Category Archives: Artificial Intelligence
North America Artificial Intelligence in Healthcare Diagnosis Market Developments, Competitive Analysis, Forecasts to 2027 Talking Democrat – Talking…
North America Artificial Intelligence in Healthcare Diagnosis Market
North America Artificial Intelligence in Healthcare Diagnosis Market is a valuable source of insightful data for business strategists. It provides the industry overview with growth analysis and historical & futuristic cost, revenue, demand, and supply data (as applicable). The research analysts provide an elaborate description of the value chain and its distributor analysis. This Market study provides comprehensive data which enhances the understanding, scope, and application of this report.
This North America Artificial Intelligence in Healthcare Diagnosis Market represents a CAGR of 44.3% from 2020 to 2027
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North America Artificial Intelligence in Healthcare Diagnosisincludes market research report Top Companies:General Electric Company, Koninklijke Philips N.V., Aidoc, Arterys Inc., Isometric, IDx Technologies Inc., MaxQ AI Ltd., Caption Health, Inc., Zebra Medical Vision, Inc., Siemens Healthcare Private Limited have their own company profiles, growth phases, and market development opportunities. This report provides the most recent business details associated with business events, import/export scenarios, and market share.
North America Artificial Intelligence in Healthcare Diagnosis Market Split by Product Type and Applications:
This report segments the North America Artificial Intelligence in Healthcare Diagnosis Market on the premise ofTypesis:
Medical Imaging Tool
Automated Detection System
Others
On the premise ofApplication, the North America Artificial Intelligence in Healthcare Diagnosis Market is segmented into:
Eye Care
Oncology
Radiology
Cardiovascular
Others
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Important sections of the TOC:
-Economic Impact Variables on North America Artificial Intelligence in Healthcare Diagnosis Market: Illuminates the consequences of environmental, political, and economic fluctuations, and explains changes in customer and consumer requirements. We also provide a detailed report of North America Artificial Intelligence in Healthcare Diagnosis on the technology risks and advancements in the market.
-Forecasts based on macro-and micro-economy: Ensuring price, revenue, and volume North America Artificial Intelligence in Healthcare Diagnosis forecasts for the market. It also includes, in addition to forecasting growth, revenue, and import volume for the region, with revenue forecasting for the North America Artificial Intelligence in Healthcare Diagnosis application, along with revenue forecasting by cost, revenue, and type.
-Marketing Strategy Analysis: In this section, North America Artificial Intelligence in Healthcare Diagnosis analysis aims at niche positioning and provides information regarding the target audience, new strategies, and pricing strategies. We provide a comprehensive North America Artificial Intelligence in Healthcare Diagnosis marketing station analysis that investigates the problem. Marketing channel development trends, direct marketing as well as indirect marketing.
-Business Intelligence: The North America Artificial Intelligence in Healthcare Diagnosis companies studied in this section are also assessed by key business, gross margin, price, sales, revenue, product category, applications and specifications, North America Artificial Intelligence in Healthcare Diagnosis competitors, and manufacturing base.
Research Methodology:
The North America Artificial Intelligence in Healthcare Diagnosis Market Report includes estimates of value (million USD) and volume (M Sqm). each top-down and bottom-up approaches area unit wants to estimate and validate the market size of the North America Artificial Intelligence in Healthcare Diagnosis Market and therefore the size of varied different sub-markets of the market as an entire.
The key players within the market are known through secondary analysis, and market share has been determined through primary and secondary analysis. Percentage splits and breakdowns area unit all determined using secondary and valid primary sources.
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North America Artificial Intelligence in Healthcare Diagnosis Market Developments, Competitive Analysis, Forecasts to 2027 Talking Democrat - Talking...
Artificial Intelligence in Manufacturing and Supply Chain Market is slated to grow rapidly 2022 to 2028 Talking Democrat – Talking Democrat
Global Artificial Intelligence in Manufacturing and Supply Chain Market Overview:
Global Artificial Intelligence in Manufacturing and Supply Chain Market presents insights on the current and future industry trends, enabling the readers to identify the products and services, hence driving the revenue growth and profitability. The research report provides a detailed analysis of all the major factors impacting the market on a global and regional scale, including drivers, constraints, threats, challenges, opportunities, and industry-specific trends. Further, the report cites global certainties and endorsements along with downstream and upstream analysis of leading players. The research report comes up with the base year 2021 and the forecast between 2022 and 2028.
This report covers all the recent development and changes recorded during the COVID-19 outbreak.
This Artificial Intelligence in Manufacturing and Supply Chain market report aims to provide all the participants and the vendors will all the details about growth factors, shortcomings, threats, and the profitable opportunities that the market will present in the near future. The report also features the revenue share, industry size, production volume, and consumption in order to gain insights about the politics to contest for gaining control of a large portion of the market share.
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Top Key Players in the Artificial Intelligence in Manufacturing and Supply Chain Market:IBM, Microsoft, Oracle, Google, SAS, SAP SE, Siemens, Salesforce, Cambridge Analytica, Civis Analytics, RapidMiner
The Artificial Intelligence in Manufacturing and Supply Chain Industry is severely competitive and fragmented due to the existence of various established players taking part in different marketing strategies to increase their market share. The vendors operating in the market are profiled based on price, quality, brand, product differentiation, and product portfolio. The vendors are turning their focus increasingly on product customization through customer interaction.
Major Types of Artificial Intelligence in Manufacturing and Supply Chain covered are:On-premiseCloud-based
Major end-user applications for Artificial Intelligence in Manufacturing and Supply Chain market:AutomotiveAerospaceChemicalsBuilding ConstructionOthers
Regional Analysis For Artificial Intelligence in Manufacturing and Supply ChainMarket
North America(the United States, Canada, and Mexico)Europe(Germany, France, UK, Russia, and Italy)Asia-Pacific(China, Japan, Korea, India, and Southeast Asia)South America(Brazil, Argentina, Colombia, etc.)The Middle East and Africa(Saudi Arabia, UAE, Egypt, Nigeria, and South Africa)
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Artificial Intelligence in Manufacturing and Supply Chain Market is slated to grow rapidly 2022 to 2028 Talking Democrat - Talking Democrat
Artificial Intelligence, Autonomy Will Play Crucial Role in Warfare, General Says – Department of Defense
The use of autonomy and artificial intelligence will play an increasingly vital role in military operations in such places as the Middle East, where U.S. forces no longer have a sizeable military presence, an Army general said.
Lt. Gen. Michael E. Kurilla, commander of the XVIII Airborne Corps, testified at a Senate Armed Services Committee nomination hearing today, considering his promotion to general and assignment to be commander, U.S. Central Command.
The XVIII Airborne Corps at Fort Bragg, North Carolina, has been a leader in the adoption of AI, he said.
The command has taken an approach to its adoption, that includes building a cultural mindset, data literacy, data governance and infrastructure that includes cloud computing, he said.
Also, the corps uses AI in quarterly exercises for target detection. Those exercises include personnel from all six of the military services, he said.
The most recent exercise culminated in a Marine Corps F-35 jet dropping a live, 1,000-pound bomb on an artificial intelligence-derived grid that was one meter off from the surveyed grid, he said.
"We do these exercises quarterly to improve the capability of the targeting ability of the Corps. I would look to take that if confirmed down to Centcom and expound upon that," he said.
Kurilla explained how targeting can be improved with the aid of AI.
"We can take large pieces of terrain and rapidly identify hundreds of targets, prioritize them based on a high priority target list that determines which ones we should strike with the resources that we have. And then that goes back into our firing solutions. That happens in seconds versus what would take hours normally, or sometimes even days to be able to develop these targets. And it's doing it in real time at the edge in our command posts and not being tied just back into a garrison computing environment."
AI would offer tremendous capabilities for counterterrorism in that region as well, he mentioned.
Kurilla also touched on a wide variety of other topics central to Centcom. He identified Iran as the number one malign influence in the region. He also noted that China has made inroads to many U.S. partners in the region, expressing his concerns for those agreements.
As for Afghanistan, Kurilla said the Taliban and the U.S. agree that ISIS-K is an enemy. However, he said he wished that the Taliban would also renounce al Qaeda. He also said he hoped that the U.S. could help Afghanistan, perhaps through the United Nation's World Food Program, to alleviate the humanitarian crisis.
The topic then turned to Pakistan. The U.S. and Pakistan have not always seen eye-to-eye, but Kurilla said the two nations share an interest in regional stability and countering violent extremist organizations.
Israel was also mentioned. Kurilla said he's particularly encouraged by the increase of cooperation between Israel and its Arab partners in the region. "Israel brings some very unique capabilities in terms of their military component that they believe they can share with their Arab partners in the region. The air and missile defense is a big area, based on the threat from Iran."
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Artificial Intelligence, Autonomy Will Play Crucial Role in Warfare, General Says - Department of Defense
Reproductive Urology and Artificial Intelligence – Physician’s Weekly
Over the last few decades, the promise of artificial intelligence (AI) in medicine has been widely theorized. Only in the last few years have physicians and computer scientists begun to realize the genuine therapeutic potential of this technology. Reproductive urology is a sub-discipline where AI might make a significant difference, as present prediction models and subjectivity in the area have severe limits. For a review, researchers conducted a literature study to highlight current AI uses in reproductive urology. Early AI applications in reproductive urology focused on predicting sperm parameters using questionnaires that identified relevant environmental variables and/or lifestyle habits that influence male fertility. AI has demonstrated efficacy in identifying which patient subpopulations are most likely to require a genetic workup for azoospermia. Automated sperm identification is now a reality thanks to recent breakthroughs in image processing. With the advent of AI, sperm analyses, which were formerly a laboratory-only diagnostic procedure, have made their way into the homes of healthcare consumers.AIs prospects in medicine were promising, and there was significant promise for AI in reproductive urology. It was critical to do research to determine the elements that might impact reproductive success, whether naturally or through assisted reproduction, in order to advance the discipline.
Reference:link.springer.com/article/10.1007/s11934-019-0914-4
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Reproductive Urology and Artificial Intelligence - Physician's Weekly
Researchers from IIT Madras Using Artificial Intelligence to Study Production of Fuel from Biomass | The Weather Channel – Articles from The Weather…
Artificial intelligence.
Researchers at the Indian Institute of Technology (IIT) Madras are using Artificial Intelligence tools to study the processes involved in the conversion of biomass to gaseous fuel.
With increasing environmental concerns associated with petroleum-derived fuels, biomass is a practical solution, not in the conventional sense of directly burning wood, cow dung cakes, and coal, but as a source of energy-dense fuel.
While models are being developed all over the world to understand the conversion of biomass into fuels and chemicals, most models take a long time to become operational. Artificial Intelligence tools such as Machine Learning (ML) can hasten the modelling processes.
"There is an urgent need to train the next generation of engineers on high-performance computing and machine learning skills so that they can address some of the biggest challenges before us, such as developing zero-emission technologies to tackle climate change. This work is one such example," said Dr Himanshu Goyal, Assistant Professor, Department of Chemical Engineering, IIT Madras, in a statement.
The IIT Madras team used an ML method called Recurrent Neural Networks (RNN) to study the reactions that occur during the conversion of lignocellulosic biomass into energy-dense syngas (gasification of biomass).
"The novelty of our ML approach is that it is able to predict the composition of the biofuel produced as a function of the time the biomass spends in the reactor. We used a statistical reactor for accurate data generation, which allows the model to be applied over a wide range of operating conditions, explained Dr Niket S Kaisare, Professor, Department of Chemical Engineering, IIT Madras.
The researchers detail the study in the peer-reviewed journal Reaction Chemistry and Engineering.
The team used AI tools not only for biomass-biofuel conversion studies but also for socially relevant and environmentally beneficial processes such as carbon capture (the capture of CO2 to prevent climate change) and the electrification of the chemical industry.
Researchers all over the world are finding methods to extract fuel from biomass such as wood, grass, and even waste organic matter.
Such biomass-derived fuel is particularly relevant to India because the current availability of biomass in India is estimated at about 750 million metric tonnes per year and extracting fuel from them can tremendously help the country attain fuel self-sufficiency.
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The above article has been published from a wire source with minimal modifications to the headline and text.
3 Ways Artificial Intelligence Can be Used to Improve Health Equity – HIT Consultant
John Sargent | Founding Partner, BroadReach Group
When I graduated from medical school and took the Hippocratic Oath, I vowed to not just treat the illness on a patients medical history form but to treat the person behind the diagnosis. To do this well, clinicians need to understand the whole person and the context in which they live their race, gender identity, native language, socioeconomic status, or zip code, among other things to ensure equitable care. According to the CDC, health equity is reached when every person has the opportunity to attain his or her full health potential regardless of social position or other socially determined circumstances.
Yet, health inequities abound in our healthcare systems. Research says that those Americans who live in rural communities have less access to care and subsequently worse health outcomes than those who live in non-rural communities. African American adults are more likely to report they cannot afford to see a doctor, leading to worse health outcomes. African Americans ages 18-49 are twice as likely to die from heart disease than whites. Beyond race and community, even employment status has a great effect on ones health. Members of the LGBTQ community are twice as likely to be unemployed and uninsured than their straight counterparts, reporting lower health and quality of life.
Healthcare inequities are also a drag on our economic systems. Medicare and Medicaid have an obligation to taxpayers who are paying into the system to help as many people as possible. When there are inequities in the healthcare system, it means that taxpayer dollars arent being well spent to impact the people they need to. If a health insurance companys risk pool is warped toward people who are very sick and dont have decent access to healthcare, its going to make that health plan a lot less profitable, increasing premiums for everyone.
Artificial intelligence (AI) technology and algorithms can help us bridge this health equity gap. But its important to remember that AI is not a one-size-fits-all solution. Data is great, but without an application, its not useful. AI allows us to use the data to interpret whats going on with a patient population and prescribe what to do with the data. Here are three ways we can apply this technology to help solve the health inequity problem in America and around the world.
1. Using AI to identify the problem
Health systems are dealing with a seemingly infinite amount of data on massive patient populations. Its hard to spend time sifting through the data by hand to understand whats happening within their population. AI technology can help these systems sort through that data to understand exactly where providers should focus to get the best ROI for positive patient outcomes. In a real-world example, a case manager logs onto work on a Monday morning and receives an email with details about their patient, John Doe. An AI-powered algorithm flagged that John Doe has two issues that may impact this ability to manage his diabetes: his current provider isnt a native Spanish speaker and he currently doesnt have a vehicle. This means that John Doe, who doesnt speak English, is facing two serious health inequities that could affect his ability to get the right information and physical access to the clinic for his appointments.
2. Using AI to identify next-best actions
Now that we know the problem, its important to take action and solve it. No one wants to spend time analyzing a million charts or rows of data in a spreadsheet. Decision-makers need to know what the issue is, what they need to do and how they need to do it to affect change. By using AI to provide predictive and prescriptive recommendations in a culturally sensitive way, we can bridge the equity gap.
In the John Doe example, the prescriptive recommendations that will improve Johns outcomes include finding John a doctor that speaks Spanish and setting up John with the telehealth services to ensure he has continued care regardless of his transportation challenges. AI allows us to replicate this over millions of patients quickly when compared to doing so by hand. If Amazon can predict which book on the history of World War II I should read next based on my buying history, certainly we can use similar technology to predict what issues will arise for our patients and what we need to do to intervene.
3. Using AI to better allocate limited resources
Resources are often limited in healthcare. AI technology can help providers make better decisions on where to invest, build and allocate resources more effectively to close the disparities. This type of technology provides a more strategic view that helps managers and executives answer the question, do I have the right skill sets and resources to meet my health equity challenges? If not, do I need to shift certain resources (e.g. Spanish speaking doctors) to other clinics and patients, or do I need to invest in new approaches (e.g. telehealth) or partnerships (e.g. taxi company, local churches) that help me to better treat each patient?
Healthcare is a human issue
AI can make the entire healthcare system more efficient and effective at identifying and solving these inequity issues. But at the end of the day, healthcare is still a people issue. As a doctor, I was trained to believe that I am in charge of a persons health. They come to me for a diagnosis and I write the prescription for a medication they need to address it. In reality, 99% of the patients life occurs outside the doctors office and in their community. In order to improve health equity, we must find ways to partner with the leaders of the communities in which they live.
Medical male circumcision has long been known to be a key tool in reducing the risk of HIV transmission. Now imagine yourself, an outsider, entering a Zulu community in Southern Africa. No one speaks English and they have a very specific understanding of healthcare. Try to convince a 21-year-old Zulu man to get circumcised for his health its an uphill battle. Who does this 21-year-old man listen to? Most likely his community tribal leaders. A lot of the work the BroadReach Group does today is identifying the local on-the-ground structures, whether they be the tribal or cultural structures, that would influence the communitys decision-making. Essentially choosing the next-best actions informed by behavior science. We then partner with these community groups to craft messaging and create programs to convince the population to take these health steps.
While it may look a little different, we face the same distrust patterns in the U.S., now more so than ever before. How do we convince people that are wary of health systems to see a doctor every year or get vaccinated against COVID-19? Close partnerships with trusted local community leaders.
The healthcare industry cant solve the equity problem alone we need partnerships. When healthcare companies partner with the private technology sector, it helps us think outside of the industry about whats cutting edge like new AI-driven technology and how we can apply it to healthcare. When healthcare companies partner with local community leaders, we can effect real change within a hard-to-reach population. Health inequity is a comprehensive problem that covers all of society. We cant do it alone.
About Dr. John Sargent
Dr. John Sargent is a globally recognized innovator focused on developing 4th Industrial Revolution technologies to radically improve healthcare delivery and catalyze broader development sector outcomes.John co-founded BroadReach Group in 2003 and currently serves on the Board of Managers. He is a popular speaker and thought leader on technology, innovation and health equity. He has been recognized by the World Economic Forum as one of the Social Entrepreneurs of the Year in 2015, by Frost & Sullivan with the Visionary Leadership Award in Healthcare, and by Devex as one of the Top 40 Under 40 Leaders in Development.
Prior to co-founding BroadReach Group, John was a management consultant specializing in strategic and clinical operations projects for top academic and private US hospitals. His last position before founding BroadReach was Senior Director and National Practice Leader in Clinical Operations for the Advisory Board Company (ABCO), a leading US healthcare think-tank. Additionally, he has served as a member of the Board of Directors of the Fulbright Association. John earned an undergraduate degree from Dartmouth College, a masters degree from Oxford University as a Fulbright Scholar and an MD from Harvard Medical School.
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3 Ways Artificial Intelligence Can be Used to Improve Health Equity - HIT Consultant
Artificial Intelligence is a growing threat to authenticity in art – Bulletin
Flying houses and cars, mailing services powered by rockets and widespread telepathy. These Jetson-esque'' innovations represent just a few of the hilariously inaccurate predictions made in the '70s regarding life in the 2020s. While most of the educated guesses our temporal brothers and sisters wagered about contemporary life were miles off, they werent wrong about one. In fact, their prediction not only came true, but has become one of the biggest threats to all forms of original art today: artificial intelligence.
No, the robots from Ex Machina havent started curating art collections just yet. However, the recent advent of both AI-generated artwork and music has sent ripples through both industries.
Thanks to TikTok, Wombo Dream (available on iOS, Android) has emerged as one of the most accessible forms of AI artwork. Simply by typing in phrases or keywords, Wombo will generate art using AI that combines the word prompts with elaborate murals made from preexisting images. Within seconds, Wombos AI is able piece together intricacies in art that would take human artists hours or even days, even with specifically vague prompts like Galactic Archeology With Metal-Poor Stars
With billions of images available in an instant to an advanced AI such as the one behind Wombo, the sophistication of AI-generated artwork is startling, but nowhere near as alarming as the music it can create.
AI musics vast capabilities span a comprehensive set of musical processes, including composition, performance, digital sound processing and even interactive composition. Plenty of websites out there can emulate something similar to what Wombo presents, offering an AI that can produce millions of songs based on user specifications. But music AI is far more intuitive as it possesses the competency to react in real time to a live, human performer. Utilized in this way, AI can replace entire live bands and orchestras by producing the same quality of music in less time, with less confusion and more harmony.
While less-advanced AIs use internet databases to power their machine learning, music AIs use neural networks to mimic how the brain works when creating music. Essentially, if you throw bits of music at these AIs, it will learn its patterns and frequencies by repeated exposure to it.
Perhaps one of the most unsettling examples of this technology is its utilization by one of the most musically-deprived fanbases in rap music: Playboi Carti fans. A simple YouTube search yields plenty of AI-generated Carti tracks created with the application of this technology. Fans even created an EP for Carti using AI, titled DIGITAL BUTTERFLIES. The project uses Cartis real voice, famous ad libs and even frequent Carti collaborator Pierre Bournes sound kit to craft bouncy, psychedelic, six-track trap project, one nearly as polished as something Carti himself would create early on in his career.
*embed "digital butterflies EP on youtube*
Beside being decidedly creepy and soulless, this clearly presents a plethora of pressing issues for the music industry. From further blurring the already murky lines regarding posthumous music to opening even more avenues for artist exploitation, the mere presence of AI music in its current state can and will be an obstacle.
One way or the other, original art is about to become more scarce whether we like it or not. Much in the same way we consume social media, art will have to be viewed with the eye of a skeptic.
Luke Modugno is a digital editor. Follow him on Twitter: @lmodugno5.
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Artificial Intelligence is a growing threat to authenticity in art - Bulletin
The Rise of Artificial Intelligence in 2022: Where is the World Headed? – Analytics Insight
The rise of artificial intelligence in the digital world is making decisions that impact our lives
Without a question, AI is still in its infancy, but it has reached a critical mass where both study and application may take place at the same time. We can categorically state that we have shifted gears. Whether we want it or not, AI is already making decisions that impact our lives, and it has made enormous progress in recent years.
While it is tempting to believe that AI has permeated practically every vertical or market, this is not the case. There are just a few technical hotspots in a few select areas where AI is gaining traction.
However, marketing techniques are at work to make everyone believe that AI has covered all, whereas, in reality, numerous areas remain unexplored.
Many image-recognition technologies are increasingly more capable of detecting malignancy or micro-fractures in MRI or X-ray data from patients. Many pattern-recognition systems can connect multiple pathology reports and generate a near-perfect prediction of the patients condition. Despite this, making medical advice without a doctors specific clearance is not usual.
This is great because, when human life is on the line, systems should never make the final decision. As a result, AI may only achieve the position of aided intelligence in the medical area, and it may not be authorized to become a mainstream phenomenon at all.
Human touch is getting more expensive as corporations continue to remove individuals from customer support and replace them with chatbots or AI-driven automated replies. One startups key difference during an event where companies pitched their company or product was that they offer personal help for any queries. In regards of AI- and non-AI-based solutions, were seeing an interesting trend.
Another field where AI is making inroads is self-learning solutions. It is gaining popularity due to its use of personalised learning, pace, and suggestions. However, as a result of this, teaching, coaching, and guiding will quickly become a high-touch service that will continue to be in great demand. As a result, its difficult to say if AI has actually impacted this industry or has simply mutated it into something new.
Performing arts and culture are another sector where AI has yet to influence and may not have an impact. These are such individualised and creative endeavours that they would be meaningless without the presence of a human. There have been a few AI-created art endeavours, but such art forms have a distinct flavour to them.
When it comes to end-users of AI technology, the majority are filled with fear, uncertainty, and doubt. The technologys inherent duality is a major source of concern. AI is a powerful tool, and people can use it for good or evil, just like any other tool. Furthermore, because no one has yet openly discussed how to deal with possible AI misuse, this has remained an increasing concern.
Another reason for AI scepticism is a plausible worry of job loss. It would be unquestionably hazardous and chaotic if large numbers of people lost their employment without an alternative mechanism in place.
However, if you think about it carefully, youll see that many people arent concerned about losing their jobs. When peoples regular jobs are disturbed, their biggest concern is that they will have nothing to do.
Regrettably, the bulk of AI implementation projects fails to address this issue from the start. It is done as an addition instead. It is possibly the most compelling reason for AI scepticism.
The rising trend in technical innovation has always been present. Apart from savings, AI and other developing technologies are also introducing new possibilities. New businesses and opportunities are being created as a result of these possibilities. As time goes on, this will continue to be the case.
Due to the amount of data, most daily jobs that rely on best estimates or guessing would witness a substantial shift. As more data becomes available, the demand for devices that can process it on the edge will grow, and this will be a crucial driver in continuing this trend.
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The Rise of Artificial Intelligence in 2022: Where is the World Headed? - Analytics Insight
The Global Artificial Intelligence Market is expected to grow by $ 8.63 bn during 2022-2026, progressing at a CAGR of 47.33% during the forecast…
New York, Feb. 08, 2022 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Global Artificial Intelligence Market in the Telecommunication Industry 2022-2026" - https://www.reportlinker.com/p06227629/?utm_source=GNW 63 bn during 2022-2026, progressing at a CAGR of 47.33% during the forecast period. Our report on the artificial intelligence market in the telecommunication industry provides a holistic analysis, market size and forecast, trends, growth drivers, and challenges, as well as vendor analysis covering around 25 vendors.The report offers an up-to-date analysis regarding the current global market scenario, latest trends and drivers, and the overall market environment. The market is driven growing use of AI for efficient predictive maintenance and rising use of AI for enhancing customer experience. In addition, growing use of AI for efficient predictive maintenance is anticipated to boost the growth of the market as well.The artificial intelligence market in the telecommunication industry analysis includes the component segment and geographic landscape.
The artificial intelligence market in the telecommunication industry is segmented as below:By Component Solutions Services
By Geographical Landscape North America Europe APAC South America MEA
This study identifies the increasing use of ai for network optimization as one of the prime reasons driving the artificial intelligence market growth in the telecommunication industry during the next few years.
The analyst presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources by an analysis of key parameters. Our report on artificial intelligence market in the telecommunication industry covers the following areas: Artificial intelligence market sizing Artificial intelligence market forecast Artificial intelligence market industry analysis
This robust vendor analysis is designed to help clients improve their market position, and in line with this, this report provides a detailed analysis of several leading artificial intelligence market vendors in the telecommunication industry that include Alphabet Inc., AT and T Inc., Baidu Inc., Cisco Systems Inc., Deutsche Telekom AG, Infosys Ltd., Intel Corp., International Business Machines Corp., Microsoft Corp., and NVIDIA Corp. Also, the artificial intelligence market in the telecommunication industry analysis report includes information on upcoming trends and challenges that will influence market growth. This is to help companies strategize and leverage all forthcoming growth opportunities.The study was conducted using an objective combination of primary and secondary information including inputs from key participants in the industry. The report contains a comprehensive market and vendor landscape in addition to an analysis of the key vendors.
The analyst presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources by an analysis of key parameters such as profit, pricing, competition, and promotions. It presents various market facets by identifying the key industry influencers. The data presented is comprehensive, reliable, and a result of extensive research - both primary and secondary. Technavios market research reports provide a complete competitive landscape and an in-depth vendor selection methodology and analysis using qualitative and quantitative research to forecast the accurate market growth.Read the full report: https://www.reportlinker.com/p06227629/?utm_source=GNW
About ReportlinkerReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.
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The Global Artificial Intelligence Market is expected to grow by $ 8.63 bn during 2022-2026, progressing at a CAGR of 47.33% during the forecast...
Artificial Intelligence To Control The Quality In Production Metrology and Quality News – Online Magazine – "metrology news"
Quality has always been part of AudisDNA, and its also the aim of apilot project launched last year at the Neckarsulmsite to check the correct execution of spot welds in high-volume production. The partners in this project, which is part of theVolkswagen Groups Industrial Cloudwhich is to be implemented in other plants, are SiemensandAmazon Web Services.
In the body of a car like theAudi A6, around 5,300 spotweldsare required. Up until now, thequalityof the welds has been monitored manually by technicians using ultrasound on the basis ofrandom analyses. In theWPS Analytics pilot project, in which specialists from the fields of manufacturing, innovation management, planning, digitization and IT are involved,artificial intelligenceis used to detect quality anomalies automatically and in real time.
The WPS Analytics Pilot Project
TheWPS Analytics team is led by Mathias Mayer and Andreas Rieker. Michael Haeffner, Head of Delivery Management DigitalizationforProduction and Logisticsat AUDI AG, says: Our goal is to test and developdigital solutionsfor vehicle manufacturing right through to their use in seriesproduction. With the use ofAI, we are testing an important key technology here that will make Audi and the location fit for the future.
The system consists of analgorithm, a graphical user interface (dashboard) and anapplicationfor more in-depth analyses. Thetargetof thisprojectis for the algorithm to be able to evaluate close to 100% of the set welding points, while the long-term goal is that the quality of theweldingprocesses can be automatically controlled and continuously optimized.
Artificial Intelligence In Production
The algorithm serves as a blueprint for further applications in connected manufacturing and allows us to make advancements to existing digital solutions, such as predictive maintenance, explains Mayer, who has already been working on the application of artificial intelligence in Audi production for some five years.
TheIngolstadt-based company is taking the lead in driving forward this pilot project within theVolkswagen GroupsIndustrial Cloud, which brings together production data from all of the Groupsfactoriesworldwide, with the main aim of increasingefficiencyand reducingcosts. Each cloud connected site can download applications and updates for its machines and systems, similar to an app store, increasing process efficiency.
Synergies Through The Industrial Cloud
The experience with WPS Analytics at Neckarsulmhas already proved useful at theVolkswagen siteinEmden, wherespot weldingis controlled byalgorithmsthanks to lessons learned from the projects that feed into theIndustrial Cloud. InIngolstadt, a further application is being implemented that uses an algorithmto make work in the press shop more efficient.Artificial intelligencewill be used to detect defects such as small cracks in the car body.
This project is also part of theAutomotive Initiative2025 (AI25), an initiative that brings together partners from the academic world and the IT sector to make plants, and therefore production and logistics, more flexible and smarter throughdigitalization. Already today, someinnovativetechnologiesare helping employees in practice, relieving them of monotonous and strenuous physical and manual tasks.
Source:AUDI AG
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