“A variety of elements — from historical events, to river level readings, to the terrain and elevation of a specific area — feed into our models,” writes Matias. “With this information, we’ve created river flood forecasting models that can more accurately predict not only when and where a flood might occur, but the severity of the event as well.”

https://www.theverge.com/2018/9/25/17900018/google-ai-predictions-flooding-india-public-alerts

Kai-Fu Lee is the chairman of Sinovation Ventures and the president of its Artificial Intelligence Institute: “The AI revolution will have two engines — China and the United States — pushing its progress swiftly forward. It is unlike any previous technological revolution that emerged from a singular cultural setting. Having two engines will further accelerate the pace of technology.”

https://www.washingtonpost.com/news/theworldpost/wp/2018/09/24/artificial-intelligence-2/?utm_term=.0a24fb14a19f

“The initiative will harness the power of AI to focus on four priorities – helping the world recover from disasters, addressing the needs of children, protecting refugees and displaced people, and promoting respect for human rights. Our AI for Humanitarian Action program is part of Microsoft’s AI for Good suite – a growing $115 million, five-year commitment to work to unlock solutions to some of society’s biggest challenges with artificial intelligence.”

https://blogs.microsoft.com/on-the-issues/2018/09/24/using-ai-to-help-save-lives/

Microsoft’s machine learning tools for developers get smarter

Machine learning algorithms, whether in the form of “AI” or simple shortcuts for sifting through data, are incapable of making rational decisions because they don’t rationalize — they find patterns. That government agencies across the US put them in charge of decisions that profoundly impact the lives of humans, seems incomprehensibly unethical.

https://thenextweb.com/artificial-intelligence/2018/09/21/artificial-intelligence-hates-the-poor-and-disenfranchised/

As described in a paper published this week in the journal Nature, researchers from universities in the US and Italy used machine learning to train an algorithm to control a glider to navigate thermals.

https://www.theverge.com/2018/9/20/17881770/ai-machine-learning-gliders-air-currents-learning-birds

Using real-time transcription overcomes this challenge, allowing businesses to capture the entirety of the conversation and take actions on it, for instance searching for keywords or terms. With this information in hand brands can hone in on what worked and what didn’t. Is there a messaging strategy that needs adjustment? How can we change our call scripts? And so on. https://www.nexmo.com/blog/2018/08/27/ai-contact-centers-bringing-real-time-intelligence-conversation/

Machines will overtake humans in terms of performing more tasks at the workplace by 2025 — but there could still be 58 million net new jobs created in the next five years, the World Economic Forum (WEF) said in a report on Monday. https://www.cnbc.com/2018/09/17/wef-machines-are-going-to-perform-more-tasks-than-humans-by-2025.html