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.

According to industry estimates, the US needs about 200,000 more workers to fill current cybersecurity roles. Globally, the gap is five times higher – an estimated 1 million workers. The issue has become such a priority that President Obama made increasing the number of cybersecurity workers a key component of his multibillion-dollar Cybersecurity National Action Plan, which was introduced earlier this year. The White House said earlier this month it plans on boosting the federal cybersecurity workforce by 3,500 new hires by year's end. But as businesses compete for scarce cybersecurity talent and policymakers weigh remedies for the digital security worker shortage, the ground underneath the profession is shifting.

The time of year when crystal balls get a viewing and many pundits put out their annual predictions for the coming year. Rather than thinking up my own, I figured I'd regurgitate what many others are expecting to happen. Chris Preimesberger (@editingwhiz), who does a monthly #eweekchat on twitter, covers many of the worries facing organizations. People focus so much on the'things' themselves rather than the risk of an internet connection. This list discusses how IoT will grow up in 2017, how having a service component will be key, the complete mess of standards and simply, 'just because you can connect something to the Internet doesn't mean that you should.' NW talks about how cyber attacks will get worse due to IoT and gives some ideas on how to protect your data in 2017.

Connected hospitals with intelligent messaging In today's hospitals, pacemakers, defibrillators and oximeters are all connected to the internet and share vitals immediately with doctors, in turn speeding response times. Hospitals have technicians, nurses, staff, billing departments, insurance providers, patients and patients' families as stakeholders, each with different requirements of information about the care given to patient. Unified Inbox offers an AI-based unified cloud IoT messaging platform for internet of things devices to connect various stakeholders, giving them the freedom to receive different messages at different frequency, with different senses of urgency in different mediums of their choice. Unified Inbox launched this at Nanyang Polytechnic in Singapore as "CUBE," the IoT-secured messaging gateway for healthcare. The artificial intelligence makes the hospitals connected, giving peace of mind to patients and their loved ones while improving efficiency in the overall hospital management and interaction with all stakeholders.

With that in mind, I'd like to share one way that Avnet has been using machine learning in the enterprise this year, with highly compelling results. In October 2016, the internet experienced a massive denial of service attack that affected more than 80 major websites and cloud service providers from Amazon to Twitter. A bit of malware that hijacked hundreds of thousands of unsecure Internet of Things devices to overwhelm specific targets. In the cybersecurity arms race, malicious hackers are increasingly looking to machines to strengthen their attacks. So larger organizations like Avnet are also tapping into the power of machines--in this case, machine learning--to strengthen our defenses.