"Will Japan be sustainable in 2050?" Our research group adopted this question as the starting point to conduct simulations of the future of Japanese society, using artificial intelligence to develop policy proposals. Figure 1 shows Japan's long-term population trends. The population rose sharply from the start of the Meiji era (1868–1912), peaking in 2008 before switching into decline. If the birthrate remains around the present rate (1.42% in 2018), Japan's population is expected to fall below 100 million after 2050, and to continue to decline thereafter.

"It's about saving as many lives as we possibly can," Tim Wood said. Wood spoke to Industrious en route to a meeting with USAID about its Global Health Supply Chain Program-Procurement and Supply Management project, implemented by Chemonics, a development contractor, and a consortium of partners, including IBM. Getting bed nets, HIV medication and other health supplies from medical storage facilities in Washington DC to remote parts of Africa is no small feat. But Wood, a global supply chain VP at IBM, and his GHSC-PSM consortium partners are doing just that. Global supply chains are crucial to any business or operation.

Now that data is the new oil, AI software startups are sprouting across the tech terrain like pumpjacks in Texas. A whopping $80 billion in venture capital is fueling as many as 12,000 new companies. Only a few will tap a gusher. Those who do, experts say, will practice six key success factors. Some of the biggest wins will come from startups with AI apps that "turn an existing provider on its head by figuring out a new approach for call centers, healthcare or whatever it is," said Rajeev Madhavan who manages a $300 million fund at Clear Ventures, nurturing nine AI startups.

President and CEO: Yoshihito Yamada) has developed a unique defect extraction AI technology that recognizes defects by reproducing "human sensibility" and "expert experience" in order to automate the appearance inspection at the manufacturing site. By providing stable detection of defects that up to now have been difficult to detect with machines, it enables further automation of appearance inspections that currently rely on human vision. This AI functionality will be added to the existing OMRON image processing system "FH Series" and will be released in the spring of 2020. In recent years, the shortage of skilled technicians and rising labor costs have become more critical, and in the manufacturing industry there is a tremendous reliance on human experience and human senses. Therefore automation of the transporting, assembly, and inspection processes that depend on people has become an urgent task for businesses.

Serial cybersecurity entrepreneur Shlomo Kramer said in a 2005 interview that cybersecurity is "a bit like Alice in Wonderland" where you run as fast as you can only to stay in place. In 2020, to paraphrase the second part of the Red Queen's observation (actually from Through the Looking Glass), if you wish to stay ahead of cyber criminals, you must run twice--or ten times--as fast as that. The 141 predictions listed here reveal the state-of-mind of key participants in the cybersecurity defense industry and highlight all that's hot today. The future is murky, but we know for sure that on January 1, 2020, the California Consumer Privacy Act (CCPA) will go into effect; that the U.S. presidential election will take place on November 3, 2020; and that on October 1, 2020, if you "wish to fly on commercial aircrafts or access federal facilities" in the U.S., you must have a REAL ID compliant card. Other than these known events, the crystal balls of the participants in this survey warn us ...

Forrester's 2020 predictions identify key market dynamics that will impact companies' growth in the coming year. Factors including heightened values-based consumer activism; the lack of clarity around Brexit; automation, Artificial Intelligence (AI) and robotics moving deeper into the organisation; and recessionary fears due to socio-political uncertainty will make 2020 a raucous year, forcing leaders to embrace adaptability. Forrester's predictions 2020 guide is underpinned by data and research found here (client access required).

This forecast is part of the Risk-Conscious Package, as one of I Know First's equity research solutions. We determine our aggressive stock picks by screening our algorithm daily for higher volatility stocks that present greater opportunities but are also riskier. Package Name: Aggressive Stocks Forecast Recommended Positions: Long Forecast Length: 3 Months (8/28/2019 – 11/28/2019) I Know First Average: 37.51% The algorithm correctly predicted 7 out 10 of the suggested trades in the Aggressive Stocks Forecast Package for this 3 Months forecast. Among the top-performing market predictions in this forecast was FRAN, which registered a return of 277.67%. MHLD and OMI also performed well for this time horizon with returns of 53.16% and 42.33%, respectively.

Facial recognition tools have significant error rates that differ by race. An AI hiring tool from Amazon "learned" gender bias against women and favored male candidates. We know diversity bias is rampant in artificial intelligence. But decisions made based on prejudiced AI systems aren't just an ethical dilemma; they're a financial one. The more unbiased a system, the more likely it is to maximize profits, make better hiring or selling recommendations and provide accurate risk predictions.

Declaring as much is a favorite line of his whenever someone asks what his two-year-old company, Hypergiant, does. What he means is that he doesn't produce anything as uniform and universal as utensils. Were he a purveyor of tableware, he wouldn't have to spend so much of his time customizing products to individual clients or explaining what can be done with them. Everybody knows what spoons are for. Contrast that with the broadest definition of what Hypergiant does in fact sell--artificial intelligence-enabled software and hardware--and you'll appreciate Lamm's problem. Even many people lacking in technological savvy have heard of AI as a force with the potential to shape much of humanity's future--for better or worse.

The use of artificial intelligence (AI) can provide an automated and accurate tool to measure a common marker of heart disease in patients undergoing lung cancer screening, according to a study presented today at the annual meeting of the Radiological Society of North America (RSNA). "The new cholesterol guidelines encourage using the calcium score to help physicians and patients decide whether to take a statin," said study co-senior author Michael T. Lu, M.D., M.P.H., director of AI in the Cardiovascular Imaging Research Center (CIRC) at Massachusetts General Hospital (MGH) in Boston in a press release about the findings. "For select patients at intermediate risk of heart disease, if the calcium score is 0, statin can be deferred. If the calcium score is high, then those patients should be on a statin." In this study, researchers trained a deep-learning system on cardiac CTs and chest CTs in which the coronary artery calcium had been measured manually.