Emerging from stealth mode, self-driving car start-up Drive.ai Drive.ai announced today its first commercial foray, a retrofit kit to make fleet vehicles, from delivery trucks to car services, self-driving. The kit includes a sensor array, computer and an LED sign to communicate with pedestrians and other drivers. Self-driving car technology is being developed by most major automakers, automotive equipment suppliers and start-up companies such as Drive.ai. The intent is to eliminate the 95 percent of fatal car accidents every year that are attributable to human error.

People convey meaning by what they say as well as how they say it: Tone, word choice and the length of a phrase are all crucial cues to understanding what's going on in someone's mind. When a psychiatrist or psychologist examines a person, they listen for these signals to get a sense of their wellbeing, drawing on past experience to guide their judgment. Researchers are now applying that same approach, with the help of machine learning, to diagnose people with mental disorders. In 2015, a team of researchers developed an AI model that correctly predicted which members of a group of young people would develop psychosis--a major feature of schizophrenia--by analyzing transcripts of their speech. This model focused on tell-tale verbal tics of psychosis: short sentences, confusing, frequent use of words like "this," "that," and "a," as well as a muddled sense of meaning from one sentence to the next.

Though I haven't lived there for nearly three decades, I still consider myself a citizen of Los Angeles. That means, among other things, I drive. For me, a car is like a suit or a good exoskeleton. Road trips, going 100 miles per hour on a freeway, racing through Park La Brea--they're all sewn as tightly into my DNA as ice-skating in Central Park is for a New Yorker. Despite that heritage, I've been running an experiment on myself and my hometown. My last three trips there, I didn't rent a car; it's been nothing but taxis, Uber, and one time I borrowed my dad's. Not only did I move through space and time every bit as efficiently--more, if you believe that screwing around on Twitter and email is useful--I took new routes.

A Markov chain is a random process with the property that the next state depends only on the current state. For example: If you have the choice of red or blue twice the process would be Markovian if each time you chose the decision had nothing to do with your choice previously (see diagram below). How can Markov Chains help us? To start with we need to define some basic terminology. The changes of state within the system are called transitions, and the probabilities associated with various state-changes are called transition probabilities.

Welcome to California Inc., the weekly newsletter of the L.A. Times Business section. Pharmaceutical company Mylan is still in the news after hiking the price of life-saving EpiPens by more than 400%. But keep this in mind: Of roughly 250 million raised for and against 17 ballot measures coming before California voters in November, more than a quarter of that amount -- about 70 million -- has been contributed by deep-pocketed drug companies to defeat the Drug Price Relief Act, which would limit drug prices charged to state healthcare programs. Spending on the measure could set a state record over coming weeks. No buzz kill: New federal rules for small commercial drones go into effect Monday.

Ariel lost 20 lbs of weight and documented his progress using a series of scripts. The VW project is co-sponsored by Microsoft and Yahoo Research. Ariel had logged his data as a simple CSV file using only weight, sleep, exercise and foods consumed as data points. He then wrote a perl script to convert his CSV over to the vowpal-wabbit traning-set. He learned which foods, exercise and sleep patterns showed a positive correlation with weight loss.

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.

The following is a condensed and edited interview with Demis Hassabis, CEO, DeepMind Technologies. Our stated mission is to solve intelligence, and we use the word "solve," because it can mean a few things. It means to understand intelligence, fundamentally understand it, and re-create it artificially. If you look at how civilization has been built and everything humans have achieved, it's down to our intelligence. It's our minds that have set us apart.

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.

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.