AAAI AI-Alert for Oct 6, 2020
The robot shop worker controlled by a faraway human
In a quiet aisle of a small supermarket in Tokyo, a robot dutifully goes about its work. It looks like a well-integrated autonomous mechanical worker, but that is something of an illusion. This robot doesn't have a mind of its own. Several miles away, a human worker is controlling its every movement remotely and watching via a virtual reality (VR) headset that provides a robot's eye view. This is the work of Japanese firm Telexistence, whose Model-T robot is designed to allow people to do physical labour in supermarkets and other locations from the comfort of their own homes.
Scientists use AI to find tiny craters on Mars
The High-Resolution Imaging Science Experiment (HiRISE) camera aboard NASA's Mars Reconnaissance Orbiter took this image of a crater cluster on Mars, the first ever to be discovered by artificial intelligence (AI). NASA said, "These craters were created by several pieces of a single meteor. The largest of the craters is about 13 feet (4 meters) wide. In total, the craters span about 100 feet (30 meters) of the red planet's surface. The craters were found in a region called Noctis Fossae, located at latitude -3.213, longitude 259.415."
Synthesizing Skin Lesion Images Using Generative Adversarial Networks
According to the World Health Organization cancer is the second leading cause of death globally [1], and the most common cancer in the world is skin cancer [2]. To get a skin cancer diagnosis, a patient will usually mention their concern to a doctor. The doctor will then refer the patient to a dermatologist, who takes a closer look to determine whether the lesion is abnormal and in need of further inspection. If it's abnormal, the next step is usually a biopsy of the lesion for further testing in a laboratory. The test results determine the final diagnosis.
Twitter is making changes to its photo software after people online found it was automatically cropping out Black faces and focusing on white ones
Twitter is making changes to its photo cropping function after an investigation into racial bias in the software, the company said on Thursday. The announcement comes after users on the platform repeatedly showed that the tool -- which uses machine learning to choose which part of an image to crop based on what it thinks is the most interesting -- cuts out Black people from photos and centers on white faces instead. Tony Arcieri, a cryptography engineer, posted a series of tweets in mid-September showing how the platform's algorithm routinely chose to highlight the face of Senate Majority Leader Mitch McConnell, who is white, instead of former President Barack Obama's in multiple photos of the two. The experiment prompted others to try similar experiments with the same result, and led to the company launching an investigation into its systems shortly after. The social media company implemented its machine-learning-powered image cropping system in 2018.
These Robots Use AI to Learn How to Clean Your House
Inside an ordinary-looking home, a robot suspended from the ceiling slowly expands arms holding a sponge, before carefully wiping a kitchen surface clean. Nearby, another robot gently cleans a flat-screen television, causing it to wobble slightly. The cleaning robots live inside a mock home located at the Toyota Research Institute in Los Altos, California. The institute's researchers are testing a range of robot technologies designed to help finally realize the dream of a home robot. After looking at homes in Japan, which were often small and cluttered, the researchers realized they needed a creative solution.
Breaking the Memory Wall for AI Chip with a New Dimension
Recent advancements in deep learning have led to the widespread adoption of artificial intelligence (AI) in applications such as computer vision and natural language processing. As neural networks become deeper and larger, AI modeling demands outstrip the capabilities of conventional chip architectures. Memory bandwidth falls behind processing power. Energy consumption comes to dominate the total cost of ownership. Currently, memory capacity is insufficient to support the most advanced NLP models.
Facebook Is Giving Away This Speech Recognition Model For Free
Researchers at Facebook AI recently introduced and open-sourced a new framework for self-supervised learning of representations from raw audio data known as wav2vec 2.0. The company claims that this framework can enable automatic speech recognition models with just 10 minutes of transcribed speech data. Neural network models have gained much traction over the last few years due to its applications across various sectors. The models work with the help of vast quantities of labelled training data. However, most of the time, it is challenging to gather labelled data than unlabelled data.
How machine learning can help to future-proof clinical trials in the era of COVID-19
The COVID-19 pandemic is the greatest global healthcare crisis of our generation, presenting enormous challenges to medical research, including clinical trials. Advances in machine learning are providing an opportunity to adapt clinical trials and lay the groundwork for smarter, faster and more flexible clinical trials in the future. In an article published in Statistics in Biopharmaceutical Research, an international collaboration of data scientists and pharmaceutical industry experts--led by the Director of the Cambridge Center for AI in Medicine, Professor Mihaela van der Schaar of the University of Cambridge--describes the impact that COVID-19 is having on clinical trials, and reveals how the latest machine learning (ML) approaches can help to overcome challenges that the pandemic presents. The paper covers three areas of clinical trials in which ML can make contributions: in trials for repurposing drugs to treat COVID-19, trials for new drugs to treat COVID-19, and ongoing clinical trials for drugs unrelated to COVID-19. The team, which includes scientists from pharmaceutical companies such as Novartis, notes that "the pandemic provides an opportunity to apply novel approaches that can be used in this challenging situation."