Wearable health monitors, ubiquitous sensors, and the ability to collect and store huge amounts of data are creating challenges for researchers hoping to use artificial intelligence to identify diseases. While the gathered data can hold important clinical answers, finding those answers means that the data must be categorized and labeled. Now, researchers at MIT have developed a system that can autonomously identify signs of a disease from data gathered from a relatively small group of people and without any initial training. The research, recently presented at the Machine Learning for Healthcare conference in Ann Arbor, Michigan, focused on learning the audio biomarkers of vocal cord disorders. Using data gathered over a week from an accelerometer attached to the necks of 100 people, the system automatically identified which sound characteristics were important for identifying whether a patient has vocal cord nodules.

New AI systems have beyond-human cognitive abilities, which many of us fear could potentially dehumanize the future of work. However, by automating these skills, AI will push human professionals up the skillset ladder into uniquely human skills such as creativity, social abilities, empathy, and sense-making, which machines cannot automate. As a result, AI will make the workplace more human, not less. This is the gift of AI to Mankind. However, humans will need to change jobs and learn new skills throughout their lives.

If you stumble over your grammar, take comfort in this: Tech companies are supercharging their digital grammar editors with artificial intelligence and machine learning in an attempt to make clear, persuasive writing easier than ever. Google became the latest to enter the game last week, when the tech giant announced it would be adding an artificial intelligence-powered tool that offers automatic detection of grammar mistakes while composing messages in Gmail, as well as auto-correction of some common spelling mistakes. The company introduced a similar AI-driven function to documents in G Suite earlier this year. While some education experts applaud the advancement of high-tech grammar tools as a way to help people more clearly express their thoughts, others aren't so sure. Artificial intelligence, according to the contrarians, is only as smart as the humans who program it, and often just as biased.

How do new scientific disciplines get started? For Iyad Rahwan, a computational social scientist with self-described "maverick" tendencies, it happened on a sunny afternoon in Cambridge, Massachusetts, in October 2017. Rahwan and Manuel Cebrian, a colleague from the MIT Media Lab, were sitting in Harvard Yard discussing how to best describe their preferred brand of multidisciplinary research. The rapid rise of artificial intelligence technology had generated new questions about the relationship between people and machines, which they had set out to explore. Rahwan, for example, had been exploring the question of ethical behavior for a self-driving car -- should it swerve to avoid an oncoming SUV, even if it means hitting a cyclist?

San Diego-based apps and security company Edge has secured $400,055 in seed funding, according to company database Crunchbase, topping the city's recent funding headlines. The cash infusion was announced on August 19. According to its Crunchbase profile, "Edge is an SDK platform that enables its users to develop security applications for its clients. Its product range includes client-side encryption, data backup, password recovery, blockchain technology, private key authentication, IoT, financial applications, bitcoin and private messaging. Edge (formerly Airbitz) was founded in 2014 and is based in California."

A prominent futurist warns that humans may soon cede their top spot on Earth's hierarchy to their own artificially intelligent creations. In a new book, scientist, environmentalist, and futurist, James Lovelock, describes what he calls the'Novacene,' -- a new age in which humans could be eclipsed by intelligent machines. 'Our supremacy as the prime understanders of the cosmos is rapidly coming to end,' writes Lovelock in a new book titled'Novacene' according to NBC. 'The understanders of the future will not be humans but what I choose to call'cyborgs' that will have designed and built themselves.' Humans may be forced to pass the torch due to impending disasters like climate change. In the Novacene -- which means literally'new age' -- Lovelock says that the replacement of humans won't necessarily be a violent or'Terminator'-like shift, but will instead be more of an evolutionary one. Unlike biologically driven changes of the past, organic creatures will take a backseat to technology. 'I think of cyborgs as another kingdom of life,' he tells NBC.

The batteries used to power electric vehicles have several key characterizing parameters, including voltage, temperature, and state of change (SOC). As battery faults are associated with abnormal fluctuations in these parameters, effectively predicting them is of vital importance to ensure that electric vehicles operate safely and reliably over time. Researchers at the Beijing Institute of Technology, the Beijing Co-Innovation Center for Electric Vehicles and Wayne State University have recently developed a new deep learning-based technique to synchronously predict multiple parameters of battery systems used for electric vehicles. The method they proposed, presented in a paper published in Elsevier's Applied Energy journal, is based on a long short-term memory (LSTM) recurrent neural network; a deep learning architecture that can process both single data points (e.g. "This paper investigates a new deep-learning enabled method to perform accurate synchronous multi-parameter prediction for battery systems using a long short-term memory (LSTM) recurrent neural network," the researchers wrote in their paper.

The oldest known knitting item dates back to Egypt in the Middle Ages, by way of a pair of carefully handcrafted socks. Although handmade clothes have occupied our closets for centuries, a recent influx of high-tech knitting machines have changed how we now create our favorite pieces. These systems, which have made anything from Prada sweaters to Nike shirts, are still far from seamless. Programming machines for designs can be a tedious and complicated ordeal: When you have to specify every single stitch, one mistake can throw off the entire garment. In a new pair of papers, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have come up with a new approach to streamline the process: a new system and design tool for automating knitted garments. In one paper, a team created a system called "InverseKnit," that translates photos of knitted patterns into instructions that are then used with machines to make clothing.

We've entered an era in which marketeres are being bombarded by volumes of data about consumer preferences. In theory, all of this information should make grouping users and creating relevant content easier, but that's not always the case. Generally, the more data added to a marketer's workflow, the more time required to make sense of the information and take action. Machine learning is a subset of artificial intelligence. The technology equips computers with the capacity to analyze and interpret data to proffer accurate predictions without the need for explicit programming.

Only 9% of people with pancreatic cancer live for five years after diagnosis. "That is an abysmally low number, probably the worst in human cancers," says Michael Wallace, M.D., a digestive disease specialist at the Mayo Clinic campus in Florida. "We want to get that rate substantially higher." Artificial intelligence is providing a way to do just that. In collaboration with the University of Central Florida (UCF), Mayo Clinic has developed an algorithm that can identify individuals at high risk of pancreatic cancer.