According to a recent press release, "Today, the U.S. Department of Energy's (DOE's) Advanced Research Projects Agency-Energy (ARPA-E) announced $15 million in funding for 23 projects to accelerate the incorporation of machine learning and artificial intelligence into the energy technology and product design processes as part of the Design Intelligence Fostering Formidable Energy Reduction (and) Enabling Novel Totally Impactful Advanced Technology Enhancements (DIFFERENTIATE) program. Launched in April of this year, the DIFFERENTIATE program aims to develop streamlined solutions to next-generation energy challenges. The program identified three general mathematical optimization problems that are common to many design processes. The selected projects then conceptualized machine learning and artificial intelligence-based solutions to help engineers execute and solve these problems in a manner that dramatically accelerates the pace of energy innovation." The release goes on, "Following the initial round of Phase I funding for the DIFFERENTIATE program, additional funding will be available to qualifying awardees at a future date… DIFFERENTIATE projects include: Iowa State University – Ames, Iowa. Iowa State University will develop machine learning tools to accelerate the inverse design of new microstructures in photovoltaics. The team will create a new deep generative model to combat challenges in real-world inverse design problems. The proposed inverse design tools, if successful, will produce novel, manufacturable material microstructures with improved electromagnetic properties relative to existing technology."

In his blog post on artificial intelligence (AI), GovTech Graduate Jonathan Manning draws on the New Zealand Law Foundation: Government use of artificial intelligence in New Zealand (the NZFL report) to discuss the role and effectiveness of explanation tools. As algorithms and AI become ubiquitous we all become'data subjects' to organisations such as governments and businesses. In response, regulations such as the EU's General Data Protection Regulation are beginning to emerge. The New Zealand government is currently exploring how governments, business and society can work together to meet the challenge of regulating AI. A part of this challenge is ensuring when things like algorithmic harm arise, we can explain what happened and why so that mistakes can be fixed and not repeated or obscured.

Crucially, Chinese policymakers see information technology, including AI, as a way of reducing the attainment gaps between schools in rural and urban areas.

The Chinese have a very public, very-deep, extremely well-funded commitment to AI. Air Force General VeraLinn Jamieson says it plainly: "We estimate the total spending on artificial intelligence systems in China in 2017 was $12 billion. We also estimate that it will grow to at least $70 billion by 2020." According to the Obama White House Report in 2016, China publishes more journal articles on deep learning than the US and has increased its number of AI patents by 200%. China is determined to be the world leader in AI by 2030.

Artificial intelligence is expected to reshape the future workplace - drastically changing or replacing entire jobs. In fact, companies are already employing AI-based technologies to recruit talent and evaluate workers' performance. The central question has emerged: To what extent will AI and automation continue to change the workforce and what does it mean for both blue-collar and white-collar workers? On Wednesday, November 20, POLITICO held a deep-dive conversation on how AI is transforming the American workplace and what legislative and policy solutions should be implemented to address this shift.

When Facebook started automatically tagging faces in uploaded images, nobody realized that this facial recognition technology would hike up to tracking people down while walking on the streets. In the past several years, this disruptive technology has gained immense popularity, that it is now used everywhere, from airports to shopping centers, to law enforcement. With its growing predominance in national safety and security, the face recognition market is estimated to reach USD 11.30 Billion by 2026. "Facial recognition has been around for a long time--like the 1960s. Perhaps the father of facial recognition, Woodrow Wilson Bledsoe, an American mathematician and computer scientist who classified photos of faces all by hand, (RAND tablet), even he might have been alarmed at how facial recognition technology is supercharged today by advances in computing power, 5G speeds and AI paired with machine learning."– Moreover, the advancements in artificial intelligence and machine learning are bringing about an active expansion to this technology.

The AI Organization used numerous algorithms to achieve an AI based prediction of a digital map of what the world will look like if President Trump is impeached and removed from office. The algorithms achieved a 93% predictability result on more than 1,000 simulated scenarios. The score never dropped to below an average of 93%, even after inputting digital codes built into Google and Baidu via Chinese influence and corporate mandates that were against the U.S and the Trump Administration. This digital report and the A.I. algorithms used the Geo-Political infrastructure and connected it with health, military, the intelligence community, human rights, safety of the U.S and the world at large. These algorithms involve the entire human race.

New technologies such as Artificial Intelligence and its subset, Machine Learning, Computer Vision, IoT, Cloud Technologies, Smart Robotics and Mobility are fostering innovation in the connected and autonomous vehicles industry.

Since the recent past years, Artificial Intelligence (AI) is a buzzword in the market. Global industries are eying at Artificial intelligence to grab profitability. This is leading to increased attention towards AI and its applications. The companies are investing in emerging technologies like machine learning (ML), deep learning, predictive analytics, speech and image recognition, natural language processing (NLP) technologies to fuel their business. In particular, machine learning and deep learning are emerging as the most fastest-growing technologies of artificial intelligence.

"Will these developments enable people to attain higher living standards, better working conditions, greater economic security, and improved health and longevity? The answers to these questions are not predetermined. They depend upon the institutions, investments, and policies that we deploy to harness the opportunities and confront the challenges posed by this new era," the report said. The warning signals keep flashing. In the past week alone, the Federal Reserve Bank of San Francisco, issued a report saying that automation has "contributed substantially" to reducing the portion of national income that goes to US workers over the past two decades, Bloomberg News reported. Technological efficiencies will result in an estimated 200,000 job cuts in the US banking industry in the next decade, according to a Wells Fargo & Co. report, Bloomberg also reported.