File photo - M1A1 Abrams main battle tanks assigned to 3rd Battalion, 67th Armored Regiment, 2nd Armored Brigade Combat Team, 3rd Infantry Division stage prior to a tactical movement during Spartan Focus, at Fort Stewart, Ga. When dismounted U.S. Army infantry are attacking fortified enemy positions, taking hostile fire and moving quickly to find the best points for continued assault -- "battery life" can determine mission success or failure and even -- life or death. Units of forward positioned Army soldiers may not have quick access to battery recharging and may, therefore, depend entirely upon the functionality of their batteries - needed to power night vision, radios, small soldier-worn sensors, portable laptops for drone control and other combat-essential items. Without the requisite battery power to advance, soldiers might be forced to retreat or, of even greater consequence, become far more vulnerable to enemy fire. It goes without saying that attacking soldiers, especially those on the move on foot, need lightweight, electrically powered equipment for communications, data sharing, enemy tracking, targeting and some weaponry.

One of the two task forces announced to be formed by the US House Committee on financial services will be investigating the use of artificial intelligence technologies (AI) for FinTech. The focus of the task force will be to examine digital identification technologies using AI to reduce fraud. It will also look into issues such as regulating ML in the financial services industry, risks associated with algorithms & big data, and the impact of automation on jobs and the economy in the US. AI has been one of the hottest technologies used by emerging FinTech players. It is used in automation, social media analytics & intelligence tools, cybersecurity, fraud prevention, and other areas.

Bottom Line: The leading growth strategy for manufacturers in 2019 is improving shop floor productivity by investing in machine learning platforms that deliver the insights needed to improve product quality and production yields. Using machine learning to streamline every phase of production, starting with inbound supplier quality through manufacturing scheduling to fulfillment is now a priority in manufacturing. According to a recent survey by Deloitte, machine learning is reducing unplanned machinery downtime between 15 – 30%, increasing production throughput by 20%, reducing maintenance costs 30% and delivering up to a 35% increase in quality. Accenture, Manufacturing The Future, Artificial intelligence will fuel the next wave of growth for industrial equipment companies (PDF, 20 pp., no opt-in) How the IIoT can change business models. How emerging technologies can transform the supply chain.

On a tower in the Brazilian rain forest, a sentinel scans the horizon for the first signs of fire. They don't blink or take breaks, and guided by artificial intelligence they can tell the difference between a dust cloud, an insect swarm and a plume of smoke that demands quick attention. In Brazil, the devices help keep mining giant Vale SA working, and protect trees for pulp and paper producer Suzano SA. In the future, it's a system that may be put to work in California, where deadly wildfires abound. The equipment includes optical and thermal cameras, as well as spectrometric systems that identify the chemical makeup of substances.

Constrained counting is a fundamental problem in artificial intelligence. A promising new algebraic approach to constrained counting makes use of tensor networks, following a reduction from constrained counting to the problem of tensor-network contraction. Contracting a tensor network efficiently requires determining an efficient order to contract the tensors inside the network, which is itself a difficult problem. In this work, we apply graph decompositions to find contraction orders for tensor networks. We prove that finding an efficient contraction order for a tensor network is equivalent to the well-known problem of finding an optimal carving decomposition. Thus memory-optimal contraction orders for planar tensor networks can be found in cubic time. We show that tree decompositions can be used both to find carving decompositions and to factor tensor networks with high-rank, structured tensors. We implement these algorithms on top of state-of-the-art solvers for tree decompositions and show empirically that the resulting weighted model counter is quite effective and useful as part of a portfolio of counters.

Guided by artificial intelligence and powered by a robotic platform, a system developed by MIT researchers moves a step closer to automating the production of small molecules that could be used in medicine, solar energy, and polymer chemistry. The system, described in the August 8 issue of Science, could free up bench chemists from a variety of routine and time-consuming tasks, and may suggest possibilities for how to make new molecular compounds, according to the study co-leaders Klavs F. Jensen, the Warren K. Lewis Professor of Chemical Engineering, and Timothy F. Jamison, the Robert R. Taylor Professor of Chemistry and associate provost at MIT. The technology "has the promise to help people cut out all the tedious parts of molecule building," including looking up potential reaction pathways and building the components of a molecular assembly line each time a new molecule is produced, says Jensen. "And as a chemist, it may give you inspirations for new reactions that you hadn't thought about before," he adds. The new system combines three main steps.

This is part of a series of stories examining how artificial intelligence is disrupting industries. Can artificial intelligence (AI) make health care smarter? The technology sector is investing heavily in new applications for AI in medicine, in the hope that algorithms can bring new capabilities to medical diagnoses and patient care. One of the areas where artificial intelligence is emerging as a valuable tool is radiology, which offers an early study in the benefits of AI in medicine, and its potential impact on the healthcare workforce. Anytime a patient breaks a bone, sprains an ankle or hits their head, the radiology industry goes to work, using x-rays, CT scanners, MRI machines and other tools and techniques to take a closer look inside the human body without the need for surgery.

Prime Minister Boris Johnson has announced £250 million in funding to establish an NHS artificial intelligence lab – marking his third funding pledge to the health service in as many days. NHS England will receive the multi-million-pound funding, which Johnson says could help revolutionise patient care and medical research. Health Secretary Matt Hancock praised the potential of deploying AI in the NHS, saying it had "enormous power" to enhance care, save lives and to allow doctors to spend more time with patients. Due to the NHS' less than stellar record with technology, health experts have warned that any new system will require "robust evaluation" to avoid it having a negative impact on the healthcare system. If implemented without high safety standards and training, they say it could cause more harm than good.

A residency program that allows fourth-generation Japanese descendants living overseas to work in the country has been rarely used due to strict requirements such as language proficiency and age. Under the program introduced in July last year, only 43 people qualified as of June 17, compared with the annual cap of 4,000 set by the Immigration Services Agency. The agency has started discussions to ease the requirements in a bid to increase the number of qualified people. Before the program's introduction, fourth-generation Japanese descendants overseas permitted to stay in Japan were limited to unmarried and underage children of third-generation Japanese with permanent residency status. In addition, they needed to be living with their parents.

You won't find violent video game displays at Walmart anymore. Late last week the company announced it is removing them from stores. This came after President Donald Trump, commenting on the Dayton and El Paso shootings, complained from the White House about "gruesome and grisly video games that are now commonplace" and surround troubled youth with a culture that celebrates violence. House Minority Leader Kevin McCarthy, meanwhile, told Fox News he has always felt violent games present "a problem for future generations and others." Would someone please point out to our leaders -- neither of whom cited actual evidence -- that they are more than a decade behind the scientific consensus?