediction, text prediction and several others. Often one wishes to supplement the experimentally observed dynamics with prior knowledge or intuition about the system. While the recurrent nature of these networks allows them to model arbitrarily long memories in the time series used in training, it makes it harder to impose prior knowledge or intuition through generic constraints. In this work, we present a path sampling approach based on principle of Maximum Caliber that allows us to include generic thermodynamic or kinetic constraints into recurrent neural networks. We show the method here for a widely used type of recurrent neural network known as long short-term memory network in the context of supplementing time series collected from different application domains. These include classical Molecular Dynamics of a protein and Monte Carlo simulations of an open quantum system continuously losing photons to the environment and displaying Rabi oscillations. Our method can be easily generalized to other generative artificial intelligence models and to generic time series in different areas of physical and social sciences, where one wishes to supplement limited data with intuition or theory based corrections.

Users of self-driving cars will be able to watch films on the motorway under planned changes to the Highway Code, although it will remain illegal to use mobile phones. The update, proposed by the Department for Transport (DfT), will allow those in the driver's seat to use a car's built-in screens to watch movies and TV programmes. The new rules also state that insurance companies will be financially liable, rather than individual motorists, for accidents in self-driving cars. However, those behind the wheel must be ready to resume control of the vehicle when they are prompted – such as when they approach motorway exits. These measures were described as an interim measure by the government to support the early deployment of self-driving vehicles.

In 2018, SpaceX sent a small robot called CIMON aboard on its Dragon cargo capsule to the International Space Station. Space Exploration Technologies Corporation, or SpaceX, founded by Elon Musk in 2002, refused to give up easily. Its first three attempts to launch its Falcon 1 rocket between 2006 and 2008 failed. In 2010, the company then shifted to building a much bigger rocket called Falcon 9. Gradually, it began to deliver cargo to the International Space Station for NASA. The next decade saw the California-based aerospace company transform itself because of its ability to lower the cost of space travel drastically.

Let's play a little game. Imagine that you're a computer scientist. Your company wants you to design a search engine that will show users a bunch of pictures corresponding to their keywords -- something akin to Google Images. You're a great computer scientist, and this is basic stuff! But say you live in a world where 90 percent of CEOs are male. Should you design your search engine so that it accurately mirrors that reality, yielding images of man after man after man when a user types in "CEO"? Or, since that risks reinforcing gender stereotypes that help keep women out of the C-suite, should you create a search engine that deliberately shows a more balanced mix, even if it's not a mix that reflects reality as it is today?

AI IS ON THE RISE, AI and Machine Learning are shaping the future in Cybersecurity, hence, leading to RISE OF AI-based cybersecurity tools as a phoenix. With a recent study finding that nearly two-thirds of organizations are using or plan to use AI capabilities in their security operations by 2023. The days of deliberate, human-driven malware attacks are fading fast. We're now seeing a surge in AI-powered attacks that can bypass even the most sophisticated security defenses. No wonder, then, that the demand for artificial intelligence cybersecurity tools is also growing at an exponential rate.

The Food and Drug Administration has approved the first artificial intelligence software to be used to interpret dental x-rays, allowing dentists to better screen for oral pathologies. Pearl's Second Opinion is the first and only FDA-cleared AI radiologic detection aid for dentists at the chairside, and it can assist dentists to discover a variety of common dental diseases such as tooth decay, calculus, and root abscesses. Pearl gathered over 100 million dental x-rays from dental practices and academic institutes to create Second Opinion. The AI platform highlights anomalies in x-rays and also acts as a patient communication tool, allowing dentists to exhibit alternative models of a patient's teeth and highlight trouble regions. Pearl's announcement is a significant step forward in the field of technology-assisted dentistry.

How much do we need humans in space? How much do we want them there? Astronauts embody the triumph of human imagination and engineering. Their efforts shed light on the possibilities and problems posed by travel beyond our nurturing Earth. Their presence on the moon or on other solar-system objects can imply that the countries or entities that sent them there possess ownership rights.

The Japanese government passed a bill Tuesday to introduce new rules for next-generation mobility, such as unmanned self-driving vehicles, automated delivery robots and electric kick scooters. The bill to revise the current road traffic law was approved at a plenary meeting of the House of Representatives, the lower chamber of the Diet, following its passage at the House of Councillors, the upper chamber, last week. Under the revised law, a license system will be introduced for operators of transport services using unmanned vehicles with Level 4 autonomy, which requires no driver in the remotely monitored vehicle within a limited area. Such vehicles are expected to be used for residents in depopulated areas. The new rules obligate the operators of unmanned vehicles to prepare a system to ensure that staff would be sent out to the site of any accidents.