Breakthroughs, discoveries, and DIY tips sent every weekday. Most of us have heard of pimple patches, those circular bandage-like patches to clear up a zit . More importantly, many of us have heard of pimple patches--the ones that cost a fortune, stick to your face for maybe 30 minutes, and do absolutely nothing for that angry whitehead you woke up with this morning. However, the team behind a small study published in the journal, claim to have developed a two-step pimple patch that actually works. How can they claim this?

The revolutions in machine learning and artificial intelligence means much higher computational ability is required.

Traffic signal control affects the daily life of people living in urban areas. The existing system relies on a theory- or rule-based controller in charge of altering the traffic lights based on traffic conditions. The objective is to reduce vehicle delay during unsaturated traffic conditions and maximize the vehicle throughput during congestion. However, the existing traffic signal controller cannot fulfill such objectives, and a human controller can only manage a few intersections. In view of this, recent advancements in artificial intelligence have focused on enabling alternate ways of traffic signal control. Current research on this front has explored reinforcement learning (RL) algorithms as a possible approach.

Researchers have found a new artificial intelligence-based drug screening technique. Read below to know the significance and process of the experiment. Developing life-saving drugs can cost billions of dollars and take years, but researchers have found a new artificial intelligence-based drug screening technique, and by using that they assume to shorten the process. Using a process that models drug and target protein interactions using natural language processing techniques, the researchers gained up to 97% accuracy in identifying promising drug candidates. The results were published currently in the journal Briefings in Bioinformatics.

People in Japan, the U.S. and Germany show different concerns regarding artificial intelligence (AI) being used in entertainment, shopping services, or to help find criminals, reports a new study in AI and Ethics. Japanese people tended to report more concern in AI used to fight crime, while Germans and Americans tended to report more concern over the ethical and social aspects of using AI in entertainment, according to the study. "We found there is a difference in the AI and ELSI [ethics, legal, and social issues] levels of understanding between countries. I think it will become important to carry out thorough discussions about the legal and policy issues surrounding AI," said first author and Kanazawa University Associate Professor Yuko Ikkatai. AI is currently being used in a wide range of fields, which has raised positive and negative attitudes in the general public.

What do these three disparate things have in common? Unlike traditional computers that use bits, quantum computers use qubits to encode information as zeros or ones, or both at the same time. Coupled with a cocktail of forces from quantum physics, these refrigerator-sized machines can process a whole lot of information--but they're far from flawless. Just like our regular computers, we need to have the right programming languages to properly compute on quantum computers. Programming quantum computers requires awareness of something called "entanglement," a computational multiplier for qubits of sorts, which translates to a lot of power.

With the use of implicit representation or volumetric representation, extensive efforts have been made to rebuild the human body and clothes as a whole. In many situations, however, having a controllable garment model is desirable. A group of academics focused on the parametric modeling of 3D clothes in a new study, which provides benefits in two ways. To begin with, clothing can be separated from the human body. Second, the topology of the reconstructed meshes may be modified, making it possible to execute downstream tasks that need high interpretability.

Natural language generation (NLG) is a broad term that encompasses a variety of tasks that generate fluent text from input data and other contextual information. In actuality, the goals of these jobs are frequently very different. Some well-known instances of NLG include compressing a source article into a brief paragraph conveying the most significant information, converting content presented in one language into another, and creating unique responses to drive the discourse. Natural language processing has advanced at a breakneck pace in terms of enhancing and developing new models for various jobs. However, assessing NLG remains difficult: human judgment is considered the gold standard, but it is typically costly and time-consuming to get.

Evaluating and quantifying the beauty of a landscape, an ecosystem and its effects on a person's well-being has become a central issue for public authorities. With this in mind, scientists from the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland and Wageningen University in the Netherlands have developed a new indicator based on deep learning and several million photos posted on the social network Flickr. An article was recently published in Nature Scientific Reports. When we walk in nature, whether in the mountains, in a forest or by the sea, we feel things, a certain well-being. Numerous studies have highlighted the benefits of such activities for our health, both physical and mental.

To operate efficiently in urban environments, mobile robots and other autonomous systems should be able to move safely on sidewalks and avoid collisions with pedestrians or other obstacles. This is particularly true for delivery robots or systems that are specifically programmed to patrol urban environments. Researchers at Georgia Institute of Technology and Stanford University have recently developed AlienGo, a quadruped robot that can follow specific routes generated by public map services while remaining on sidewalks and avoiding collisions with obstacles or humans. This robot, presented in a paper pre-published on arXiv, is based on a new, highly performing two-staged learning framework for safe sidewalk navigation. "As part of this project, we developed an intelligent quadrupedal robot that can navigate sidewalks in the real world," Sehoon Ha, one of the researchers who carried out the study, told TechXplore.