Category Archives: Artificial Intelligence

Artificial Intelligence (AI) to be $100 billion sector by 2025

AI startups received $14 billion investment in 2019

AI, an effective tool for Indian Judiciary System : CII Summit and Expo on AI Application & Digi-Tech

Day two ofConfederation of Indian Industrys (CII)Summit and Expo on AI Application & Digi-Tech,kick started with a thought-provoking panel discussion onAI in Public Service.The session highlighted the benefits of AI interventions in Agriculture, Smart Cities, Healthcare, Skilling, Education, Public Utility Services, Judiciary and Governance.

Mr. Sameer Dhanrajani, CEO, AIQRATEsaid that in India we are seeing a great opportunity for AI to support various processes both in the public and private entities. One of the areas where AI can be most effective is in the countrys judicial system. Currently we have 33 million legal cases pending in India. 84% of which has an average pendency of 13 years. AI can be used to deal with all previous cases that we have in our repository by extrapolating it by means of text-mining, multilayer perceptron (MLP) and deep learning. Leaving the legal system to focus on their core job, which is to solve and close cases on an agile basis.

Globally, AI has seen $45 to $58 billion investment during the last year. It is growing at the fastest pace of any exponential technology. The AI segment will be worth over $100 billion by 2025. This gives ample indication of the scale and opportunities in this sector. According to Mr. Dhanrajani, the companies that have adopted AI will take away $1.2 trillion worth of business from their competitors. In 2019 alone AI startups have received $14 billion investment across 600 funding events.

Realizing the importance of AI currently, 28 nations around the world are curating or drafting AI policies and strategies. India is one among them however where the country lags behind is in research. In India we have only 2000 to 2500 research papers submitted every year and China has 10 times more. Out of 34.8 million students coming out of our higher education system in the country only 18% are employed. The job opportunities in the new age will require skills that are not taught in our educational system and this needs to change.

India is uniquely poised to be a global leader in AI, and this is due to the diversity of our population generating a diverse set of data. Attaining a premier position in AI will require convergence of all stakeholders. Towards this, India need to focus on 3 broad areas i.e.Education infusing new age courses and adapting personalized learning powered by AI,Enable create an open innovation platform, a pipeline of AI centric solutions and their adoption andEthics Draft an operating framework within which AI can be developed, Mr. Dhanrajani elaborated.

The panel discussion highlighted the sectors in India where AI can make the most difference:

Governance AI can power several governance initiatives ranging from security threats, RTI, potential fraud and corruption to improving the legal system, curbing human trafficking and tracking of missing persons.

Ms.AparnaGupta,Analytics&DataScienceLeader,OracleCloudSolutionsHub;MrKapilGandhi,VicePresidentStrategyIntelligentAutomation,GenpactDigital;Ms.PadmashreeShagrithaya,VicePresident&HeadAnalytics,DataScienceandVisualization, Capgemini;MrSanjeevKumar,SrDirectorData&Analytics, BakerHughes;MrSatyamoyChatterjeeExecutiveVicePresident AnalytticaDatalabInc also participated in the panel discussion chaired byMr. Sameer Dhanrajani.

With an objective of identifying and showcasing the best Start-up with the most Innovative scale deployment of Artificial Intelligence & Industrial AI in a large corporate environment CII in association withAccenture Ventures held theCII AI Challenge which felicitated the best startups in each of the segment.

AskSidhas been recognized as the Best Start up for Innovative deployment of Artificial Intelligence in large scale corporate environment.

QualitasTechnologieshas been recognized as the Best Start up for Innovative deployment of Industrial AI in large scale corporate environment.

The summit witnessed a live audience poll for the presentation made by the Start-ups and Orbo.aiwas recognized has Best Start up (Audience poll category ).

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Artificial Intelligence to be $100 billion sector by 2025 - CXOToday.com

Radiology is one of the most essential fields in clinical medicine. Experts in this field are specialists in deciphering and diagnosing disease based on various imaging modalities, ranging from ultrasound, magnetic resonance imaging (MRI), computerized tomography (CT), and x-rays. Studies have shown that the use of radiology in clinical practice has exponentially grown over the years: at the Mayo Clinic, between the years 1999 to 2010, use of CT scans increased by 68%, MRI use increased by 85%, and overall use of imaging modalities for diagnostic purposes increased by 75%, all numbers that have likely continued to rise, and indicate the sheer demand and growth of this robust field.

A unique proposal that has become prominent over the last few years to help alleviate this increased demand is the introduction of artificial intelligence (AI) technology into this field. Simply put, the premise of AI as an addition to the practice of radiology is straightforward, and has been envisioned in two main ways: 1) a system that can be programmed with pre-defined criteria and algorithms by expert radiologists, which can then be applied to new, straightforward clinical situations, or 2) deep learning methods, where the AI system relies on complex machine learning and uses neural-type networks to learn patterns via large volumes of data and previous encounters; this can then be used to interpret even the most complicated and abstract images.

Variety of body scans.

However, while much of the theoretical basis for AI in the practice of radiology is extremely exciting, the reality is that the field has not yet fully embraced it. The most significant issue is that the technology simply isnt ready, as many of the existing systems have not yet been matured to compute and manage larger data sets or work in more general practice and patient settings, and thus, are not able to perform as promised.Other issues exist on the ethical aspects of AI. Given the sheer volume of data required to both train and perfect these systems, as well as the immense data collection that these systems will engage in once fully mainstream, key stakeholders are raising fair concerns and the call for strict ethical standards to be put into place, simultaneous to the technological development of these systems.

Furthermore, the legal and regulatory implications of AI in radiology are numerous and complex. There are significant concerns in the data privacy space, as the hosting of large volumes of patient data for deep learning networks will require increased standards for data protection, cybersecurity, and privacy infrastructure. Additionally, given that AI systems will act as an additional diagnostic tool that must be accounted for in the patient encounter, legal frameworks will be required to fully flush out and navigate where liability falls in the case of misdiagnosis or medical negligence. Will this become an issue for the product manufacturer, or will there be a dynamic sharing of the responsibility by multiple parties? This will depend significantly on the amount of autonomy afforded to these systems.

However, radiologists must remain central to the diagnostic process. While AI systems may be able to detect routine medical problems based on pre-defined criteria, there is significant value provided by a trained radiologist that software simply cannot replace. This includes the clinical correlation of images with the physical state of the patient, qualitative assessments of past images with current images to determine progression of disease, and ultimately the most human aspect of medicine, working with other healthcare teams to make collaborative care decisions.

Using a human brain model to interpret MRI scans.

Indeed, there are significant potential benefits to the mass integration of certain AI systems into the practice of radiology, mainly as a means to augment a physicians workflow, especially given increasing radiology demands in clinical medicine. With some reports citing an expected rise in the use of AI in radiology by nearly 16.5% within the next decade, significant complexities remain unaddressed. However, these issues will ultimately need to be resolved in order to achieve a comprehensively capable and ethically mindful AI infrastructure that can become an integral part of clinical radiology.

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Artificial Intelligence Is Not Ready For The Intricacies Of Radiology - Forbes

The role AI plays in your life is a matter of choice (but only to a certain extent).

It doesnt seem too long ago that artificial intelligence (AI) was mostly the stuff of science fiction. Today it seems to be everywhere: in our home appliances, in our cars, in the workplace, even on our wrists.

To some extent, our use of AI is still a matter of personal choice. But because AI is becoming increasing ubiquitous, we need to make a lot of conscious decisions.

Regardless of the choices we make, we need to stay educated on the evolution of this science. A thoughtful primer on this is Rhonda Scharfs bookAlexa Is Stealing Your Job: The Impact of Artificial Intelligence on Your Future.

My conversation with Rhonda provides some good tips what we should know and what we can do.

Rodger Dean Duncan:AI today is similar to the introduction of the desktop computer three decades ago. Many people resisted computers and got left behind. Whats the best argument for AI today?

Rhonda Scharf

Rhonda Scharf:Artificial Intelligence is not going away. When the desktop computer was introduced in the 1980s, many people felt it was a fad, and it would disappear over time.

Hazel, a woman I worked with, was willing to bet her career on it.When the company I worked at insisted we transition to desktops or leave the company, she rolled the dice and called their bluff. She lost. She believed there was no way a company could exist without tried-and-true manual systems and that computers were a big waste of time and money.

We are in precisely that situation again.

If you can write instructions for a task so that someone can follow them, then AI can replicate those actions.

Duncan:So whats the implication?

Scharf:Not only can your company exist without you performing these tasks, it will also (eventually) be more profitable (with fewer errors) because of it.

By refusing to learn about AIand by refusing to adapt and be flexibleyoure rolling the dice that AI will not take over the tasks you currently do. Call yourself Hazel, and youll soon be out of a job.

AI is alive and well in the workplace, only many people dont realize it. Being nave and refusing to acknowledge what is right under your nose is a recipe for disaster. Take a look around at how much AI we already have in our lives. Artificial Intelligence is not going away. Adapt or become unemployed.

Duncan:Most people have grown comfortable with the idea of letting machines replace humans to do monotonous, heavy, repetitive, and dangerous tasks. But the notion of having AI make decisions and predictions about the future often evokes skepticism or even fear. What do you say to people who have such concerns?

Scharf:Movies like2001: A Space Odyessyand its AI character, HAL 9000, have planted the seeds of fear and mass destruction in our minds. We are afraid of what computers can do on their own. AI learns from its experiences and will make decisions on its owncalculated, logical, and statistically accurate decisions.

What AI doesnt do is make emotional decisions. Take AI stock trading as an example. Without any emotions involved, the robo-advisers can determine the optimal price to buy and sell specific stocks. They dont get emotionally tied into one more day and potentially lose profits. AI can evaluate millions of data points and make conclusions instantly that neither humans nor computers can do. As quickly as the market changes, AI changes its course of action based on the data.

Im not about to have AI make life-or-death decisions for me. The same way we now trust machines to handle monotonous, heavy, repetitive, and dangerous tasks, I will rely on AI to do some heavy thinking and bring me logical conclusions, quickly and efficiently.

If you don't want to be left behind, you'd better get educated on AI.

Duncan:What do you tell people who have privacy concerns about AI applications?

Scharf:The privacy concerns are real, but you gave up your privacy when you got your first mobile phone (for some this was as early as 1996). It could track you. Technically, that impacted your privacy 20-plus years ago.

Once the Blackberry was introduced in 1999, followed by the iPhone eight years later, your privacy became severely compromised. Your phone knows where you are, and it knows what youre doing. Even if you keep your Bluetooth off, your device and its apps know a lot about you.

If you wear any technology whatsoever, you are giving up your privacy. According to a 2014 study by GlobalWebIndex, 71% of people ages 16 to 24 want wearable tech. That was over five years ago before we had much wearable technology.

In the same study, 64% of internet users aged 16 to 64 said theyve either already used a piece of wearable tech or were keen to do so in the future.

Fast forward five years, and half of Americans use fitness trackers daily. More than 96% of Americans have a cell phone of some kind.

People may say they have privacy concerns, but when it comes to using technology that improves our lives, we forgo privacy for convenience.

Next: Artificial Intelligence, Privacy, And The Choices You Must Make

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What Role Will (Or Does) Artificial Intelligence Play In Your Life? - Forbes

Artificial intelligence is all the rage, and theres good money to be made in an industry thats still largely emerging from its infancy. But, the problems that AI solves are not easy, and to work in the AI industry you will need a strong and focused set of skills.

Heres the good news: We live in a society where a shocking number of people would rather have a robot boss than a human one. We would rather be led by machines.

This means that most of us are accepting of the idea of artificial intelligence, or AI.

In many sectors, machines have already taken over monotonous jobs. Manufacturing is a prime example. Auto and aerospace manufacturers use machines heavily in their assembly lines. In fact, machines completely transformed the way that our cars are built.

Artificial intelligence isnt just a fad. Its here to stay.

And, that means the industry will need a skilled workforce to build, test and deploy more and more artificial brains around the world. Get in early and youll stand to make a lot of money.

Not to mention help change the world.

If you are interested in a career in artificial intelligence, then youre in the right place.

Artificial intelligence attempts to mimic (and surpass) the power of the human brain using nothing but machines. Machine learning is another common term in AI.

The primary goals of artificial intelligence are:

Artificial intelligence attempts to build machines that think and reason rather than operate in a relatively confined space with pre-built routines, procedures and outcomes. Smart AI systems recognize patterns and remember past events and learn from them, making each subsequent decision smarter, logical and more organic.

AI is a giant paradigm shift in modern computing and requires a deeply scientific and logical approach to design computer systems that think and learn. In other words, build robots that arent just robots.

And believe it or not, AI capabilities are all over the place.

A few examples of artificial intelligence systems include speech recognition (available on many cell phones and smart home devices), email spam blockers, plagiarism checkers, language translation services (like Google Translate) and the auto-pilot system on airplanes.

Companies like Google, Microsoft, Apple, Amazon, Facebook, Accenture, Boeing and so many others are hiring for artificial intelligence roles. AI salaries are typically higher than average because good AI talent can be hard to find.

Artificial intelligence is everywhere in society, and the industry is growing rapidly in 2020. Here is exactly what you need to know to pursue a career in AI.

Artificial intelligence is highly scientific. After all, mimicking the human brain using machines is a very tough problem to solve, much less master. The skills that you will need to pursue AI as a career are varied, but all of them require a great deal of education, training and focus.

That said, there is a wide variety of career types available in AI and machine learning, and they range from higher-level research to low-level programming and implementation.

For example, researchers use their breadth of knowledge in theory and study to reveal new types of systems and capabilities. Researchers hypothesize new or different ways for machines to think and test their research for real-world feasibility.

Algorithm developers take AI research and transform that research into repeatable processes through mathematical formulas that can be implemented using hardware and software.

Software developers and computer scientists use those algorithms to write sophisticated pieces of software that analyze, interpret and make decisions.

Hardware technicians build pieces of equipment (like robots) to interact with the world. Robots use its internal software to move and operate.

Most careers in artificial intelligence require coursework and experience in a variety of math and science-related topics like:

Want a career in AI? Then read. A lot.

Read papers and case studies. Experiment with technologies like Map-Reduce, PHP, MySQL, Postgres and Big Data, especially if you are targeting a computer science-related career in AI. Expose yourself to as many technologies as you can.

Pro tip: Browse through AI job opportunities. Read the job descriptions and especially the requirements to get a feel for specific qualifications that you need for that job.

For example, some might need experience in low-level programming languages like Python or MatLab. Others, especially in the healthcare industry, need expertise in data services like Spark and Blockchain.

Regardless of the type of job that youre after in artificial intelligence, there is no better way to figure out the exact skills you need than to read job requisitions and stay as up-to-date in the industry as possible.

Use the Job Search tool here on The Ladders to find AI and machine learning jobs.

Though the types of careers in the AI industry are varied, most professionals in AI possess five key skills and capabilities, regardless of their individual roles.

Most AI professionals:

Are highly critical thinkers. They take nothing at face value and are naturally curious. They believe in trial and error and must test and experiment before making a concrete decision.

Like to push the envelope. AI is all about pushing the boundaries. Pegging the capabilities of hardware and software to their max, always looking for more. More ways to improve existing systems. More ideas for inventing new ways to live.

Live naturally-curious lives. Always wanting to know more, artificial intelligence pros want to know how things work. They dont just look. They observe. They dont hear. They listen.

Dont get easily overwhelmed. They understand that artificial intelligence is highly technical, but also realize that venturing into uncharted waters is difficult and mysterious. They enjoy the process rather than getting frustrated by it.

Love math and science. AI is highly technical and its a natural good fit for those who are gifted and interested in hard sciences and mathematics.

Artificial intelligence is not just about replacing the human component of the industry. Its also about making it easier to make decisions based on observable patterns, use logic and reasoning to form conclusions and build pathways to boost efficiency and production.

It is not an easy discipline, but thats also why salaries in the AI industry are much higher than average. It takes the right type of person with the right skill set to excel.

Are you the type of person whos right for a career in AI? If you have many of these skill sets, then you just might be.

Continued here:

These are the exact skills you need to get a job in artificial intelligence - Ladders

SAN FRANCISCO, Feb. 5, 2020 /PRNewswire/ -- The global artificial intelligence marketsize is expected to reach USD 390.9 billion by 2025, according to a new report by Grand View Research, Inc. The market is anticipated to expand at a CAGR of 46.2% from 2019 to 2025. Artificial Intelligence (AI) is considered to be a revolutionary technological development and its integration across a host of applications is one of the key factors driving this market. Advances in image and voice recognition are driving the growth of the regional market. Improved image recognition technology is critical in enhanced drones, self-driving cars, and robotics.

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Read 100 page research report with ToC on "Artificial Intelligence Market Size, Share & Trends Analysis Report By Solution, By Technology (Deep Learning, Machine Learning), By End Use (Advertising & Media, Law, Healthcare), And Segment Forecasts, 2019 - 2025" at: https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-market

The two major factors fueling market growth are emerging Artificial Intelligence technologies and growth in big data espousal. Rising prominence of Artificial Intelligence is enabling new players to venture into the market by offering niche application-specific solutions. Furthermore, companies are engaging in industry consolidations in a bid to gain competitive advantages. For instance, in January 2017, Microsoft Corporation acquired Maluuba in order to advance in the deep learning and AI landscape. Existing solution providers are innovating their product portfolio to include both hardware and software solutions.

North America held the dominant share in the global AI market in 2018 thanks to the availability of high government funding, presence of leading players, and strong technical base. Asia Pacific, however, is anticipated to overtake North America to emerge as the leading regional market by 2025, registering the highest CAGR. This can be attributed to rapid improvements in information storage capacity, high computing power, and parallel processing, all of which have contributed to the swift uptake of Artificial Intelligence technology in end-use industries such as automotive and healthcare.

AI has the potential to reduce the burden on clinicians and provide an efficient tool to workforces for accomplishing their tasks in a better way. For instance, AI voice-enabled symptom checkers can better access a situation and assist patients to the emergency department when immediate treatment is required. Artificial Intelligence is expected to resolve around 20% of unmet healthcare demands.

Grand View Research has segmented the global Artificial Intelligence market based on solution, technology, end use, and region:

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About Grand View Research

Grand View Research, U.S.-based market research and consulting company, provides syndicated as well as customized research reports and consulting services. Registered in California and headquartered in San Francisco, the company comprises over 425 analysts and consultants, adding more than 1200 market research reports to its vast database each year. These reports offer in-depth analysis on 46 industries across 25 major countries worldwide. With the help of an interactive market intelligence platform, Grand View Research helps Fortune 500 companies and renowned academic institutes understand the global and regional business environment and gauge the opportunities that lie ahead.

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Artificial Intelligence Market Size Worth $390.9 Billion by 2025: Grand View Research, Inc. - Yahoo Finance

For Immediate Release: February 07, 2020

Today, the U.S. Food and Drug Administration authorized marketing of software to assist medical professionals in the acquisition of cardiac ultrasound, or echocardiography, images. The software, called Caption Guidance, is an accessory to compatible diagnostic ultrasound systems and uses artificial intelligence to help the user capture images of a patients heart that are of acceptable diagnostic quality.

The Caption Guidance software is indicated for use in ultrasound examination of the heart, known as two-dimensional transthoracic echocardiography (2D-TTE), for adult patients, specifically in the acquisition of standard views of the heart from different angles. These views are typically used in the diagnosis of various cardiac conditions.

Echocardiograms are one of the most widely-used diagnostic tools in the diagnosis and treatment of heart disease, said Robert Ochs, Ph.D., deputy director of the Office of In Vitro Diagnostics and Radiological Health in the FDAs Center for Devices and Radiological Health. Todays marketing authorization enables medical professionals who may not be experts in ultrasonography, such as a registered nurse in a family care clinic or others, to use this tool. This is especially important because it demonstrates the potential for artificial intelligence and machine learning technologies to increase access to safe and effective cardiac diagnostics that can be life-saving for patients.

According to the Centers for Disease Control and Prevention, heart disease is the leading cause of death in the United States, killing one out of every four people, or approximately 647,000 Americans each year. The term heart disease refers to several types of heart conditions. The most common type is coronary artery disease, which can cause heart attack. Other kinds of heart disease may involve the valves in the heart, or the heart may not pump well and cause heart failure.

Cardiac diagnostic tests are necessary to identify heart conditions. Among them are electrocardiograms (more widely known as an EKG or ECG), Holter monitors and cardiac ultrasound examinations. The software authorized today is the first software authorized to guide users through cardiac ultrasound image acquisition. The Caption Guidance software was developed using machine learning to train the software to differentiate between acceptable and unacceptable image quality. This knowledge formed the basis of an interactive AI user interface that provides prescriptive guidance to users on how to maneuver the ultrasound probe to acquire standard echocardiographic images and video clips of diagnostic quality. The AI interface provides real-time feedback on potential image quality, can auto-capture video clips, and automatically saves the best video clip acquired from a particular view. Importantly, the cardiologist still reviews the images for a final assessment of the images and videos for patient evaluation.

The Caption Guidance software currently can be used with a specific FDA-cleared diagnostic ultrasound system produced by Teratech Corporation, with the potential to be used with other ultrasound imaging systems that have technical specifications consistent with the range of ultrasound systems used as part of the development and testing.

In its review of this device application, the FDA evaluated data from two independent studies. In one study, 50 trained sonographers scanned patients, with and without the assistance of the Caption Guidance software. The sonographers were able to capture comparable diagnostic quality images in both settings. The other study involved training eight registered nurses who are not experts in sonography to use the Caption Guidance software and asking them to capture standard echocardiography images, followed by five cardiologists assessing the quality of the images acquired. The results showed that the Caption Guidance software enabled the registered nurses to acquire echocardiography images and videos of diagnostic quality.

The FDA is dedicated to ensuring medical device regulation keeps pace with technological advancements, such as todays marketing authorization. This February, the FDA is hosting a public workshop titled Evolving Role of Artificial Intelligence (AI) in Radiological Imaging and seeks to discuss emerging applications of AI in radiological imaging, including AI devices intended to automate the diagnostic radiology workflow, as well as guided image acquisition. Discussions will also focus on best practices for the validation of AI-automated radiological imaging software and image acquisition devices, which is critical to assess safety and effectiveness.

The FDA reviewed the device through the De Novo premarket review pathway, a regulatory pathway for low- to moderate-risk devices of a new type. Along with this authorization, the FDA is establishing special controls for devices of this type, including requirements related to labeling and performance testing. When met, the special controls, along with general controls, provide reasonable assurance of safety and effectiveness for devices of this type. This action creates a new regulatory classification, which means that subsequent devices of the same type with the same intended use may go through FDAs 510(k) premarket process, whereby devices can obtain marketing authorization by demonstrating substantial equivalence to a predicate device.

The FDA granted marketing authorization of the Caption Guidance software to Caption Health Inc.

The FDA, an agency within the U.S. Department of Health and Human Services, protects the public health by assuring the safety, effectiveness, and security of human and veterinary drugs, vaccines and other biological products for human use, and medical devices. The agency also is responsible for the safety and security of our nations food supply, cosmetics, dietary supplements, products that give off electronic radiation, and for regulating tobacco products.

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FDA Authorizes Marketing of First Cardiac Ultrasound Software That Uses Artificial Intelligence to Guide User - FDA.gov

The "Artificial Intelligence (AI) in the Global Freight Transportation Industry, Forecast to 2025" report has been added to ResearchAndMarkets.com's offering.

This study analyses the key trends and applications of artificial intelligence in the freight transportation industry by mode of transport i.e. road, rail, air, and ocean freight transportation. This research also analyses the disruptive impact of artificial intelligence on freight transportation business operations and discusses its adoption prospects until 2025.

Market Insights

With increased trade flow, the fleet population in freight transportation has become denser, and expectations of customers have evolved beyond recognition, resulting in complex transport operations, requiring operational flexibility from freight operators. Human errors in operations, underutilized assets, low workforce productivity, inefficient operational planning, inability to match supply with demand, and trimmed profit margins are key prevailing concerns with freight operators.

The emergence of digital technologies and the rapid technological advancements in digitization have transformed the business and operational landscape of the global freight transportation industry. It is essential for freight operators to embrace such operational complexity and evolve by adopting technologies to turn complexity into an advantage.

Today, the world is connected more than ever, and the growth of data generation has been exponential with smart devices and process automation. Data-driven insights help freight operators move forward and gain a competitive advantage over their peers. Artificial intelligence enables freight operators to harness data more effectively for actionable insights.

Artificial intelligence-powered systems in conjunction with other digital technologies such as internet of things and big data analytics utilize data to its full potential to anticipate events for freight operators, aiding them to avoid risks and create innovative solutions. Machine learning algorithms based on neural networks powered by artificial intelligence would unlock multiple benefits for companies operating in the freight transportation industry.

AI brings changes to the supply chain with autonomous vehicles, helping fleet operators reduce operating cost with and fuel consumption and plan optimized routes for service. The freight operators that are enhancing their capabilities with artificial intelligence are reaping its benefits by increasing efficiency with predictive intelligence. Artificial intelligence also enriches the relationship between the shipper and carrier with personalized service offerings.

Advanced sensor fusion with artificial intelligence supports the integration of smart infrastructure and operating assets and the freight operators in the development of connected freight ecosystem, aiding autonomous fleet management. The transformation of the logistics industry due to artificial intelligence is imperative in the near future; however, the readiness and openness of freight operators for an AI-based data-driven environment will determine how well this industry copes with challenges.

Key Topics Covered:

1. Executive Summary

2. Research Scope and Methodology

3. AI in Logistics Industry

4. AI in Freight Forwarding

5. AI in Freight Transportation

6. Stature of AI Adoption in Freight Transportation

7. Growth Opportunities and Companies to Action

8. The Last Word

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/nusb51

View source version on businesswire.com: https://www.businesswire.com/news/home/20200207005450/en/

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ResearchAndMarkets.comLaura Wood, Senior Press Managerpress@researchandmarkets.com For E.S.T Office Hours Call 1-917-300-0470For U.S./CAN Toll Free Call 1-800-526-8630For GMT Office Hours Call +353-1-416-8900

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Global Forecast on Artificial Intelligence (AI) in the Freight Transportation Industry (2020 to 2025) - Disruptive Impact of AI on Freight...

We might still be decades away from the superhuman artificial intelligence (AI), like sentient HAL 9000 from 2001: A Space Odyssey, but our fear of robots having a mind of their own and acting at their own (free) will and using it against humankind is nonetheless present. Even some of the greatest minds of our time, such as Elon Musk and Stephen Hawking have been talking about this possibility.

On a more down-to-earth and practical level, artificial intelligence has already sneaked into our lives. Weve grown so accustomed to some of the best AI apps,such as Cortana, Alexa or Siri, that we already think of them as our trusted companions that help us run our everyday tasks easily and smoothly.

However, while a catastrophic sci-fi movie scenario is not a thing we should be worried about (at least not at the moment) there are some risks related to AI implementation which are far more tangible and possible.

Read on to find out more about some real-life benefits and risks of AI implementation.

By now, all of the industries have opened their doors to the various advancements AI brings. Here are some of the most prominent usages were witnessing and will be seeing more of in the years to come, in the digital marketing, healthcare, and finance industry.

If youve recently used a chat to reach customer service, chances are high youve been talking to a chatbot, maybe even without realizing this fact. It may come as a surprise that 40% of customers are fine with both options, as long as they get their issues solved.

Chatbots embody many benefits AI brings to businesses, and are a great example of how it may improve a sensitive and time-consuming matter such as customer service.

Some of the crucial points where you can see the advantages of AI-powered chatbots are:

Besides chatbots, AI can benefit digital marketing in many different ways, as it can be used to automate many different tasks, such as email and paid ads campaigns. It can also help marketers create more precise buyer personas, predict customers behavior and give sales forecasts, help with content creation, etc. These benefits to the e-commerce industry can hardly be measured, as businesses can now always be there for their online customers, assisting them in making their purchasing decisions and helping them navigate their customer journey.

Another noticeable way AI benefits our lives is through its usage in healthcare.

Weve recently witnessed a win of trained AI over human experts, as AI outperformed six radiologists in reading mammograms and recognizing breast cancer. Images can now be analyzed in a few seconds by the computer algorithm, so the use of AI can significantly improve the speed of diagnosis.

Except in radiology, AI is widely used in digital consultations, on platforms such as Buoy or Isabel symptom checkers, offering remote medical assistance, and suggesting how to see a professional based on their location.

The advantages of AI have been recognized early by the finance and banking sectors, and the technology is now implemented in the ways beneficial for both parties.

One of the best examples of how beneficial AI in this industry can be, is Erica, a virtual employee of the National Bank of America. Erica has by now served over 7 million customers and managed over 50 million of their requests, helping them with their transactions and budgeting, tracking their spending habits and giving useful advice.

As for the potential actual risks of AI nowadays, the one that seems to bring the most concerns is job loss, which in some industries seem inevitable.

AI-powered employees have quite a few advantages when compared to their human colleagues. As they have no personal and emotional responses theyre never exhausted, bored or distracted, not to mention that they are more productive and efficient. Furthermore, their capacity to make errors is significantly reduced.

Such qualities of AI are the most likely to cause layoffs where a lot of tasks can be automated, such as the trucking, food service and retail industry, leading to millions of unemployed and an even higher income inequality.

Another rising concern has been an invasion of privacy. This has already taken place in China, where AI-powered technologies are used for the purposes of mass surveillance, impacting the so-called social credit system.

The system tracks users behavior everywhere it has access to their social media profiles, their financial reports, health records etc. Data collected this way, including jaywalking and failing to correctly sort personal waste can now negatively influence the credit score while donating blood or volunteering can increase it. Negative credit can, for example, ban you from buying plane tickets, or enrolling your kids in certain schools.Finally, the possibility of using AI capacities for military purposes shouldnt be neglected, as the idea of having this kind of power concentrated in the hands of any of the world leaders, seems like a genuine threat to the world as we know it.

And while we think about all the benefits and the risks artificial intelligence brings, lets not forget one crucial point AI doesnt set its own goals. The power it has is the power we delegate it to achieve the things we are trying to accomplish, meaning that were responsible for both its benefits and its risks.

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Benefits and Risks of Artificial Intelligence - TechSpective

Graham Allison alerts us to artificial intelligence being the epicenter of todays superpower arms race.

Drawing heavily on Kai-Fu Lees basic thesis, Allison draws the battlelines: the United States vs. China, across the domains of human talent, big data, and government commitment.

Allison further points to the absence of controls, or even dialogue, on what AI means for strategic stability. With implied resignation, his article acknowledges the smashing of Pandoras Box, noting many AI advancements occur in the private sector beyond government scrutiny or control.

However, unlike the chilling and destructive promise of nuclear weapons, the threat posed by AI in popular imagination is amorphous, restricted to economic dislocation or sci-fi depictions of robotic apocalypse.

Absent from Allisons call to action is explaining the so what?why does the future hinge on AI dominance? After all, the few examples (mass surveillance, pilot HUDs, autonomous weapons) Allison does provide reference continued enhancements to the status quoincremental change, not paradigm shift.

As Allison notes, President Xi Jinping awoke to the power of AI after AlphaGo defeated the worlds number one Go human player, Lee Sedol. But why? What did Xi see in this computation that persuaded him to make AI the centerpiece of Chinese national endeavor?

The answer: AIs superhuman capacity to think.

To explain, lets begin with what I am not talking about. I do not mean so-called general AIthe broad-spectrum intelligence with self-directed goals acting independent of, or in spite of, preferences of human creators.

Eminent figures such as Elon Musk and Sam Harris warn of the coming of general AI. In particular, the so-called singularity, wherein AI evolves the ability to rewrite its own code. According to Musk and Harris, this will precipitate an exponential explosion in that AIs capability, realizing 10,000 IQ and beyond in a matter of mere hours. At such time, they argue, AI will become to us what we are to ants, with similar levels of regard.

I concur with Sam and Elon that the advent of artificial general superintelligence is highly probable, but this still requires transformative technological breakthroughs the circumstances for which are hard to predict. Accordingly, whether general AI is realized 30 or 200 years from now remains unknown, as is the nature of the intelligence created; such as if it is conscious or instinctual, innocent or a weapon.

When I discuss the AI arms race I mean the continued refinement of existing technology. Artificial intelligence that, while being a true intelligence in the sense of having the ability to self-learn, it has a single programmed goal constrained within a narrow set of rules and parameters (such as a game).

To demonstrate what President Xi saw in AI winning a strategy game, and why the global balance of power hinges on it, we need to talk briefly about games.

Artificial Intelligence and Games

There are two types of strategy games: games of complete information and games of incomplete information. A game of complete information is one in which every player can see all of the parameters and options of every other player.

Tic-Tac-Toe is a game of complete information. An average adult can solve this game with less than thirty minutes of practice. That is, adopt a strategy that no matter what your opponent does, you can correctly counter it to obtain a draw. If your opponent deviates from that same strategy, you can exploit them and win.

Conversely, a basic game of uncertainty is Rock, Scissors, Paper. Upon learning the rules, all players immediately know the optimal strategy. If your opponent throws Rock, you want to throw Paper. If they throw Paper, you want to throw Scissors, and so on.

Unfortunately, you do not know ahead of time what your opponent is going to do. Being aware of this, what is the correct strategy?

The unexploitable strategy is to throw Rock 33 percent of the time, Scissors 33 percent of the time, and Paper 33 percent of the time, each option being chosen randomly to avoid observable patterns or bias.

This unexploitable strategy means that, no matter what approach your opponent adopts, they won't be able to gain an edge against you.

But lets imagine your opponent throws Rock 100 percent of the time. How does your randomized strategy stack up? 33 percent of the time you'll tie (Rock), 33 percent of the time you'll win (Paper), and 33 percent of the time you'll lose (Scissors)the total expected value of your strategy against theirs is 0.

Is this your optimal strategy? No. If your opponent is throwing Rock 100 percent of the time, you should be exploiting your opponent by throwing Paper.

Naturally, if your opponent is paying attention they, in turn, will adjust to start throwing Scissors. You and your opponent then go through a series of exploits and counter-exploits until you both gradually drift toward an unexploitable equilibrium.

With me so far? Good. Let's talk about computing and games.

As stated, nearly any human can solve Tic-Tac-Toe, and computers solved checkers many years ago. However more complex games such as Chess, Go, and No-limit Texas Holdem poker have not been solved.

Despite all being mind-bogglingly complex, of the three chess is simplest. In 1997, reigning world champion Garry Kasparov was soundly beaten by the supercomputer Deep Blue. Today, anyone reading this has access to a chess computer on their phone that could trounce any human player.

Meanwhile, the eastern game of Go eluded programmers. Go has many orders of magnitude more combinations than chess. Until recently, humans beat computers by being far more efficient in selecting moveswe don't spend our time trying to calculate every possible option twenty-five moves deep. Instead, we intuitively narrow our decisionmaking to a few good choices and assess those.

Moreover, unlike traditional computers, people are able to think in non-linear abstraction. Humans can, for example, imagine a future state during the late stages of the game beyond which a computer could possibly calculate. We are not constrained by a forward-looking linear progression. Humans can wonderfully imagine a future endpoint, and work backwards from there to formulate a plan.

Many previously believed that this combination of factorsnear-infinite combinations and the human ability to think abstractlymeant that go would forever remain beyond the reach of the computer.

Then in 2016 something unprecedented happened. The AI system, AlphaGo, defeated the reigning world champion go player Lee Sedol 4-1.

But that was nothing: two years later, a new AI system, AlphaZero, was pitched against AlphaGo.

Unlike its predecessor which contained significant databases of go theory, all AlphaZero knew was the rules, from which it played itself continuously over forty days.

After this period of self-learning, AlphaZero annihilated AlphaGo, not 4-1, but 100-0.

In forty days AlphaZero had superseded 2,500 years of total human accumulated knowledge and even invented a range of strategies that had never been discovered before in history.

Meanwhile, chess computers are now a whole new frontier of competition, with programmers pitting their systems against one another to win digital titles. At the time of writing the world's best chess engine is a program known as Stockfish, able to smash any human Grandmaster easily. In December 2017 Stockfish was pitted against AlphaZero.

Again, AlphaZero only knew the rules. AlphaZero taught itself to play chess over a period of nine hours. The result over 100 games? AlphaZero twenty-eight wins, zero losses, seventy-two draws.

Not only can artificial intelligence crush human players, it also obliterates the best computer programs that humans can design.

Artificial Intelligence and Abstraction

Most chess computers play a purely mathematical strategy in a game yet to be solved. They are raw calculators and look like it too. AlphaZero, at least in style, appears to play every bit like a human. It makes long-term positional plays as if it can visualize the board; spectacular piece sacrifices that no computer could ever possibly pull off, and exploitative exchanges that would make a computer, if it were able, cringe with complexity. In short, AlphaZero is a genuine intelligence. Not self-aware, and constrained by a sandboxed reality, but real.

Despite differences in complexity there is one limitation that chess and go both share they're games of complete information.

Enter No-limit Texas Holdem (hereon, Poker). This is the ultimate game of uncertainty and incomplete information. In poker, you know what your hole cards are, the stack sizes for each player, and the community cards that have so far come out on the board. However, you don't know your opponent's cards, whether they will bet or raise or how much, or what cards are coming out on later streets of betting.

Poker is arguably the most complex game in the world, combining mathematics, strategy, timing, psychology, and luck. Unlike Chess or Go, Pokers possibilities are truly infinite and across multiple players simultaneously. The idea that a computer could beat top Poker professionals seems risible.

Except that it has already happened. In 2017, the AI system Libratus comprehensively beat the best Head's-up (two-player) poker players in the world.

And now, just months ago, another AI system Pluribus achieved the unthinkableit crushed super high stakes poker games against multiple top professionals simultaneously, doing so at a win-rate of five big blinds per hour. For perspective, the difference in skill level between the best English Premier League soccer team and the worst would not be that much.

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Explained: The Artificial Intelligence Race is an Arms Race - The National Interest Online

An artificial intelligence tool has been developed to help predict the structure of the universe and aid research into the mysteries of dark energy and dark matter.

Researchers in Japan used two of the world's fastest astrophysical simulation supercomputers, known as ATERUI and ATERUI II, to create an aptly-named "Dark Emulator" tool, which is able to ingest vast quantities of data and produce analysis of the universe in seconds.

The AI could play a role in studying the nature of dark energy, which seems to make up a large amount of the universe but remains an enigma.

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When observed from a distance, the team noted how the universe appears to consist of clusters of galaxies and massive voids that appear to be empty.

But as noted by NASA, leading models of the universe indicate it is made of entities that cannot be seen. Dark matter is suspected of helping to hold galaxy clusters in place gravitationally, while dark energy is believed to play a role in how the universe is expanding.

According to the researchers responsible for Dark Emulator, the AI tool is able to study possibilities about the "origin of cosmic structures" and how dark matter distribution may have changed over time, using data from some of the top observational surveys conducted about space.

"We built an extraordinarily large database using a supercomputer, which took us three years to finish, but now we can recreate it on a laptop in a matter of seconds," said Associate Prof. Takahiro Nishimichi, of the Yukawa Institute for Theoretical Physics.

"Using this result, I hope we can work our way towards uncovering the greatest mystery of modern physics, which is to uncover what dark energy is. I also think this method we've developed will be useful in other fields such as natural sciences or social sciences."

Nishimichi added: "I feel like there is great potential in data science."

The teams, which included experts from the Kavli Institute for the Physics and Mathematics of the Universe and the National Astronomical Observatory of Japan, said in a media release this week that Dark Emulator had already shown promising results during extensive tests.

In seconds, the tool predicted some of effects and patterns found in previous research projects, including the Hyper Suprime-Cam Survey and Sloan Digital Sky Survey. The emulator "learns" from huge quantities of data and "guesses outcomes for new sets of characteristics."

As with all AI tools, data is key. The scientists said the supercomputers have essentially created "hundreds of virtual universes" to play with, and Dark Emulator predicts the outcome of new characteristics based on data, without having to start new simulations every time.

Running simulations through a supercomputer without the AI would take days, researchers noted. Details of the initial study were published in The Astrophysical Journal last October. The team said they hope to input data from upcoming space surveys throughout the next decade.

While work on this one study remains ongoing, there is little argument within the scientific community that understanding dark energy remains a key objective.

"Determining the nature of dark energy [and] its possible history over cosmic time is perhaps the most important quest of astronomy for the next decade and lies at the intersection of cosmology, astrophysics, and fundamental physics," NASA says in a fact-sheet on its website.

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AI Tool Created to Study the Universe, Unlock the Mysteries of Dark Energy - Newsweek