They say beauty lies in the eye of the beholder, but in actuality, it goes far deeper than that. The concept of physical beauty resides in the mind, defined by whatever features we find attractive in other people's faces. These subtle preferences represent some of our most private inner thoughts – but that doesn't mean they can't be monitored, and perhaps even predicted. In a new study, researchers used electroencephalography (EEG) measurements to identify what kind of facial features people found to be attractive, and then fed the results to an artificial intelligence (AI) program. The machine learning system – termed a generative adversarial neural network (GAN) – was first able to familiarise itself with what sorts of faces individual people found desirable, and then fabricate entirely new ones specifically designed to please: tailored visions of synthesised beauty, as unattainable as they were perfect.
The work as we know it today is not how it was a decade ago. We have computer systems and software making our jobs less labor-focused. Work after a decade from now won't be the same either. Innovative technologies like artificial intelligence, machine learning, and robotics along with the disruption that came along with COVID-19 are reshaping the future of work. The coronavirus pandemic changed the physical distribution of the workforce by making employees work remotely.
ATAC-seq is a widely-applied assay used to measure genome-wide chromatin accessibility; however, its ability to detect active regulatory regions can depend on the depth of sequencing coverage and the signal-to-noise ratio. Here we introduce AtacWorks, a deep learning toolkit to denoise sequencing coverage and identify regulatory peaks at base-pair resolution from low cell count, low-coverage, or low-quality ATAC-seq data. Models trained by AtacWorks can detect peaks from cell types not seen in the training data, and are generalizable across diverse sample preparations and experimental platforms. We demonstrate that AtacWorks enhances the sensitivity of single-cell experiments by producing results on par with those of conventional methods using ~10 times as many cells, and further show that this framework can be adapted to enable cross-modality inference of protein-DNA interactions. Finally, we establish that AtacWorks can enable new biological discoveries by identifying active regulatory regions associated with lineage priming in rare subpopulations of hematopoietic stem cells. ATAC-seq measures chromatin accessibility as a proxy for the activity of DNA regulatory regions across the genome. Here the authors present AtacWorks, a deep learning tool to denoise and identify accessible chromatin regions from low cell count, low-coverage, or low-quality ATAC-seq data.
A new robotic puppy developed to help older people, particularly those living with dementia, has been launched in the UK. Ageless Innovation, a US company with ambitions to work with the NHS, makes robotic pets which can be safer and more predictable alternatives to living animals designed to comfort adults who are lonely or who have dementia. The freckled pup robot is capable of responding to human voices, being touched and hugged with realistic dog-like sounds and has a simulated heartbeat to make it appear more life-like. The battery-powered puppy resembles a liver and white cocker spaniel thanks to its soft, tufty fur, and is small and light enough to easily rest on a lap. It will go on sale in the UK for £129 from 15 March, having previously been launched in the US last October.
The technology sector has always been the disruptor by introducing new and capable advancements in the field. Although, the rapid digital transformation has effectively disrupted technology companies around the globe. They have been revamping operational processes, creating value propositions for the customers, and innovating business models. Tech firms are strongly investing in cutting-edge technologies like AI and RPA to enhance productivity and minimize costs. According to research by Bain & Company, technology companies are 12% more likely to be disrupted than companies in retail and 25% more likely than those in financial services, two other industries that have historically gone through disruptions.
Researchers from Nvidia and Harvard are publishing research this week on a new way they've applied deep learning to epigenomics -- the study of modifications on the genetic material of a cell. Using a neural network originally developed for computer vision, the researchers have developed a deep learning toolkit that can help scientists study rare cell types -- and possibly identify mutations that make people more vulnerable to diseases. The new deep learning toolkit, called AtacWorks, "allows us to study how diseases and genomic variation influence very specific types of cells of the human body," Nvidia researcher Avantika Lal, lead author on the paper, told reporters last week. "And this will enable previously impossible biological discovery, and we hope would also contribute to the discovery of new drug targets." AtacWorks, featured in Nature Communications, works with ATAC-seq -- a popular method for finding the parts of the human genome that are accessible in cells.
Researchers have succeeded in making an AI understand our subjective notions of what makes faces attractive. The device demonstrated this knowledge by its ability to create new portraits that were tailored to be found personally attractive to individuals. The results can be used, for example, in modeling preferences and decision-making as well as potentially identifying unconscious attitudes. Researchers investigated whether a computer would be able to identify the facial features we consider attractive and, based on this, create new images matching our criteria. The researchers used artificial intelligence to interpret brain signals and combined the resulting brain-computer interface with a generative model of artificial faces.
The Daily Star's FREE newsletter is spectacular! A new smartphone app designed to slash the risk of people misreading rapid Covid test results has been released. The AI-powered tech comes as 57million Covid test packs have been sent to schools ahead of the reopening in England on Monday. French researchers said up to one in five rapid Covid tests produced difficult to read pregnancy test style bands. They hoped their new xRcovid app can help boost the accuracy of the "highly subjective" readings set to take place in schools.
Aspen is disappointed as he replies, "I don't want to go to bed" and looks pleadingly at his dad. His dad shrugs and says it's not up to him. The virtual voice persists: "I need you to cooperate" and starts counting down from 10. By six, Aspen gives in and retires to his room. Aspen's father then explains to his guests how the virtual assistant, Lady, has helped him'disrupt fatherhood', where he gets to be the good cop, and the Lady gets all the bad rap.