About 20 percent of youth in the United States live with a mental health condition, according to the National Institute of Mental Health. The good news is that mental health professionals have smarter tools than ever before, with artificial intelligence-related technology coming to the forefront to help diagnose patients, often with much greater accuracy than humans. A new study published in the journal Suicide and Life-Threatening Behavior, for example, showed that machine learning is up to 93 percent accurate in identifying a suicidal person. The research, led by John Pestian, a professor at Cincinnati Children's Hospital Medical Center, involved 379 teenage patients from three area hospitals. Each patient completed standardized behavioral rating scales and participated in a semi-structured interview, answering five open-ended questions such as "Are you angry?" to stimulate conversation, according to a press release from the university.

Artificial intelligence came alive in the 80s with many startups, governments, and large enterprises deploying new systems that executed tasks typically performed by human experts. These were largely rule-based systems that encoded behaviors in rules versus the strict procedural logic of traditional programming languages. Then, as memory became more affordable, systems were able to handle much more computationally-intense tasks such as machine learning, planning and scheduling, and natural language understanding. Now in the age of Big Data, many believe AI has completely changed the tech landscape, but in some ways, as the Talking Heads song goes, it's the "same as it ever was". What remains the same are the core elements of an intelligent application.

Michigan went red in the last presidential election, it has a Republican governor, and the GOP has control of both houses of the state legislature. But the Wolverine State has just enacted the most progressive autonomous driving laws in the country. Governor Rick Snyder signed the new laws into action today, in a move backed by the Detroit Three, Toyota, tech giant Google, and ride-sharing kings Uber and Lyft. As we reported when the bills originally passed through the Michigan Senate in September, the new laws mean autonomous vehicles can operate on any road in the state, at any time, and by anyone. Michigan's laws are unusual compared to Florida or California because they give companies the right to sell cars without traditional controls, like steering wheels or pedals.

Thanks to the development of new technologies like cognitive computing, virtual and augmented reality and the Internet of Things (IoT), the technology industry is experiencing massive job demand and growth. According to the Bureau of Labor Statistics, the employment of tech and computer occupations is expected to grow 12% by 2024, greater than the average for allother occupations. Nearly 500,000 jobs are projected to be added from 2014 to 2024 in technology alone. Not only that, but the newest and most in-demand tech careers are netting some of the highest salaries we've ever seen. To put it simply, tech is the future.

In the west, AI and machine learning startups and tech giants of all stripes have been doing the M&A dance. Google, Apple and the like have been busy snapping up AI/ML startups and according to CB Insights, 30 companies in the space have been acquired since 2011 (five in this year alone). Activity in Asia has been decidedly quieter, with AI research and development mostly happening at the institutional and corporate level. In the region, it seems that Japan, South Korea and China are front runners in terms of AI activity. While Japan's Toyota is putting in $1 billion to ramp up AI research, mainly into autonomous vehicles, the South Korean government is also reportedly injecting $860 million into an AI research institute.

In multiagent systems, social choice functions can help aggregate the distinct preferences that agents have over alternatives, enabling them to settle on a single choice. Despite the basic manipulability of all reasonable voting systems, it would still be desirable to find ways to reach plausible outcomes, which are stable states, i.e., a situation where no agent would wish to change its vote. One possibility is an iterative process in which, after everyone initially votes, participants may change their votes, one voter at a time. This technique, explored in previous work, converges to a Nash equilibrium when Plurality voting is used, along with a tie-breaking rule that chooses a winner according to a linear order of preferences over candidates. In this paper, we both consider limitations of the iterative voting method, as well as expanding upon it. We demonstrate the significance of tie-breaking rules, showing that no iterative scoring rule converges for all tie-breaking. However, using a restricted tie-breaking rule (such as the linear order rule used in previous work) does not by itself ensure convergence. We prove that in addition to plurality, the veto voting rule converges as well using a linear order tie-breaking rule. However, we show that these two voting rules are the only scoring rules that converge, regardless of tie-breaking mechanism.

The government should play a bigger role in developing new tools based on artificial intelligence, or we could miss out on revolutionary applications because they don't have obvious commercial upside. That was the message from prominent AI technologists and researchers at a Senate committee hearing last week. They agreed that AI is in a crucial developmental moment, and that government has a unique opportunity to shape its future. They also said that the government is in a better position than technology companies to invest in AI applications aimed at broad societal problems. Today just a few companies, led by Google and Facebook, account for the lion's share of AI R&D in the U.S.

Japan's space program, JAXA, soars this weekend after its robotic cargo spacecraft began its four-day journey to the International Space Station (ISS) on Friday. Onboard the spacecraft, called Kounotori (after the Japanese word for "white stork"), are more than four tons of cargo, including JAXA's massive debris clearing space whip and a new array of lithium ion batteries for the space station's solar arrays. Friday's cargo launch is particularly important after the failure of a Russian Progress cargo launch earlier this month. Several other cargo launches have met similar fates over the past two years. "Spaceflight's not an easy thing," said NASA astronaut Peggy Whitson in an interview aboard the ISS.

Shaunak Khire is co-founder of a stealth ML/AI startup that can analyze, write and output insights autonomously. He also is a partner at the MaghaCGI30 social impact index fund. Previously he was the co-founder of an adtech startup and has served on the global board of the Mobile Marketing Association. He was formerly part of the Clinton Global Initiative tech and poverty alleviation working groups. As the world was collectively watching results of the 2016 election, we got a barrage of emails from people congratulating our AI for predicting a Trump win.

The holding company that owns the Kansas-based Sprint Corp. has pledged to invest up to $50 billion in U.S. startup companies and acquisitions. This vow was made by Masayoshi Son, chief executive of SoftBank Group, which owns Sprint. Son made the promise following a 45-minute meeting with President-elect Donald Trump yesterday. Son (pictured above) said SoftBank will make the investment from a $100 billion technology fund that the company previously said it would raise in part using its own capital and commitments from the Saudi Arabian sovereign wealth fund. First announced in October, the SoftBank Vision Fund will create as many as 50,000 tech jobs in the U.S, according to Son.