Three independent groups of researchers have designed powerful artificial muscles that are around 100 times stronger than ours. The synthetic muscles are are designed around coiled or coiling fibres that can stretch and contract just like their natural counterparts. The muscle designs could have various applications -- from developing smart clothing that changes in response to the weather, to prosthetic limbs and robots. Three independent groups of researchers have designed powerful artificial muscles that are around 100 times stronger than ours. The same basic principle underpins the brawny robots developed by each research team -- that coiled materials can stretch just like natural muscles.

The modern world is becoming increasingly technology driven. Many areas, such as healthcare, have been quick to realise the possibilities. AI and machine learning in oil & gas focused sectors has been slower to establish itself. This is largely because the industry has been slow to realise the potential. However this is slowly changing. Machine learning in oil & gas can be used to enhance the capabilities of this increasingly competitive sector. Not only can it help to streamline the workforce. The technology can also be used to optimise extraction and deliver accurate models. These benefits are just some of the reasons why machine learning in oil & gas is becoming increasingly important. Here are 10 ways that the impact of machine learning in oil & gas industries is being felt. One of the most noticeable impacts of machine learning in oil & gas focused industries is how it transforms discovery processes. Applications employing machine learning in oil & gas enable computers to quickly and accurately analyse huge amounts of data. This includes being able to sift precisely through signals and noise in seismic data.

The Union Health Ministry is working towards using Artificial Intelligence (AI) in a safe and effective way in public health. Union Health Minister Harsh Vardhan said in Lok Sabha on July 12 that to address gaps in India's AI ecosystem and realise its economic impact, the central government has prioritised building AI technology capabilities. "The potential of AI in public health is being explored in our country. The Ministry of Health and Family Welfare (MoHFW) is working towards using AI in a safe and effective way in public health in India," he said during Question Hour. Mr. Vardhan said a few of the initiatives undertaken by the central government to use AI in public health are Imaging Biobank for cancer, for which the NITI Aayog with Department of Bio-Technology (DBT) aims to build a database of cancer-related radiology and pathology images of more than 20,000 profiles of cancer patients with focus on major cancers prevalent in India.

Artificial intelligence has given the world of banking and the financial industry as a whole a way to meet the demands of customers who want smarter, more convenient, safer ways to access, spend, save and invest their money. We've put together a rundown of how AI is being used in finance and the companies leading the way. A recent study found 77% of consumers preferred paying with a debit or credit card compared to only 12% who favored cash. But easier payment options isn't the only reason the availability of credit is important to consumers. Having good credit aids in receiving favorable financing options, landing jobs and renting an apartment, to name a few examples.

In 2017 Gartner predicted that artificial intelligence (AI) would benefit procurement and sourcing technology. That moment has arrived, according to Mike Quindazzi, managing director at PriceWaterhouseCoopers and top financial-tech influencer. "We're now in the golden age of AI, where advancements come from voluminous sets of data, new algorithms being created, computing power and the ability to do this in the cloud at scale," said Quindazzi. Procurement data has exploded because procurement has evolved into something called "intelligent spend management," which oversees all corporate purchasing processes including direct and indirect purchases, travel and external labor. Quindazzi cautions that while AI has many use cases in procurement, such as rating vendors, "there will always be a human at the end of AI processes, so there needs to be a sense of accountability."

In a wide-ranging discussion today at VentureBeat's AI Transform 2019 conference in San Francisco, AWS AI VP Swami Sivasubramanian declared "Every innovation in technology is going to be driven by developers." Sivasubramanian made the statement while talking about growing demand for machine learning engineers and internal efforts at Amazon to train more employees to use machine learning. Facebook VP Jérôme Pesenti also stressed plans to make machine learning part of each employee's job at the company. And earlier today, Amazon committed $700 million to upskilling its U.S. workers. "Amazon developed what we call Machine Learning University. This is what we use to train our own engineers on machine learning even if they didn't take it as part of their own university [course work]," Sivasubramanian said.

The introduction of AI is helping the textile manufacturers to improve efficiency and enhance capabilities of employees extracting huge business insights from historical and real-time data. FREMONT, CA: Though artificial intelligence (AI) is transforming several industries, its contribution to the field of the textile industry is relatively new. Conventionally, the textile industry has been associated with low-fixed capital investment, variable production volumes, high competitiveness, high demand on product quality, and a wide range of designs. The introduction of AI is helping the textile manufacturers to improve efficiency and enhance the capabilities of employees extracting tremendous business insights from historical and real-time data. The value of textile products is dramatically affected in case of defects.

"If we properly incorporate artificial intelligence, we can achieve a revolution with regard to sustainability. AI will be the driving force of the fourth industrial revolution," says Hendrik Fink, head of Sustainability Services at PricewaterhouseCoopers, Germany's largest auditing and consulting company. His comment aptly describes the opportunities opened up by new technical developments. In business, for example, it is now common to use systems that analyze and intelligently interpret meaningful data, with one application being the optimization of work and manufacturing processes. In the future, moreover, it will also be in the interest of small and medium-sized businesses to pay attention to sustainability and environmental issues.

In recent years there have been great strides in artificial intelligence (AI), with games often serving as challenge problems, benchmarks, and milestones for progress. Poker has served for decades as such a challenge problem. Past successes in such benchmarks, including poker, have been limited to two-player games. However, poker in particular is traditionally played with more than two players. Multiplayer games present fundamental additional issues beyond those in two-player games, and multiplayer poker is a recognized AI milestone. In this paper we present Pluribus, an AI that we show is stronger than top human professionals in six-player no-limit Texas hold'em poker, the most popular form of poker played by humans. Poker has served as a challenge problem for the fields of artificial intelligence (AI) and game theory for decades (1). In fact, the foundational papers on game theory used poker to illustrate their concepts (2, 3). The reason for this choice is simple: no other popular recreational game captures the challenges of hidden information as effectively and as elegantly as poker. Although poker has been useful as a benchmark for new AI and game-theoretic techniques, the challenge of hidden information in strategic settings is not limited to recreational games.

FRANKFURT - Volkswagen AG and Ford Motor Co. will cooperate on electric and self-driving car technology, sharing costs on a global scale to take a major step forward in the industry's disruptive transformation. VW will invest $2.6 billion in Ford's autonomous-car partner Argo AI in a deal that values the operation at more than $7 billion, the two manufacturers said Friday in a joint statement in New York, confirming a figure first reported by Bloomberg. This includes $1 billion in funding and VW contributing its Audi $1.6 billion Autonomous Intelligent Driving unit. "While Ford and Volkswagen remain independent and fiercely competitive in the marketplace, teaming up and working with Argo AI on this important technology allows us to deliver unmatched capability, scale and geographic reach," Ford Chief Executive Officer Jim Hackett said. Ford shares climbed as much as 2.1 percent as of 9:40 a.m.