Today, it seems like everything in our lives has gone digital.Let's look at what WIT affiliate expert Scott Steinberg feelsis propelling technological change forward in the world ofartificial intelligence (AI).

Today, it seems like everything in our lives has gone digital;the pandemic pause created a need for innovations to support theshift and ignited a wave of innovation unlike any other. Thatpaired with the rise of artificial intelligence (AI) and elevatedmachine learning capabilities are two of the main drivers that WITaffiliate expert and noted technology analyst Scott Steinberg feels are propellingtechnological change forward. During a recent WIT webinar, he explained that"more and more tasks will be outsourced to self-awaretechnology. More and more devices will communicate with one anotherand use it as an opportunity to learn from what they see in theenvironment to make decisions in real-time." As theseactivities are contracted out to increasingly more intelligent AIs,the market will begin pushing for more advanced technologicalstructures to support this integration.

With the development of improved artificial intelligence comeshigher levels of deployment. For example, one of the main ways manyof us currently interact with AI is in the form of chatbots; theseconnections typically occur in online environments and thepersonalities are smart enough to solve human problems with 90-100%accuracy. Going forward, Steinberg sees artificial intelligenceoperating in every environment from factory floors to offices andchemical plants. But he also acknowledges the fact that AI is onlyas capable and fallible as its creators are, and it will be subjectto subconscious bias. To mitigate this, AI needs to be trained withmillions of situational examples as the technology gets smarterwith the more data it can examine.

But no matter how much information you feed it, artificialintelligence is still just like humans; it's never going to beable to account for every situational variable. Training withhistorical data makes the technology predisposed to certainproblems, but going forward, this technology is going to bepowerful enough to create its own AI routines. And because AI canmore rapidly spot patterns and process information faster than thehuman eye, we're only going to outsource more tasks.

Since we are going to be trusting artificial intelligence withmore important tasks, it is imperative to remember that it is stillfundamentally a piece of computer software. Steinberg laments that"After 25 years in the technology business, I have yet to meeta single piece of computer software that didn't containglitches or loopholes and, for that matter, that is only going tobe more subject to things like hackers, thieves, and outsideinfiltration or influence going forward. [This] presents a lot ofpotential challenges. As we move to a digital world, we really cedea lot of control to technology that we might have in the realworld."

With autonomous vehicles slated to become widelyavailable within the next few years, it is important to look at howAI will play a role in propelling this technology forward.Steinberg feels that there is going to be a lot of advancement inthis space as more manufacturers begin implementing AI software;Tesla already has some self-driving capabilities built-in, fleetsof autonomous trucks are hitting the road in droves, and in thenext few months, he sees cities deploying entire networks ofsensors that can speak with vehicles intelligently. These networkswill be built on the back of 5G, allowing the devices to communicate whatobjects are on the road and where- ultimately transforming the carsto function more like computers. He states, "It used to beabout steel but going forward, the vehicle of tomorrow really willbe about silicon."

An increased level of connectivity will create more complexvehicles with AI, real-time sensors, 3D cameras, and more allcommunicating, bringing on its own set of concerns. But moreimportantly, it also creates greater safety and securityproblems.

In fact, in terms of security, Steinberg thinks of the vehiclesutilizing this technology as an extension of your personalcomputer. He sees issues arising with hackers, lockouts,ransomware, and more. What happens if someone locks you out of yourcar or worse, begins altering your trip to send you to anundisclosed location making YOU the ransom? Any computer system, nomatter how powerful, is going to be subject to errors, technicalhiccups, and, of course, outside compromise.

This pushes us to examine the safety of this software; is aself-driving vehicle going to crash less than a human driver would?And how can people ensure that their car will continuecommunicating with other devices on the road? Automakers havealready reported around 400 crashes in a little under a year after TheNational Highway Traffic Safety Administration required the reportto help them assess the risks and trends associated with partiallyautomated driver-assist systems. technology. Steinberg wonders how,if a car is a computer, manufacturers will implement the necessarysoftware updates needed to guarantee that their vehicles willcontinue working in sync with others on the road. This level ofcomplexity will make it more difficult to keep things movingforward in a time where computers think at a much faster rate thanhumans. So how can we begin regulating this activity?

From a legal standpoint, this will raise issues with the parts,pieces, and technologies that go into these vehicles. Who is liablefor the complications associated with these technologies? Who isresponsible for setting standards for AI and vehicles? And lastly,who will be thinking about the way these complex systems interfacewith one another to ensure the safety of drivers, products, andvaluables? Steinberg feels that "technology really kind ofrockets ahead and oftentimes, we have to play catch up. We struggleto think about the potential applications, use cases, and scenariosthat these advancements may present, at least from a legalstandpoint." And with this comes the opportunity for disputeson a multitude of fronts.

It's too early to say how manufacturers can prepare fordeveloping markets as there will be automakers, technologycompanies, software providers, hardware creators, and thegovernment all participating in the creation of them. There arecurrently no major governing laws that are geared to help with theintegration of AI and technology, amplifying the potential forconflict among parties from differing industries. He details that"There's a big "mod" [modifications or upgradesto assets] culture around cars and upgrades that are going toimpact the on-road experience. What's going to happen withresell and the transfer of data that's going to reside in thatcar when you bring it to a new owner? On top of that, you'realso going to have to wonder if you have different states crackingdown in different ways on the way the technology exchangesinformation and what types of data can be traded."

In order to help push regulations forward, Steinberg feels thatwe are going to need more participation in this conversation fromindustry thought leaders; this way, they can work alongside thegovernment to keep up with all of this change. In his opinion,"We need advisory boards, we need experts, we need to get manyvoices at the table. But we really need to be having a lot of theseconversations at the highest levels, a lot more frequently and alot sooner."

Stay tuned for more insights from our conversation with WITaffiliate expert Scott Steinberg. Mr. Steinberg ishailed as one ofthe world's most celebrated futurists and strategic innovationconsultants. He has been featured in hundreds of media outlets fromCNN to TIME toThe Wall St. Journal, with the Fortune 500calling him a "defining figure in business andtechnology" and "top trendsetter to follow."

Next in this series, we'll cover innovations in wireless technologies and the implications ofthese advancements on the market.

Learn more about our top industry and technical experts in automotive technology.

The content of this article is intended to provide a generalguide to the subject matter. Specialist advice should be soughtabout your specific circumstances.

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The Rise And Impacts Of Artificial Intelligence - Rail, Road & Cycling - United States - Mondaq

Firstly, as the main basis for AI development in the Peoples Republic of China, the State has significantly increased its investment in the industry. It pays special attention to long-term financial support for basic research, and strengthens support for the AI industry purposefully and selectively with foundations and benefits.

It was necessary to learn from the experience and lessons relating to the allocation of national scientific research and development funds in the past, to formulate and improve the principles and methods of the rational allocation of funds, as well as take effective and fair measures to solve the problem of the unfair distribution of research funds, and make the best use of the support provided by staff incentives.

Secondly, China has encouraged private capital to invest in the AI industry and entrepreneurship. Inspired by the current booming of the AI sector, much private capital necessarily wants to join the AI industry. Giants and start-ups are collaborating to revitalise the AI market. The Internet companies such as Baidu, Alibaba, and Tencent have already lined up in the AI field and the injection of capital is expected to revitalise the market. According to some surveys, a large number of start-ups are getting involved in the AI field and almost all of them have received investment, with funding far exceeding five billion yuan.

Driven by factors such as national policy support, the demand for applications, technological progress and capital injection, a market window of over one hundred billion is opening. Paying attention to create a good development environment for non-public AI enterprises, providing free and good services in terms of market access, examination and approval, processing and services, etc., as well as mobilising private enterprises enthusiasm and accelerating the development of the non-public economy, have been the foundations of this development.

However, due to the characteristics of the AI sector with broad application prospects, high technological content, long payback period and short technology iteration cycle, many investors bluntly stated that they did not understand when it came to AI technology, meaning that before investing they wanted to better understand what it was all about beyond the echo effect of the phenomenon in order to invest capital wisely.

Besides assessing the technological progress and the prospects for commercial application of the AI field or the AI project invested nationally or abroad, there was also the issue of the staff that had to possess certain professional skills, as the financers experts had to have a long-term investment vision.

Over the years and considering the successes achieved, many credit and investment institutions are now more concerned with the value of short-term investment since long-term investment has long brought economic benefits, visibility and authoritativeness abroad with the hope of generating returns over a three- or five-year period. It has to be said, however, that the projects investing in AI often have a relatively long payback period and further assessment is required to see whether they can generate returns within the expected terms. Investing in AI technology and industries has to be assessed carefully.

While increasing support for IA research and development, the management of funds needed to be strengthened. It was recommended to implement scientific management of the entire process in the project review and implementation process, strengthen peer review, especially the review of funds and the management of the use of funds, eliminate waste and prevent corruption, so that the limited funds could be cut. Technology was thus greatly enhanced.

During the works at the National Committee of the Chinese Peoples Political Consultative Conference, as early as 2015 it was recommended to build one of the largest AI development platforms in the world, in view of the need and feasibility of establishing a national AI development plan.

In the era of the Internet networks, big data and cloud computing, it is unimaginable to develop high-tech and large supercomputing data science and fields such as AI without their own general platform. It is necessary for scientific research institutes, companies and even individual manufacturers to bring various innovations to this platform in a fair and equitable manner. AI technology has now substantial applications: voice recognition, image recognition, multilingual translation, machine learning, intelligent planning, smart control or driverless cars, unmanned aerial vehicles and autonomous underwater vehicles, etc. The basic AI technology starts with the mobile robot and a development platform for intelligent robots is the first step for the further development of big data, cloud computing, smart games, general education, logistics systems, services, transport, smart cities and tourism, expert systems, smart grid (in electrical and telecommunications engineering, a smart grid is the combination of an IT network and an electrical distribution network, which enables the electricity grid to be managed smartly in various aspects or functionalities, i.e. by managing it efficiently for the distribution of electricity and for a more rational use of energy, while minimising overloads and variations in the electrical voltage around the nominal value), etc.

This platform is open to innovation, to the sharing of resources and facilities, and gets strong support from convinced investors.

China already has extremely rich Internet computing and technology resources and, as computing and network resources become ever more plentiful and the cost ever lower, many intellectual functions that could not be simulated by computers are now able to do so. AI is the highest trend of technology in the current world. For the time being, the other great objective the humans journey to Mars is only at the theoretical-experimental stage. China currently has the ability to build an AI platform with global influence. At the same time, we need to realize that there are still great gaps and difficulties in achieving the sharing of resources on national and even global issues such as data storage, and this should not be taken lightly.

AI products have both hardware and software, with software as the core technology. In the past there were not many AI products in China both hardware and software, with software as the core technology and, without a national standard, the impact was minimal. With the fast rise of the AI industry, new products increased exponentially. Such AI acquisitions will certainly be confused and will inevitably mix with a number of fake and lower-quality products, thus disrupting the market. With a view to ensuring the healthy development of the AI sector and protect the consumers legitimate rights and interests, government legislation, as well as quality inspection and market management departments, take precautions and seize the opportunity to formulate or revise standards, through rigorous inspections and staff audits, in order to carefully prevent the entry of unskilled labour.

Only by letting qualified AI products enter the market can the AI high-tech reputation be maintained, which enables the AI industry to create a healthy development and thus promote the industry so that it can truly become the core technology of smart production: a new lever for the transformation and enhancement of the national economic structure, i.e. the engine of a new industrial revolution. (12. continued)

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The Development of Artificial Intelligence in China: Conclusions - Modern Diplomacy

1. A model combining artificial intelligence-enabled analysis of retinal vascular images from a large database with several traditional risk factors performed comparably to Framingham risk scores in predicting stroke and myocardial infarction (MI) risk.

2. Addition of retinal vascular scores to Framingham risk scores did not improve prediction of incident stroke and MI.

Evidence Rating Level: 2 (Good)

Study Rundown: Changes in retinal vasculature, such as tortuosity, arteriolar narrowing, and branching, have been shown to be associated with cardiovascular disease severity. Retinal imaging thus has potential as a noninvasive prognostic tool. This study aimed to develop a predictive model using artificial intelligence (AI)-enabled analysis of fundus photographs then assess the models performance relative to existing risk scores. The AI model was developed using images and outcomes data from about 64,000 patients in the UK Biobank and tested on about 6,000 patients in another database. A model including retinal vessel metrics, age, smoking, and medical history [use of blood pressure and cholesterol medications, diabetes history, past stroke or myocardial infarction (MI)] predicted incident stroke or MI about as well as Framingham risk scores. Adding retinal data to Framingham risk scores did not improve their predictive performance. Patients in both databases had <1% incidence each of stroke, MI, and circulatory death, which limits the applicability of this predictive model to higher-risk populations. The overall performance data here suggests that retinal vascular metrics may perform a similar predictive role to serum lipid levels and blood pressure. Clinical integration of fundus photography in this setting would be challenging, but could one day provide a useful alternative.

Click to read the study in BJO

Relevant Reading: Retinal microvascular signs as screening and prognostic factors for cardiac disease: A systematic review of current evidence

In-Depth [retrospective cohort]: For both the UK Biobank and EPIC-Norfolk databases, retinal vessel analysis was performed on non-dilated 45 color fundus photographs centered on the fovea. The AI analysis system was fully automated and returned average vessel width, total vessel area, tortuosity, and variance of widths across both eyes for each patient. The optimism adjusted C-statistic for circulatory mortality from a model including retinal vasculometry (RV), smoking, and medical history was 0.774 for men and 0.748 for women in the EPIC-Norfolk database, with R2 values of 0.392 and 0.333, respectively. The C-statistics for incident stroke and MI ranged from 0.641-0.714 with R2 from 0.150-0.274. Framingham Risk score C-statistics for stroke and MI for the same population ranged from 0.682-0.732 with R2 from 0.199-0.309. The RV-based model placed 45.5% of men and 49.9% of women from EPIC-Norfolk with incident stroke or MI in the top quintile of risk scores, compared to 45.5% and 50.9% for Framingham risk score.

Image: PD

2022 2 Minute Medicine, Inc. All rights reserved. No works may be reproduced without expressed written consent from 2 Minute Medicine, Inc. Inquire about licensing here. No article should be construed as medical advice and is not intended as such by the authors or by 2 Minute Medicine, Inc.

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Artificial intelligence-aided analysis of retinal imaging may predict cardiovascular mortality - 2 Minute Medicine

AI provides unfair advantages to its users, undermining the spirit of competition.

Editor's note: Abjini Chattopadhyay is a Silver Chips artist

AIArtImage2

Photo: Created by Alexander Liu via Midjourney

Photo: Created by Alexander Liu via Midjourney

Ever since Jason M. Allen won the Colorado State Fairs annual art competition, the internet has exploded into arguments over whether or not AI belongs in art competitions. While some argue that AI should be allowed as a tool for artists to use, AI in art competitions gives its users an unfair advantage over others and should not be allowed.

To understand what makes AI (artificial intelligence) so unfair in competitions, we should first understand how AI art programs work. Most AI art programs feed thousands of images to train neural networks to recognize what certain objects look like. When a user prompts the AI for a dog, it generates images iteratively, comparing each iteration to what it thinks a dog looks like.

As AI teacher Nora Burkhauser puts it, AI artists are pre-trained to generate images based on what theyve seen. It's actually generating them and then putting it through an image recognition thing to say, okay, is this anything close to what we want? Burkhauser explains.

That means once someone prompts the AI on what they want to see, they can sit back and relax as the AI generates an image in mere seconds. Anybody that has ever played around with the multitude of freely available AI art generators can attest to how easy it is to generate breath-taking images at the click of a button.

AIArtImage3

Photo: Created by Alexander Liu via Midjourney

Photo: Created by Alexander Liu via Midjourney

For that reason, art teacher Sara Foraker doesnt think that AI belongs in art competitions as a whole. Its a small little snippet of someones creative thought, but I honestly dont see the value, Foraker says.

Silver Chips artist Abjini Chattopadhyay agrees, saying AI removes the originality from art. I don't think that [AI] should be legal because when making art yourself, you put in your own style and your own thinking into it, but with AI art, youre incorporating the styles of other people and their thoughts and ideas, Chattopadhyay says.

Because making art with AI requires very little effort from the user, complete beginners can create works of art with more advanced techniques and detail than those who have put years of work into learning how to draw. Allowing for the continued use of AI in art competitions undermines the hard work of everyone else participating.

Indeed, art resource teacher Jacqueline Armstead-Thomas says that AI art is more akin to searching for images than making your own artwork. Youre just typing in a phrase and you're getting the results, and so when you think about the actual function of it, it's no different than typing into google an image, and getting results for that image, Armstead-Thomas says.

AIArtImage1

Photo: Created by Alexander Liu via Midjourney

Photo: Created by Alexander Liu via Midjourney

Another issue is the speed of AI generated art. AI programs like Midjourney and Dall-E can generate pieces in under a minute, while it may take an artist hours to render a piece of similar quality. That means anybody not using AI is put at an extreme time disadvantage against those who are, putting them at a massive disadvantage.

The images in this article, despite being quite detailed and beautifully rendered, took perhaps 10 minutes in total to generate. Its absurd to think that AI artists can churn out a portfolio of pieces in about as much time as it takes to register for many competitions, or for a traditional artist to do one simple sketch.

In response, proponents of AI in art competitions point out that AI is just another tool that artists can use, like Photoshop or Procreate. While true, this argument misses the point of what makes AI so unfair in the first place.

AI is fundamentally different from other tools in a digital artists arsenal. Even when using tools like Photoshop, you must manually manipulate and compose your artwork, using your own skills and creativity as you do so. While drawing the piece, you must consider the placement of objects, contrast, lighting and so much more.

Armstead-Thomas says that AI requires less work than using other digital drawing tools. I dont think it's the same skill level of actually having created that piece, whether you did it traditionally or whether you did it digitally, but actually creating every stroke and line and color that shows up, Armstead-Thomas says.

Compare this to using AI, where you need only know the basic themes or objects in an image, and the program takes it from there. Even if that image is subsequently altered by a contestant manually, it is still no different than finding an image online, tweaking it, and calling it your own.

AI in art competitions undermines the hard work of traditional artists, puts them at a massive time disadvantage, and limits overall creativity. Going forward, competitions ought to either make an entirely new category for these works, or ban the use of AI outright.

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Artificial intelligence has no place in art competitions | Silver Chips - Silver Chips Online

Artificial intelligence technology is being used more and more and in many situations it is used to see how people would look with the passing of time or by removing aesthetic touch-ups

This is the case with a TikTok account, run by the Australian streamers Vandahood Live. They posted a video compilation of what the Kardashians would look like naturally on their profile.

Kim Kardashian, Kylie Jenner, Khloe Kardashian, Kris Jenner and Kourtney Kardashian have been the subjects of that now viral TikTok, showing their faces without the surgeries they have been getting over the last few years.

The real video used is from 'Keeping Up with the Kardashians' where you can see their real faces compared to the one generated by artificial intelligence.

The most obvious Kardashian differences are Kylie's thinner lips or Khloe's much thinner nose. In addition, both have admitted in interviews that they have had these surgeries.

"We used three different artificial intelligence software and two different standard graphics software and a full week to get it done," explained Keith, one of the members of Vandahood Live to PetaPixel.

"We had to take a different approach for each family member, as each experienced different changes over the years."

Deep Face Lab, FaceApp and EbSynth were the programs used to recreate the Kardashians.

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Artificial intelligence reveals what the Kardashians would look like without all their cosmetic surgeries - Marca English

Review time shortened from an average of nine days to less than one day

BOSTON, Oct. 12, 2022 /PRNewswire/ --Blue Cross Blue Shield of Massachusetts("Blue Cross") today announced the completion of a proof-of-concept pilot called "FastPass," an automated prior authorization process from end-to-end, eliminating the need for faxes, phone calls and manual processes for payers and providers. The initiative, piloted at New England Baptist Hospital (NEBH), focused on addressing the major problem areas, including reducing the time from submission to decision, alleviating administrative burden, decreasing clinical review time, and increasing clinician satisfaction.

The ProblemPrior Authorization (also known as "Pre-Certification") is a process through which a clinician seeks advanced approval from a health plan to ensure that a service or treatment is covered, medically necessary, and not duplicated. Prior authorizations exist to manage excess health care costs and mitigate patient risk while also helping ensure consumers receive high-quality care. However, prior authorization can be cumbersome for clinicians.

"We realize that the prior authorization process is widely recognized as the single biggest administrative pain point for hospital staff," said Kathy Gardner, RN, vice president of clinical operations at Blue Cross. "We wanted to figure out a way to retain the value of prior authorizations ensuring our members receive treatments that are medically necessary and clinically effective while eliminating the administrative burden on our clinical partners and allowing members to get the care they need sooner."

How it worksBlue Cross engaged Olive, a leading automation and intelligence company bridging the divide in health care, to help streamline both clinician and payer processes and prior authorization decision-making using artificial intelligence (AI).

The technology automated the process of cross-checking Blue Cross' prior authorization requirements in real-time to identify if a prior authorization was required. If a prior authorization was not required, the provider received instant notification that they could proceed with scheduling the procedure. When prior authorizations were required, FastPass used AI to cross-check the clinical history in the electronic medical record against Blue Cross' medical necessity criteria and automatically generate a recommendation in real time, again giving the clinician the ability to proceed with scheduling the procedure. For the remaining prior authorization submissions that required more complex clinical review, FastPass automatically packaged and made available all the clinical documentation and notes to the clinical review team, significantly streamlining and accelerating the reviews.

The ResultsThe pilot at NEBH focused on hip and knee procedures for 32 orthopedic providers over the course of a four-month period. 88% of prior authorization submissions were processed automatically in real-time. The overall impact on prior authorization approval time went from an average of nine days to an average of less than one day. The associated impact on administrative burden and cost has been significant for Blue Cross.

"The FastPass proof-of-concept is just one step in our journey toward automating prior authorizations across BCBSMA to continue to make the process frictionless for our clinical partners and ultimately our members," said Deb Vona, senior director of business operations at Blue Cross.

About Blue Cross Blue Shield ofMassachusettsBlue Cross Blue Shield ofMassachusetts(http://www.bluecrossma.org) is a community-focused, tax-paying, not-for-profit health plan headquartered inBoston. We are committed to the relentless pursuit of quality, affordable and equitable health carewithan unparalleled consumer experience.Consistent with our promise to always put our members first, we are rated among the nation's best health plans for member satisfaction and quality.Connect with us onFacebook,Twitter,YouTube,andLinkedIn.

About OliveOlive delivers automation and intelligence to bridge the divide in healthcare. By addressing the most burdensome operational issues, Olive is reducing costs and increasing capacity for hospitals, health systems and payers, so the focus can remain on delivering the best, most effective care to patients. To learn more about Olive, visit oliveai.com.

SOURCE Blue Cross Blue Shield of Massachusetts

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BLUE CROSS BLUE SHIELD OF MASSACHUSETTS USES ARTIFICIAL INTELLIGENCE TO SPEED REVIEW TIME, AUTOMATE AUTHORIZATIONS & ELIMINATE ADMINISTRATIVE...

The future of the mining industry will be shaped by a range of disruptive themes, with artificial intelligence (AI) one of the themes that will have a significant impact on mining companies.

The mining industry is under more pressure than ever to increase efficiencies. This comes as declining ore grades and more disparate and remote deposits create greater challenges in securing new resources, and rising mining costs drive the need for greater productivity at the mine site. At the same time, there is a strong focus on ensuring safety and sustainability within mines. Artificial intelligence (AI) can address many of these challenges and inefficiencies through several key technologies in the value chain, including computer vision, smart robots, data science, and machine learning.

Exploration costs can be reduced by using AI to identify the most likely locations of mineral deposits. Predictive maintenance can ensure that equipment defects are solved before they become extremely costly and ensure that equipment downtime is kept to a minimum, increasing productivity. Smart sensors and cameras aid automated equipment while also monitoring the safety of workers in mines.

However, not all companies are equal when it comes to their capabilities and investments in the key themes that matter most to their industry. Understanding how companies are positioned and ranked in the most important themes can be a key leading indicator of their future earnings potential and relative competitive position.

According to GlobalDatas thematic research report, Artificial Intelligence (AI) in Mining, leading adopters include: Goldcorp, BHP, Rio Tinto, Freeport-McMoRan, Fortescue Metals Group, Newcrest, Barrick Gold, Dundee Precious Metals

BHP

BHPs Maintenance Centre of Excellence performs ML on vast troves of data collected from its operational equipment. This provides actionable insights for predictive maintenance on items such as haul trucks and improving supply chain management. The company also employs self-driving trucks to reduce accidents caused by fatigued drivers and automated drills. BHP fortified its supply chain during the COVID-19 pandemic using analytics. At its 2019 SmartMine conference, the company demonstrated its use of ML to interpret geological data and generate targets.

The company also currently has the largest fleet of autonomous trucks in operation with 300 spread across ten mines. The company has invested evenly across Komatsu and Caterpillar with a recent investment at South Flank with 42 Komatsu 930E ATs. It has operated a fully-autonomous truck fleet at its Jimblebar mine in Western Australia since 2017 and has cited benefits such as productivity increases of 20%, operating cost reduction of 20% and over 90% reduction in haul accidents due to the automation of trucks.

Rio Tinto

Rio Tinto has been incorporating automation into its operations for more than a decade to improve safety, efficiency, and reduce the cost of operations. Automated trucks, drills, and trains are used to remove driver error, thus improving safety. Rio Tinto is closing the gap on BHP the opening of its Gudai-Darri iron ore mine will add 23 CAT 793F autonomous haul trucks to its total taking it to 210, which would move it into second place ahead of Fortescue Metals Group.

The companys Iron Ore business operates AutoHaul, the worlds first fully autonomous heavy-haul long-distance railway system. AutoHaul transports iron ore to port facilities in the Pilbara region of Western Australia. Around 200 locomotives on more than 1,700km of track have travelled over 7 million km to date. Each 240-wagon hauler is 2.4km long, requiring two to three locomotives to transport 28,000 tonnes of iron ore, an average of 800km over 40 hours. Using this autonomous technology reduces risk at level crossings and auto-responds to speed restrictions and alarms, improving overall safety. By eliminating the need to transport drivers to and from trains mid-journey, almost 1.5 million km of road travel are saved annually. This also removes the need to change drivers two to three times during the journey, saving an hour from each journey and increasing average speeds by between 5 and 6%. AutoHaul can move about one million tons of iron ore a day. Loading and unloading product from the wagons is an entirely automated process.

Fortescue Metals Group

Fortescue has undertaken one of the largest fleet conversions to autonomous haulage projects, with almost 200 autonomous trucks operating at its Solomon and Chichester hubs. The fleet includes Cat 793F, 789D, and Komatsu 930E haul trucks. Since 2013, the fleet has safely travelled over 52 million km and moved 1.5bn tons of material. Some 900 additional assets, such as excavators, wheel loaders, and light vehicles, are integrated with the autonomous fleet using CAT Minestar Command for Hauling Technology. Fortescues autonomous haulage fleet has delivered a 30% increase in productivity. Fortescue plans to use the data collected from the autonomous haulage fleet to understand their operations better and look for ways to optimize, such as haul road design and maintenance scheduling.

Sources

GlobalData, the leading provider of industry intelligence, is the parent company of Mining Technology and provided the underlying data, research, and analysis used to produce this article.

GlobalDatas Thematic Scorecard ranks companies within a sector based on their overall leadership in the 10 themes that matter most to their industry, generating a leading indicator of their future earnings and relative position within key strategic areas.

High-Performance Adhesives and Coatings for Mining Equipment

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Who's leading the way? Top ranked mining companies in the artificial intelligence theme - Mining Technology