Reproducibility is an essential requirement for a lot of fields related to research. It also includes areas that are based on machine learning techniques. But it's also true that most of the ML-based research publications are either not reproducible or are too difficult to reproduce. The PyTorch Team announced the release of PyTorch Hub yesterday. If you don't know, PyTorch is basically a machine learning library for Python.

Neural networks are behind technologies that are revolutionizing our daily lives, such as face recognition, web searching, and medical diagnosis. These general problem solvers reach their solutions by being adapted or "trained" to capture correlations in real-world data. Having seen the success of neural networks, physicists are asking if the tools might also be useful in areas ranging from high-energy physics to quantum computing [1]. Four research groups now report on using neural network tools to tackle one of the most computationally challenging problems in condensed-matter physics--simulating the behavior of an open many-body quantum system [2–5]. This scenario describes a collection of particles--such as the qubits in a quantum computer--that both interact with each other and exchange energy with their environment.

A Los Angeles police officer wears an Axon body camera in 2017. On Thursday, the company announced it is holding off on facial recognition software, citing its unreliability. A Los Angeles police officer wears an Axon body camera in 2017. On Thursday, the company announced it is holding off on facial recognition software, citing its unreliability. The largest manufacturer of police body cameras is rejecting the possibility of selling facial recognition technology – at least, for now.

Worldwide, about 44 million people are living with Alzheimer's disease or a related form of dementia. Although 82 percent of seniors in the United States say it's important to have their thinking or memory checked, only 16 percent say they receive regular cognitive assessments. Many traditional memory assessment tools are widely available to health professionals, though deficiencies in screening and detection accuracy and reliability remain prevalent. But even with increasingly available tools like MemTrax, an online memory test based on image recognition, the clinical efficacy of this approach as a memory function screening tool has not been sufficiently demonstrated or validated. In practice, there are numerous integrated and complex factors to consider in interpreting memory evaluation test results, which presents a real challenge for clinicians.

Scientists growing miniature brains in a lab have created neural networks that act like those in the human brain. They hope the discovery will enable cheaper and easier research into brain diseases and drug development. In recent years researchers have been working on creating small, three-dimensional human brains, or cerebral organoids. The hope is that they will eventually replace animal models, imaging techniques and autopsies as tools for understanding the brain. These simplified organoids have some of the architecture of the brain's cerebral cortex – which is responsible for many of the features that make us human, such as thinking, perceiving, memory and language.

Five Japanese automakers will join a self-driving technology joint venture formed last year by Toyota Motor Corp. and SoftBank Corp., sources close to the matter said Wednesday. Mazda Motor Corp., Suzuki Motor Corp., Subaru Corp., Isuzu Motor Ltd., and Toyota's minivehicle-making unit Daihatsu Motor Corp. will each buy a stake of less than 10 percent in Monet Technologies Inc., they said. Currently, SoftBank owns 40.2 percent of the joint company, with Toyota holding a 39.8 percent stake. Honda Motor Corp. and Toyota's truck-making subsidiary Hino Motor Ltd. already have a 10 percent stake each in the venture. Monet is developing next-generation mobility services using autonomous driving technology.

In this Saturday June 15, 2019 photo customers leave an Apple store on the 3rd Street Promenade in Santa Monica, Calif. Apple has bought a struggling self-driving car startup as the iPhone maker continues to explore the potential market for robotic vehicles, despite recently curtailing its work on the technology. The Cupertino, Calif., company confirmed its acquisition of Drive.ai The Cupertino, California, company confirmed its acquisition of Drive.ai A recent filing with California labor regulators disclosed that Drive.ai

A solar-powered flying robot has become the lightest machine capable of flying without an attached power source. Weighing just 259 milligrams, the insect-inspired RoboBee X-Wing has four wings that flap at a rate of 170 times per second. It has a wingspan of 3.5 centimetres and is 6.5 cemtimetres high. The flying robot was developed by Noah Jafferis and colleagues at Harvard University. Its wings are controlled by two muscle-like plates that contract when voltage passes through them.

British workers are being shut out of decisions over the rising use of robots in the UK economy, according to a report. According to the commission on workers and technology, run by the Fabian Society and the Community trade union, almost six in 10 employees across Britain in a poll said their employers did not give them a say on the use of new technologies. Risking a future where workers' jobs get worse and people's voices go unheard over changes in the workplace, the findings come as a separate report finds the use of robots in poorer regions triggers the loss of almost twice as many jobs as in wealthier ones. In a study by the consultancy firm Oxford Economics, the rapidly growing use of robots is expected to have a profound impact on jobs across the world, resulting in up to 20m manufacturing job losses by 2030. Around 1.7m manufacturing jobs have already been lost to robots since 2000, according to the study, including as many as 400,000 in Europe, 260,000 in the US and 550,000 in China.

Researchers from the Max Planck Institute for Intelligent Systems, a member of NVIDIA's NVAIL program, developed an end-to-end deep learning algorithm that can take any speech signal as input – and realistically animate it in a wide range of adult faces. "There is an extensive literature on estimating 3D face shape, facial expressions, and facial motion from images and videos. Less attention has been paid to estimating 3D properties of faces from sound," the researchers stated in their paper. "Understanding the correlation between speech and facial motion thus provides additional valuable information for analyzing humans, particularly if visual data are noisy, missing, or ambiguous." The team first collected a new dataset of 4D face scans together with speech.