Artificial intelligence is one of a series of technologies that are on the radar for implementation in Chile's mining industry. AI, which, simply put, is the ability of a computer program or machine to think and learn from observing large quantities of data, to identify trends and make recommendations to improve decision making, all in a matter of milliseconds. The impending tsunami of data that will be collected from sensors and internet of things (IoT) devices will be too overwhelming for humans to compute. Businesses that are able to compute and extract value from huge volumes of data are expected to have a key advantage over their competitors by being able to improve efficiency, productivity and lower costs as well as identify new business opportunities. A recent study by consultancy Accenture, showed 82% of executives in the global mining industry expecting to increase investment in digital technology over the next three years.

Artificial Intelligence, Robotics, Machine learning-led technological innovation has already laid the foundation for higher productivity, better-income jobs, and socio-economic prosperity. In the coming years, automation will completely transform the nature and future of work, making things better and faster. However, these developments have also created the fear that the fourth industrial revolution or automation will lead to widespread labor displacement, lower wage growth, and worsen income inequality, especially in developing economies. The concerns may somehow be true as the automated technologies will replace aging and unskilled workforce with the new and technically skilled. As the Organisation for Economic Co-operation and Development has stated in its'OECD Employment Outlook 2019' report, "the risk of job automation is real but the trend varies greatly across countries. Automation technologies do not just destroy jobs, they also create and transform them. Historically, the net effects of major technological revolutions on employment have been positive, and there are few signs of this trend changing radically in the years to come."

A team of researchers from Bioversity International in Africa has created a smartphone app to help banana farmers protect their crops against diseases and pests. The Tumaini App (meaning'hope' in Swahili) is based on artificial intelligence algorithms that have been trained to recognize five major diseases and one common pest affecting the world's favorite fruit, demonstrating accuracy of more than 90 per cent in most models. The software has been tested in Colombia, the Democratic Republic of the Congo, India, Benin, China, and Uganda. Tumaini can recommend the means of addressing a specific disease and automatically upload identification data into a global database to help coordinate international response. It is hoped that the app can stop disease outbreaks and protect the livelihood of small, independent farmers.

This month, images of the burning Amazon rainforest have reverberated around the world. These fires, believed to have been set deliberately by cattle ranchers and loggers, have now spun out of control, leading to unprecedented destruction and dire warnings from environmentalists that the crisis will lead to the loss of a precious ecosystem and an acceleration of climate change. Brazil has rejected aid and the crisis has been blamed on the country's president Jair Bolsonaro, who critics say has encouraged farmers and loggers to burn far more of the forest than they typically do to clear land in order to graze cattle. But elsewhere, technology is helping some communities prevent and tackle wildfires...

When the data is distributed across multiple servers, efficient data exchange between the servers (or workers) for solving the distributed learning problem is an important problem and is the focus of this paper. We propose a fast, privacy-aware, and communication-efficient decentralized framework to solve the distributed machine learning (DML) problem. The proposed algorithm, GADMM, is based on Alternating Direct Method of Multiplier (ADMM) algorithm. The key novelty in GADMM is that each worker exchanges the locally trained model only with two neighboring workers, thereby training a global model with lower amount of communication in each exchange. We prove that GADMM converges faster than the centralized batch gradient descent for convex loss functions, and numerically show that it is faster and more communication-efficient than the state-of-the-art communication-efficient centralized algorithms such as the Lazily Aggregated Gradient (LAG), in linear and logistic regression tasks on synthetic and real datasets. Furthermore, we propose Dynamic GADMM (D-GADMM), a variant of GADMM, and prove its convergence under time-varying network topology of the workers.

India's higher education sector has supplied some of the world's best talent. The CEOs of some of the biggest Fortune 500 companies--Microsoft, Google, Mastercard, and Adobe--are a product of the Indian higher education system. The landscape has also expanded over the past decade--from 436 universities in 2009–10 to 903 in 2017–18 and from 26,000 colleges to over 39,000.1 Student enrolment, at 36.6 million, is the third-largest in the world, next to China and the United States.2 Besides, India is already in the middle of the "demographic dividend" with a surge in its younger and working-age population, which is estimated to become the world's largest by 2030.3 India is expected to account for about 20 percent of the total young talent pool supplied by the non–Organisation for Economic Cooperation and Development (OECD) G-20 countries.4

Global Augmented Analytics Market was valued US$ 4.6Bn in 2018 and is expected to reach US$ 20.2Bn by 2026 at a CAGR of 19.98%. This report provides a detailed analysis of the market segment based on insurance type, sales channel and region. This report also focuses on the top players in North America, Europe, Asia Pacific, Middle East & Africa, and South America. The objective of the report is to present a comprehensive assessment of the market and contains thoughtful insights, facts, historical data, industry-validated market data and projections with a suitable set of assumptions and methodology. The report also helps in understanding the global augmented analytics market dynamics, structure by identifying and analysing the market segments and project the global market size.

This report on global Drone Analytics market is a detailed research study that helps provides answers and pertinent questions with respect to the emerging trends and growth opportunities in this particular industry. It helps identify each of the prominent barriers to growth, apart from identifying the trends within various application segments of the global market. The global Drone Analytics market size was 2.3 million US$ and it is expected to reach 5.6 million US$ by the end of 2025, with a CAGR of 10.4% during 2019-2025. Based on industry, the drone analytics market has been segmented into agriculture & forestry, construction, insurance, mining & quarrying, utility, telecommunication, oil & gas, transportation, scientific research, and others. The construction segment is projected to grow at the highest CAGR during the forecast period.

SHANGHAI: Jack Ma believes artificial intelligence poses no threat to humanity, but Elon Musk called that "famous last words" as the billionaire tech tycoons faced off Thursday in an occasionally animated debate on futurism in Shanghai. The Chinese co-founder of Alibaba and the maverick industrialist behind Tesla and SpaceX frequently pulled pained expressions and raised eyebrows as they kicked off an AI conference with a dialogue that challenged attendees to keep up, veering from technology to Mars, death, and jobs. However, the hot topic in the hour-long talk was AI, which has provoked increasing concern among scientists such as late British cosmologist Stephen Hawking who warned that it will eventually turn on and "annihilate" humanity. "Computers may be clever, but human beings are much smarter," Ma said. "We invented the computer -- I've never seen a computer invent a human being."

Artificial intelligence and machine learning algorithms are shaping the business processes across different industries. According to California-based customer service company Zendesk, 81% of Brazilian consumers would not hesitate to abandon a brand if they received poor service. Given this scenario, companies need to constantly seek for tools that help them stay competitive, ensuring the satisfaction of users by recognizing their service area as key for business transformation. "Companies are increasingly looking for artificial intelligence solutions, especially startups, as they look to do more with less, to have more productivity at lower cost," Zendesk Brasil sales director Marcelo Rocha told BNamericas. Zendesk provides customer services solutions to 145,000 customers in over 30 languages.