For the past year, Amazon has been cracking down on sellers and third parties offering money for positive reviews. But for one team of data scientists, negative reviews on Amazon are much more interesting than positive ones. Researchers from the University of Washington's Data Science for Social Good program have set out to harness Amazon reviews to predict food product recalls. The team has developed a machine learning platform that can mine the text of Amazon reviews to make predictions about the safety of products. While the program is still in progress, it has the potential to revolutionize the process of food recalls.

Artificial intelligence is improving rapidly, and a lot of people are worried that it will lead to massive job losses. In the past, technology mostly displaced workers doing routine tasks or manual labor. But as software becomes more sophisticated, there's a growing prospect that truck drivers, teachers, and perhaps even doctors could see their jobs replaced by a robot or a computer program. Ryan Avent is an economics correspondent for the Economist who has been thinking about the economics of automation for several years. He's a technology optimist -- he thinks software and robots really will massively boost economic productivity. But in a new book, he argues that this won't necessarily be good news for ordinary workers, since a glut of underemployed workers will make it harder to bargain for higher pay.

A Cambridge entrepreneur who sold his company to Amazon is increasing the amount of angel investing he's doing now he no longer works for the e-commerce giant. William Tunstall-Pedoe sold Evi Technologies, his voice recognition startup to Amazon in 2012, for an undisclosed amount that TechCrunch reported to be around 26 million ( 20 million). Following the acquisition, Tunstall-Pedoe became part of the Amazon family. However, his investment activities have been somewhat limited over the last four years. "I did a bit of investment while I was in Amazon but obviously that was constrained by Amazon legal; I had to get permission if it overlapped at all with anything Amazon did and most things overlap with something that Amazon is doing," Tunstall-Pedoe told Business Insider at his home in Cambridge.

Amy Kennedy, Education Director of the Kennedy Forum, and wife of Patrick J. Kennedy, honoree, advocate and former U.S. Representative from Rhode Island, speaks on stage at 2016 Many Faces Of Mental Health Gala at The Pierre Hotel on April 12, 2016 in New York City. In recent months, the pervasiveness of artificial intelligence (AI) in the field of precision medicine has continuously progressed. In fact, its influence has not only concentrated in transforming healthcare systems but also revolutionizing the approaches when it comes to diagnosing diseases such as cancer, autism and now, mental health disorders. Artificial intelligence has indeed proven its potential and significance in various field of sciences. With the integration of AI into the medical field, a promising future awaits the full utilization of data-driven medicine, which was dubbed as healthcare transformation's "next frontier," Parent Herald previously noted. After proving that artificial intelligence can be useful in the diagnosis of cancer, eye diseases, autism and even in cosmetic medicine, experts found that AI's machine learning approach can potentially assist them in diagnosing mental health disorders such as schizophrenia, depression and bipolar disorders.

While that sounds insanely convoluted, the aim is to actually help humans. If a schizophrenia patient is about to have a violent episode, for instance, an EEG could trigger the release of powerful drugs. That way, they'd only get them when needed, minimizing harmful side effects. The nanobots injected into the roaches are made from so-called DNA origami that's natural and easy to program. They're also fitted with iron oxide nanoparticle "locks" that open and release drugs when exposed to an EEG-controlled electromagnet.

When you hear the words "cyborg," or "augmented human," you inescapably picture Arnold Schwarzenegger as The Terminator, the Borg from Star Trek: The Next Generation, or perhaps The Six Million Dollar Man, if you're a little older. In Hollywood, any futuristic pairing of man and machine had better be so superawesome, or so superscary, that you'd be willing to spend a good couple of hours (and dollars) being entertained by it. The crazy thing is, even though these images come from a time when technology was barely able to fake the on-screen action, we are now on the cusp of the real thing. We're entering an age that will enhance who we are as humans in ways that go well beyond these cultural clichés. Here's where the art and science of human augmentation is today, and a tantalizing peek at where it's going in the not-too-distant future. Our time as pure, natural humans has an expiration date. It had an expiration date, and it was about 2 million years ago. It was around that time that we first put technology to use to enhance what we could accomplish with just our bodies. It took the form of a crude cutting tool, and though it might not have been much to look at, it beat the hell out of having to use our teeth for everything. "It's going overboard but we don't know how to do it another way at the moment." This, according to Super You: How Technology is Revolutionizing What it Means to Be Human author Andy Walker, was the moment the human race became cyborgs. "Any technology that enhances your natural biology and gives you an advantage over somebody else to either survive or procreate is'cyborgism,'" Walker says. His definition likely flies in the face of your lovingly preserved image of Steve Austin leaping over walls in slow motion. Walker isn't the only one who takes such a liberal view of our cyborgian nature.

When artificial intelligence is as smart as humans, the world will change forever. While technological change itself is neutral, neither good nor bad, AI's effects on society will be so powerful that they've been described in both utopian and apocalyptic terms. And some futurists think those changes are just on the horizon. That includes Ray Kurzweil -- author of five books on AI, including the recent best seller "How to Create a Mind," and founder of the futurist organization the Singularity University. He is currently working with Google to build more machine intelligence into their products.

Fintech reloaded maps out a strategy showing how traditional banks should become a digital platform.

Nonmedical use of prescription medications/drugs (NMUPD) is a serious public health threat, particularly in relation to the prescription opioid analgesics abuse epidemic. While attention to this problem has been growing, there remains an urgent need to develop novel strategies in the field of "digital epidemiology" to better identify, analyze and understand trends in NMUPD behavior. We conducted surveillance of the popular microblogging site Twitter by collecting 11 million tweets filtered for three commonly abused prescription opioid analgesic drugs Percocet (acetaminophen/oxycodone), OxyContin (oxycodone), and Oxycodone. Unsupervised machine learning was applied on the subset of tweets for each analgesic drug to discover underlying latent themes regarding risk behavior. A two-step process of obtaining themes, and filtering out unwanted tweets was carried out in three subsequent rounds of machine learning.

From personalised recommendations to fraud protection, the data-crunching powers of artificial intelligence are changing the face of financial services, writes Alexey Utkin. The past few years have seen a number of exciting advances in artificial intelligence (AI) which could change the way customers interact with financial services. Examples are the evolution of predictive analytics, recommender systems, anomaly detection, decision trees, computer vision and voice recognition. These have enabled delivery of an industrial-scale personalisation and automation of various processes in the financial services industry. The majority of financial services are still aimed at specific financial products, meaning it falls to customers to analyse their own situation and then research which products they should be using.