You know the moment when you go in for a yearly physical and the doctor asks, "So, how have you been?" I can't recall what I ate yesterday, let alone remember a pattern of headaches or the overall quality of my sleep. The problem is that I am human. I forget and can be lax when it comes to taking care of myself. Most health issues sneak up on us, and we're not inherently wired to remember patterns.

Scientists say machine learning is up to 93 percent accurate in identifying a suicidal person based on their responses to interview questions. The algorithm was described in a study published in the journal Suicide and Life-Threatening Behavior. Researchers were able to use the tool to classify patients as being suicidal, mentally ill but not suicidal, or neither. "These computational approaches provide novel opportunities to apply technological innovations in suicide care and prevention, and it surely is needed," study author John Pestian said in a press release. "When you look around healthcare facilities, you see tremendous support from technology, but not so much for those who care for mental illness. Only now are our algorithms capable of supporting those caregivers."

When it comes to maintaining the mental health and wellness of American citizens, the 2016 presidential election cycle has been less than ideal. In a recent article in Politico, therapists and their clients described how the last several months of political turmoil have thrown them for a loop. One psychologist even commissioned a poll of 1,000 voter-age respondents to probe the emotional impact of the election. The results: Nearly 30 percent of respondents reported emotional distress due to Hillary Clinton's campaign, while over 40 percent reported emotional distress due to Donald Trump's campaign. Perhaps most tellingly, a whopping 90 percent of those who reported emotional distress felt that the toll of this election was worse than any other election in the past, offering perspective into the general American psyche right about now.

New research published in the journal Suicide and Life-Threatening Behavior shows how machine learning can help identify suicidal behavior using a person's spoken or written words. The technology was able to pinpoint which participants in the study were suicidal, mentally ill but not suicidal, or neither in the vast majority of cases. John Pestian and a team of researchers studied 379 patients from emergency departments and inpatient and outpatient centers at three locations between Oct. 2013 and March 2015. The patients, who were classified as suicidal, mentally ill but not suicidal, or neither (serving as the control group), answered standardized behavioral rating tests and took part in a semi-structured interview in which they were asked five open-ended questions such as "Do you have hope?" and "Are you angry?" to stimulate conversation. The researchers then pulled verbal and non-verbal language (e.g., laughs, sighs, etc.) from the gathered data and used machine learning algorithms to analyze it.

With Alexa and Google Assistant are gunning for control over the general voice-driven experience with technology, that might open doors for some more targeted verticals that are centered around voice. It's not an unheard of strategy -- building services and tools around specific experiences rather than trying to do it all at once has been an effective approach for many startups in Silicon Valley. Those services can even try to slot into larger platforms like an Alexa or a Google Assistant. And in the case of Hello, the makers of a sleep-tracking orb called Sense, that's what they're hoping to do with by launching new version of the device that enables voice control. "As a company we're trying to get rid of intrusive tech from your life -- how do you have more tech like Sense that blends in and disappears," Proud said.

Artificial intelligence can thank Hollywood for its bad rep. Movies like "Ex Machina" and the "Terminator" series conjure up futuristic doomsday scenarios where intelligent machines wreak havoc on humans. However, in real life, humans are already surrounded by artificial intelligence. Amazon and Netflix recommendation engines suggest books or movies based on previous selections, Google Now reroutes drivers around traffic accidents on the commute home, and smartphone digital assistants like Apple's Siri and Microsoft's Cortana answer questions about the weather and sports scores. Brands are using artificial intelligence to build better customer experiences and they're just getting started.

Mastercard has announcedplans to launch an artificial intelligence (AI) bot platform that allows consumers to transact, manage finances, and shop via messaging platforms. The Mastercard bot for banks will extend Mastercard services to customers on messaging platforms and make financial information and decisions part of consumers' everyday lives. In the pilot phase, Mastercard is partnering with Kasisto, the company that powers branded virtual assistants and smart bots for financial services and is a current participant in the Mastercard Start Path Global program. The Mastercard bot is powered by KAI Banking, a conversational AI platform with deep knowledge in financial services. It can fulfill customer requests and solve problems on messaging platforms such as Facebook Messenger and SMS, enabling financial institutions to create entirely new consumer experiences – ones that are as easy and natural as texting a friend.

"It's not just a normal update," Uber CEO Travis Kalanick said during a press briefing Tuesday at the company's swanky San Francisco headquarters. "This is a radical redesign and rebuild of the app from scratch." Uber's premise is simple: It pairs drivers with passengers via smartphone app. In the past seven years, it has gone from a small startup to one of the largest ride-hailing services on the planet, operating in more than 70 countries. With a valuation of $68 billion, Uber is also the world's highest-valued venture-backed company.

The UK fintech market is experiencing a new wave of innovation. Developments in artificial intelligence and machine learning are giving rise to a new generation of fintech startups. Prop trading houses and hedge funds have been using machine learning techniques for years to beat financial markets. It's interesting to see A.I. making its way into mainstream fintech. Companies are leveraging the technology to make sense of large volumes of data, making financial products and services more accessible for the end user.

BOT TO THE FUTURE: Mastercard wants to make commerce'more conversational' Mastercard has unveiled plans to launch artificial intelligence (AI) bots for its merchant and bank partners, allowing consumers to use chat, messaging and natural language interfaces to shop and manage their finances. Mastercard KAI, the payments giant's bot for banks, will allow consumers to ask the bot questions about their accounts, review purchase history, monitor spending levels and receive contextual offers. Meanwhile, the Mastercard Bot for Merchants will allow consumer to shop and transact on messaging platforms and then check out with the Masterpass global digital payment service. According to research firm Gartner, nearly US$2bn in online sales will be performed exclusively through mobile digital assistants by the end of 2016. Kiki Del Valle, SVP at Mastercard, explained to NFC World the company was aiming to make commerce "more conversational by combining secure digital payments and artificial intelligence technology".