Mobile transportation platform provider, Didi Chuxing (DiDi), has launched an initiative to fully understand the social impact on communities of artificial intelligence (AI).

The company, which offers a range of app-based transportation options for 550 million users including taxi, carpooling and bike-share, made the announcement at its Tech Day in Beijing, where it also unveiled its latest developments in AI with industry partners, academia, students and engineers.

At the event, DiDi’s tech executives, led by Bob Zhang Bo, chief technology officer, shared details of breakthroughs in the company’s popular Express Pool service, which aims to improve the user experience by using machine learning algorithms. Operating across more 100 cities in China, Express Pool now accounts for over 20 per cent of all trips in many core markets.

Machine learning for better mobility

It said the algorithms can help carpooling become the most effective mobility option for drivers to increase their income, for passengers to reduce costs, and for cities to enjoy a high level of efficiency in the transportation system.

DiDi also debuted two pilot projects slated for street testing: its indoor augmented reality (AR) navigation and a driver voice assistant. The interactive, app-based AR navigation service, which is built on computer vision positioning and 3D scene reconstruction technology, can help passengers seamlessly navigate through large buildings, such as airports, train stations and malls, to reach a vehicle pick-up location.

The driver voice assistant, which is voice-activated via an in-vehicle smart device, is designed to provide a full spectrum of services ranging from audio and video content search, information inquiry and temperature adjustment, to passenger communications, customer service, and even refuel, recharging or repair services.

Understanding AI’s social impact

Its AI for Social Good project has been launched in conjunction with more than 10 founding partners, which include the China Cultural Information Service Centre for the Visually Impaired, China Research Centre of Information and Accessibility for Disability, National Engineering Laboratory for Big Data Analysis and Technique, School of Environment of Tsinghua University and the Special Education College of Beijing Union University.

DiDi believes that as we develop more powerful AI capabilities, tech companies need to work more closely with communities to fully understand AI’s social impacts and to reinforce its social commitments. The initiative will seek joint technological and social solutions to environmental, safety, health and accessibility challenges.
The company is committed to collaborating with cities, the taxi industry and communities to solve the world’s transportation, environmental, and employment challenges with smart transportation innovations. It is working with a growing alliance of car industry players to build out an auto-solution and operation platform.

Globally, it is also in a partnership network with Grab, Lyft, Ola, Uber, 99, Taxify, and Careem, reaching over 80 per cent of the world’s population and covering more than 1,000 cities.

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Big Data was not created to be big by premeditation. Instead, it is a logical result of the accumulation of data related to consumer habits, tastes, and expectations, as well as the growing sharing of this data, plus worldwide communication, media storage, and entertainment.

Big Data manages a lot. Everything, to some people, but whatever your level of technological prowess, the worldwide system of networks and data centers that make up Big Data likely manages something important to you.

It is true that Facebook, Google, and the other big companies rely on certain types of predictive algorithms to work through their massive amounts of data. These are AI systems that require technical and financial resources that small businesses can’t typically afford.

While often associated with large companies, Big Data can also benefit small businesses that want to tap into new development opportunities.

And these businesses don’t need to make heavy investments in infrastructure or human resources to do so. There are various solutions that make Big Data accessible to almost any business. This is the “how” question.

On the other hand, for the “why” question, Big Data can be integrated into BtoC and BtoB strategies of businesses to help them address at least five key challenges.

5 Ways Big Data can Improve Your Small Business:

1. Customer UX (User Experience)

Big data reveals information about customers and their shopping habits that can be used to understand customer behavior and ensure a better experience for them and the business through marketing, sales, and customer service.

Offering a personalized experience for customers provides a competitive advantage to small businesses that translates into revenue and growth.

In a recent research report, the Boston Consulting Group (BCG) expects businesses that create personalized customer experience to increase their revenue by 6 – 10%.

What’s one example of Big Data making this a possibility? We’re sure you’ve seen ads for Squarespace, Wix, and more. These tools can help you build attractive web spaces for your business no matter how small.

2. Predictive Marketing

Understanding the behavior of customers now will help you anticipate the evolution of their needs and tailor effective marketing campaigns accordingly.

If traditional marketing strives to understand consumers to bring them the product that best meets their needs, predictive marketing, thanks to Big Data, goes beyond product or service recommendation.

Predictive marketing is about knowing customers’ desires before they even think about it, and to propose a personalized service that evolves according to the behavior of the customer.

There are web-based tools you can use to do just that. Check out what’s trending on Buzzsumo in relation to your products and services to see who’s attracting the most attention in your neck of the woods.

3. Product Innovation

The two first points above converge to make the often risky endeavor of product innovation, well, less risky.

Big Data also helps brands improve their existing products and/or services (customer UX) or innovate and create new ones to meet future needs (anticipation and predictive marketing).

User data analytics (knowing which features make customers tick and which don’t, detecting problems and discovering new opportunities) allow businesses to improve product adoption and accelerate innovation. If you use a web page for part of your business, check out Google Analytics to see which parts of your page are attracting the most attention.

Tech companies have the ability to design, develop and roll out new attractive products at short periods of times thanks in a large part to Big Data.

4. Decision Making Process

Big Data is changing the paradigm of decision making and can bring much more than Business Intelligence in this regard.

Traditional decision-making processes require internal expertise. However, having a dedicated BI center is not within the reach of all businesses, but if they take advantage of Big Data, it is accessible.

For example, Big Data, via the internet and advanced search engines, allows you to seek out your competitors. From there, you’re able to understand the best ways to stand out to consumers that may have otherwise just stuck with the competition.

A data-centric company is a company that knows how to fructify data and use it to manage every aspect of business.

Big Data enables smaller companies to make informed decisions and choose the right investment to create more wealth.

5. Get Ready for Insights-Driven Business

Competition is getting increasingly intrusive, and you should make use of your own user data before someone else does!

The majority of business leaders plan on taking advantage of Big Data and you should be one of them if you don’t want to be left behind.

In a study entitled Big and Fast Data: The Rise of Insight-Driven Business by Capgeminiand EMC², 75% of business leaders said they will be using Big Data to transform, reorganize and restructure their businesses.

Per the report, 64% of respondents said non-traditional players were getting into their territory, and 53% expect increased competition enabled by data.

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Guizhou province takes advantage of new technology to develop economy, boost employment and combat poverty

Guizhou in Southwest China struggled with unemployment and poverty before big data created a big future for the province.

Nestled in a mountainous region, it has been transformed in the past three years into an innovation hub as major global companies, such as Apple Inc, Alibaba Group Holding Ltd and Hyundai Motor Group, flocked to the area.

“Big data has helped relieve local poverty as it has brought huge opportunities to impoverished areas and created jobs at the same time,” said Jing Yaping, deputy director of the bureau responsible for Guizhou province’s big data development.

Innovation and cutting-edge technology has fueled economic growth across China with big data playing a crucial role.

This transformation is in line with General Secretary Xi Jinping’s remarks during the 19th National Congress of the Communist Party of China.

Xi emphasized that innovation is the primary force driving development.

“We will move Chinese industries up to the medium-high end of the global value chain, and foster a number of world-class advanced manufacturing clusters,” he said.

Xi called for more efforts to develop advanced manufacturing, promote further integration of the internet, big data and artificial intelligence with the real economy.

Guizhou has certainly adopted this approach to achieve rapid growth.

Official data showed the industrial output of large-scale digital information manufacturing in the province was at 5.26 billion yuan ($800 million) in the first half of this year, a jump of 64 percent compared to 2016.

It was first time the sector had contributed double-digit numbers to industrial growth.

“In Guizhou, big data has become the new growth engine for economic transformation,” said Qin Rupei, executive vice-governor of Guizhou, and a delegate at the Congress.

Figures also revealed that software and IT services produced revenue of 15.59 billion yuan in the first half of 2017, a 36.4 percent increase year-on-year.

“Thanks to big data, Guizhou has been able to rejuvenate itself,” Jing, of the big data bureau, said.

An hour’s drive out of the provincial capital of Guiyang is Guian New Area, a 1,795-square-kilometer industrial technology park, packed with blue-chip brands.

Hyundai is one of the latest big names to open a big data center there. The South Korea-based automotive company plans to collate and analyze massive data for its advanced automated vehicles. It will also use the information for research and development.

“Hyundai Motor’s knowhow in big data analysis, coupled with Guizhou province’s push into (the sector), will surely accelerate development in connected car technologies,” Hwang Seung-ho, executive vice-president and head of the auto intelligence division at Hyundai, told the company’s website.

Earlier this year, China Daily reported that more than 400 companies in the big data industry had set up in Guian New Area, including Apple, Microsoft, Alibaba, Tencent Holdings Ltd and Huawei Technologies Co Ltd.

China’s major telecom operators, China Telecommunications Corp, China Mobile Communications Corp and China United Network Communications Group Co Ltd, also have centers there.

Up to 20 Fortune 500 companies and 14 of China’s top 500 firms have a presence in the technology park.

Apple, for example, invested $1 billion on its first big data center in the country. The Guian setup will be used to help meet growing demand for advanced cloud services.

The global tech giant’s decision to ramp up investment in China comes at a time when it is losing ground to domestic rivals such as Huawei.

Still, this move will cement its place in the market here.

“The big data industry will play an important role in helping Guian build a modern industrial system, create more jobs and improve administrative efficiency,” said Ma Changqing, then head of the administrative committee of Guian New Area.

“We are developing a smart city,” Ma added.

Another high-profile business in Guizhou is FAST or the Five-hundred-meter Aperture Spherical radio Telescope. The installation recently celebrated its first anniversary there.

Known as the world’s largest radio telescope, it is able to collect celestial big data by detecting emissions from stars and galaxies across the cosmos.

FAST has also been used to study pulsars, which is short for pulsating radio stars.

“New discoveries, such as pulsars, have been made by FAST, which is of great importance to solving key physics problems,” the National Astronomical Observatories of China stated in a media conference.

Back on earth, leading cloud service provider Baishan Cloud has increased its sales volume by more than 50-fold since opening up in Guizhou in 2015, although the private company declined to disclose further financial information.

Indeed, firms such as Baishan Cloud have helped create jobs and fuel the province’s economy.

Last year, e-commerce turnover in the province’s rural areas increased by 27.1 percent and helped the added value side of the agricultural processing industry.

Statistics from Guizhou Poverty Alleviation Office also showed that poverty rates dropped from 26.8 percent in 2012 to 10.6 by the end of last year. Additionally, up to 1,500 villages have been removed from the poverty-stricken list.

“We have made significant progress in fighting poverty in the past few years through industry development,” said Qin Rufang, deputy director of Poverty Relief Office of Guizhou province.

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Applying big data analysis to mineralogy offers a way to predict minerals missing from those known to science, where to find them, and where to find new deposits of valuable minerals such as gold and copper, according to a groundbreaking study.

In a paper published by American Mineralogist, scientists report the first application to mineralogy of network theory (best known for analysis of e.g. the spread of disease, terrorist networks, or Facebook connections).

The results, they say, pioneer a way to reveal mineral diversity and distribution worldwide, mineral evolution through deep time, new trends, and new deposits.

Led by Shaunna Morrison of the Deep Carbon Observatory and DCO Executive Director Robert Hazen (both at the Carnegie Institution for Science in Washington, D.C.), the paper’s 12 authors include DCO colleagues Peter Fox and Ahmed Eleish at the Keck Foundation sponsored Deep-Time Data Infrastructure Data Science Teams at Rensselaer Polytechnic Institute, Troy NY.

“The quest for new mineral deposits is incessant, but until recently mineral discovery has been more a matter of luck than scientific prediction,” says Dr. Morrison. “All that may change thanks to big data.”

Humans have collected a vast amount of information on Earth’s more than 5,200 known mineral species (each of which has a unique combination of chemical composition and atomic structure).

Millions of mineral specimens from hundreds of thousands of localities around the world have been described and catalogued. Databases containing details of where each mineral was discovered, all of its known occurrences, and the ages of those deposits are large and growing by the week.

Databases also record essential information on chemical compositions and a host of physical properties, including hardness, color, atomic structure, and more.

Coupled with data on the surrounding geography, the geological setting, and coexisting minerals, Earth scientists now have access to “big data” resources ripe for analysis.

Until recently, scientists didn’t have the necessary modelling and visualization tools to capitalize on these giant stockpiles of information.

Network analysis offers new insight into minerals, just as complex data sets offer important understanding of social media connections, city traffic patterns, and metabolic pathways, to name a few examples.

“Big data is a big thing,” says Dr. Hazen. “You hear about it in all kinds of fields—medicine, commerce; even the US National Security Agency uses it to analyze phone records—but until recently no one had applied big data methods to mineralogy and petrology.”

The network analysis technique enables Earth scientists to represent data from multiple variables on thousands of minerals sampled from hundreds of thousands of locations within a single graph.

These visualizations can reveal patterns of occurrence and distribution that might otherwise be hidden within a spreadsheet.

In other words, big data provides an intimate picture of which minerals coexist with each other, as well as what geological, physical, chemical, and (perhaps most surprising) biological characteristics are necessary for their appearance.

From those insights it’s a relatively simple step to predict what minerals are missing from scientific lists, as well as where to go to find new deposits.

Says Dr. Hazen: “Network analysis can provide visual clues to mineralogists regarding where to go and what to look for. This is a brand new idea in the paper and I think it will open up an entirely new direction in mineralogy.”

Already the technique has been used to predict 145 missing carbon-bearing minerals and where to find them, leading to creation of the Deep Carbon Observatory’s Carbon Mineral Challenge. Ten have been found so far.

The estimate came from a statistical analysis of carbon-bearing minerals known today, then extrapolating how many scientists should be looking for.

Predicted before they were found

“We have used the same kinds of techniques to predict that at least 1,500 minerals of all kinds are ‘missing,’ to predict what some of them are, and where to find them,” Dr. Hazen says.

Says Dr. Morrison: “These new approaches to data-driven discovery allow us to predict both minerals unknown to science today and the location of new deposits.

Additionally, understanding how minerals have changed through geologic time, coupled with our knowledge of biology, is leading to new insights regarding the co-evolution of the geosphere and biosphere. ”

In a test case, the researchers explored minerals containing copper, which plays critical roles in modern society (e.g., pipes, wires), as well as essential roles in biological evolution. The element is extremely sensitive to oxygen, so the nature of copper in a mineral offers a clue to the level of oxygen in the atmosphere at the time the mineral formed.

The investigators also performed an analysis of common minerals in igneous rocks-those formed from a hot molten state. The mineral networks of igneous rocks revealed through big data recreated “Bowen’s reaction series” (based on Norman L. Bowen’s painstaking lab experiments in the early 1900s), which shows how a sequence of characteristic minerals appears as the magma cools.

The analysis showed the exact same sequence of minerals embedded in the mineral networks.

The researchers hope that these techniques will lead to an understanding and appreciation of previously unrecognized mineral relationships in varied mineral deposits.

Mineral networks will also serve as effective visual tools for learning about mineralogy and petrology – the branches of science concerned with the origin, composition, structure, properties, and classification of rocks and minerals.

Network analysis has numerous potential applications in geology, both for research and mineral exploration.

Mining companies could use the technology to predict the locations of unknown mineral deposits based on existing data.

Researchers could use these tools to explain how Earth’s minerals have changed over time and incorporate data from biomarker molecules to show how cells and minerals interact.

And ore geologists hope to use mineral network analysis to lead to valuable new deposits.

Dr. Morrison also hopes to use network analysis to reveal the geologic history of other planets. She is a member of the NASA Mars Curiosity Rover team identifying Martian minerals through X-ray diffraction data sent back to Earth. By applying these tools to analyze sedimentary environments on Earth, she believes scientists may also start answering similar questions about Mars.

“Minerals provide the basis for all our material wealth,” she notes, “not just precious gold and brilliant gemstones, but in the brick and steel of every home and office, in cars and planes, in bottles and cans, and in every high-tech gadget from laptops to iPhones.”

“Minerals form the soils in which we grow our crops, they provide the gravel with which we pave our roads, and they filter the water we drink.”

“This new tool for understanding minerals represents an important advance in a scientific field of vital interest.”

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