Category Archives: Artificial Intelligence
Important role of Artificial Intelligence in education – PC-Tablet
For decades, humanity predicted and waited for something that we know of now as Artificial Intelligence. These days, you see AI in almost anything, starting with your cell phone and ending with smart houses. Of course, one thing that we still wait for is the creation of robots that are going to be so human-like that it will be difficult to tell a real person from an artificial one. However, that sort of AI is mainly fiction.
On the other hand, it is safe to say that the kind of AI that we have now influenced almost every sphere of our lives, and education is not an exception. However, for one reason or another, the role of AI in education has been mainly underestimated, so we at CustomWritings.com, a professional essay writing company, decided to change that. We are going to list all the main aspects that AI improved in modern education.
You cant imagine how long it takes a regular teacher to go through all the tests and grade them all. That is when AI comes is more than helpful. Many programs allow teachers to take a break from grading while the system checks all the multiple-choice and fill-in-the-blank tests. When it comes to essay checking, things are a little different since such programs are not developed yet, but they are being worked on.
It is not a secret that every student has a particular learning technique, and not always a teacher can provide him or her with a necessary educational approach. That is when various kinds of educational software step in. These days you can choose a program or a system that helps you most while the teachers help is also provided when required.
Teachers are not gods, and at times, they also make mistakes. When some essential information or concept skips the teachers mind, the students are to make equal mistakes in the upcoming tests. That is when such useful course providers as Coursera step in. The system notices the patterned mistake and improves it while notifying both the teacher and the student about the mistake.
When you do not understand one point in the study, you cant move to the other. That is why many students tend to use the services of tutors so that all explained well. At the same point, not every student can afford a tutor. That is when AI tutoring systems come in. They are not ideal or too creative and complex, but they are developed to provide that basic knowledge that will help you move forward from the place that you are stuck.
The constant access to all the miracles of technology that we have on offer now has changed the way we perceive the information. It is neither good nor bad, per se. It is different. Such an AI involvement in the information perception process may result in something entirely innovative in the future. It will surely affect all the spheres, and education is clearly not an exception.
It goes without saying that no AI can substitute a real teacher. However, the scientists and developers are working on improving the AI educational systems so that they can take off all the unnecessary load of teachers.
At times it seems that there is rarely anything worse than standing in front of the class and being unable to answer the set question. The very same goes for the negative grades that you get when all the peers seem to succeed with any set task. Things like that will not have a chance in the future. When you are learning using a set program, you do not have to fail so everyone can see that. Whenever you do fail, the system will correct the mistake explaining why you failed in the first place. This is probably one of the best features that AI can bring into the educational process.
When a person fails, the AI system may not. All the data that is necessary for successful research, as well as the educational process required by every student, is never easy to gather and then sort it out accordingly. For a powerful AI system, such a task is not that difficult to understand and carry out. When you have all the data gathered in one place, you can come up with the best courses, attract the most promising student, implement the best learning techniques that correspond to the needs of modern students, etc.
It happens so very often that you cant go to the college that you like just because you cant afford traveling to the city it is situated in or anything of the kind. With the development of AI, such things may become extinct. The thing is that with the ever-developing technologies soon, you will be able to access anything from any place, and that will make education affordable for all those who are willing to learn.
To sum all up, it is safe to say that there are many changes that AI has already brought into the education system. However, that is clearly not all that we can reap from its developments. Many changes are waiting in the future as well.
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Important role of Artificial Intelligence in education - PC-Tablet
Love in the time of Artificial Intelligence – Philippine Star
Everybody loves a good love triangle, but heres one that veers away from the usual. The formidable third wheel in the romance between a man and a woman is a hologram!
Netflixs newest and now-streaming K-drama My Holo Love takes on love in the time of Artificial Intelligence (AI).
So-yeon is a woman who distances herself from people because of her face blindness disorder, which is described as the inability to recognize even familiar faces. Then she meets someone whom she can turn to for support, understanding and attention ideal qualities one hopes to find in The One, except hes someone she cant hold and touch. His name is Holo and hes an AI-powered hologram.
Now here comes Nan-do, So-yeons reclusive next-door-neighbor and Holos genius inventor. While Holo is made in Nan-dos exact likeness, the latter is the polar opposite hes lonely and disconnected from the world, too, and certainly not as sweet and kind.
But Nan-do gets drawn into the interactions between So-yeon and Holo, and becomes his own creations rival for So-yeons affection.
Yoon Hyun-min (Tunnel, Witch at Court, Tale of Fairy) plays the dual role of Holo and Nan-do, opposite the new-gen rom-com queen Ko Sung-hee (Suits, While Youre Sleeping, Diary of a Night Watchman) as So-yeon.
Can someone really find emotional attachment with Artificial Intelligence? Is AI capable of changing human capacity for friendship and ultimately, love? These are some questions that the series explores.
True to My Holo Loves tech-inspired theme, the Philippine press interviewed Hyun-min, 34, and Sung-hee, 29, via a video-conference call last Tuesday. Here are excerpts from the almost 40-minute chat:
On the possibility of a human being growing feelings for a robot or an AI-assisted hologram:
Sung-hee: First of all, in our (series), there is a point in time where So-yeon starts to develop feelings for Holo and is very confused. And I think it was when I had to act that particular part (that) I really had to think a lot about that issue, that thing that you just asked. Obviously, its not very easy. However, you can see that the character Holo in our work is very lovable and extremely charming.
Hyun-min: I dont think that its something that is completely impossible. Just the fact that we are holding this press conference, with us being here and you all the way in your respective countries this is something that I couldnt even imagine when I was a child but here we are. This is our reality today. The world is changing at such a rapid pace. I feel that in the near future, maybe a human being can have a relationship with an AI, who knows? I am open to all possibilities.
On working and being paired with each other in the series:
Sung-hee: It was great. I think it was one of those times when I felt the closest and most open in terms of having a conversation with a co-actor. And, I think, the kind of chemistry we formed behind the screens is really evident in our portrayal of the characters.
Hyun-min: It was really great for me as well. Sung-hees positive energy really exuded on set. It didnt only affect me but also members of the staff, the team, everyone. I think we all had a great time, thanks to her wonderful energy. I would love to get the chance to work with her again. And she was a really great partner (fist-bumping Sung-hee).
On finding similarities or differences with their characters:
Hyun-min: Holo is always sweet and kind because he is an AI. Nan-do the developer due to his child trauma has built walls around himself and disconnected himself from the outside world. He kind of has a hard time being kind at all times and expressing himself. I think, personally, I feel for Nan-do more out of the two, because I can always be kind and gentle when Im working or when outside of my home like Holo. However, upon returning home... theres that sense of emptiness and depression sometimes. So, I think, the imperfect human being that is Nan-do really draws me to this character and thats why I feel more for him.
Sung-hee: I share similarities, in that both of us are a little bit different when in terms of how we act when were working or when Im outside among other people and also when I am alone, and in that sense, I really related to my character. And also I myself, I often hear, I think, I appear to be cold. However, So-yeon has a completely different character once you get to know her so that was another factor that really appealed to me. I do feel that the character So-yeon is a lot nicer, much more lovely and a lot more warmhearted that I actually am (laughs). Shes very considerate of other people so much to the point that sometimes I felt frustrated with the character. So, So-yeon is definitely a character that I related a lot to, but also someone that I learned a lot from.
On preparing for their roles and learning new lessons as actors:
Sung-hee: Im mostly focused on how to really bring to light So-yeon having a relationship with an AI that is, of course, Holo, and in particular how to develop feelings for him, to love him. And also another thing was in terms of appearance, and how to maximize this sort of cold character that So-yeon had and also how she was a little bit more laidback when she was alone.
Rather than something that I learned about myself, because there were so many factors in this series where it was a completely new challenge for me. Of course, there were difficulties... but I think I grew a lot as an actress. Also because it was a sci-fi genre and I had to work against the green screen. This was something that I was completely new to. However, I did learn a lot in that aspect. So, I feel like I can be a little bit more confident in the future if I were to start in a similar type of series.
Hyun-min: Weve worked about a little over a year on this series and because it was a dual role that I had to play, it was very difficult. It was also my first-ever dual role. So, there were a lot of difficulties that came with that. But throughout the year, I think I focused mostly on my level of concentration and how not to break it. I would say that I focused mostly on the effectivity and capability in my acting.
Last year, as I was working on this series, during that time... I was also very exhausted and I was a little bit sensitive due to all of the homework. However, now looking back last year, I think it was truly a valuable experience. The fact that I was able to take on my very first dual role as an actor has become an invaluable asset to me. And it has led me to achieve a lot of personal growth. And also what I felt was that the first part of the story about the lonely couple of man and a woman and a hologram in between, its rather a unique love triangle that we see. And I think at the end of the day, we all carry a sense of loneliness. We are all a little bit lonely. But ultimately, only people or only humans can can fill that void.
On advice they would give the characters (and which viewers can learn from) on how to avoid loneliness:
Hyun-min: If I were to give advice solely on the character played by Sung-hee here, I would like to say that if you feel alone or if you have a sense of loneliness, dont take it all on yourself. Reach out, stretch out your hand because there is going to be someone that can help you, and of course, to all the journalists out there, if youre ever lonely (laughs)...
Sung-hee: I think I would give similar advice to both Holo and Nan-do. I would say you are enough. Holo himself, though hes AI, is enough. And hes a character that is sometimes and in some parts better than a human being and Nan-do despite all the hurt inside him and the way he sort of isolates himself to be more lonely, I still want to say to Nan-do, you are enough. So, know that you are enough and that you are already such a wonderful and amazing human being.
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Love in the time of Artificial Intelligence - Philippine Star
Intel drops work on one of its AI-chip lines in favor of an other – Network World
Well, that was short.
Intel is ending work on its Nervana neural network processors (NNP) in favor of an artificial intelligence line it gained in the recent $2 billion acquisition of Habana Labs.
Intel acquired Nervana in 2016 and issued its first NNP chip one year later. After the $408 million acquisition by Intel, Nervana co-founder Naveen Rao was placed in charge of the AI platforms group, which is part of Intel's data platforms group. The Nervana chips were meant to compete with Nvidia GPUs in the AI inference training space, and Facebook worked with Intel in close collaboration, sharing its technical insights, according to former Intel CEO Brian Krzanich.
For now, Intel has ended development of its Nervana NNP-T training chips and will deliver on current customer commitments for its Nervana NNP-I inference chips; Intel will move forward with Habana Labs' Gaudi and Goya processors in their place.
There are two parts to neural networks: training, where the computer learns a process, such as image recognition; and inference, where the system puts what it was trained to do to work. Training is far more compute-intensive than inference, and its where Nvidia has excelled.
Intel said the decision was made after input from customers, and that this decision is part of strategic updates to its data-center AI acceleration roadmap. "We will leverage our combined AI talent and technology to build leadership AI products," the company said in a statement to me.
The Habana product line offers the strong, strategic advantage of a unified, highly-programmable architecture for both inference and training. By moving to a single hardware architecture and software stack for data-center AI acceleration, our engineering teams can join forces and focus on delivering more innovation, faster to our customers, Intel said.
This outcome from the Habana acquisition wasn't entirely unexpected. "We had thought that they might keep one for training and one for inference. However, Habana's execution has been much better and the architecture scales better. And, Intel still gained the IP and expertise of both companies, said Jim McGregor, president of Tirias Research.
The good news is that whatever developers created for Nervana wont have to be thrown out. The frameworks work on either architecture, McGregor said. "While there will be some loss going from one architecture to another, there is still value in the learning, and I'm sure Intel will work with customers to help them with the migration.
This is the second AI/machine learning effort Intel has shut down, the first being Xeon Phi. Xeon Phi itself was a bit of a problem child, dating back to Intels failed Larrabee experiment to build a GPU based on x86 instructions. Larrabee never made it out of the gate, while Xeon Phi lasted a few generations as a co-processor but was ultimately axed in August 2018.
Intel still has a lot of products targeting various AI: Mobileye, Movidius, Agilex FPGA, and its upcoming Xe architecture. Habana Labs has been shipping its Goya Inference Processor since late 2018, and samples of its Gaudi AI Training Processor were sent to select customers in the second half of 2019.
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Intel drops work on one of its AI-chip lines in favor of an other - Network World
Artificial Intelligence Market Size Worth $390.9 Billion by 2025: Grand View Research, Inc. – Yahoo Finance
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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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
Global Artificial Intelligence (AI) Market in Food and Beverage (F&B) Industry 2017-2021 | Evolving Opportunities with Aboard Software and Ailytic |…
LONDON--(BUSINESS WIRE)--The global artificial intelligence (AI) market in food and beverage (F&B) industry market is poised to grow by USD 275.34 million during 2017-2021, progressing at a CAGR of more than 42% during the forecast period. Request Free Sample Pages
Read the 77-page research report with TOC on "Artificial Intelligence (AI) Market in Food and Beverage (F&B) Industry Analysis Report by Application (Transportation and logistics, Quality control, Production planning, and Others), by Geography (Americas, APAC, and EMEA), and Segment Forecasts, 2017-2021".
https://www.technavio.com/report/global-artificial-intelligence-market-in-food-and-beverage-industry
The introduction of regulations to improve food safety and emergence of IIoT is anticipated to boost the growth of the market.
Manufacturers in the F&B industry are increasingly adopting automation to meet regulations and guidelines set by industry associations for the maintenance of quality products. F&B manufacturers are required to have a safety system in place for analysis of hazards and risk-based preventive controls. To meet these requirements, food companies are expected to set up systems for thorough documentation of the processes implemented, to demonstrate that they are meeting the legal criteria. Vendors are offering AI platforms to meet requirements regarding preventive controls related to food safety, sanitary transportation, and foreign supplier verification programs. Quality management, database management, food production management, and enterprise resource planning are expected to be implemented with the help of technologies involving sensors and AI algorithms. Thus, the introduction of regulations to improve food safety is expected to drive market growth during the forecast period.
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Major Five Artificial Intelligence (AI) Market Companies in Food and Beverage (F&B) Industry:
Aboard Software
Aboard Software offers real-time operational solutions that allow end-users to achieve maximum efficiency, eliminate complexity, and speed up operations by providing a repository of business. The company offers Aboard Active ERP/MRP, Visual Ledger MRP, Small Business Consolidator MRP, and Enterprise Integrator MRP.
Ailytic
Ailytic delivers innovative decision support solutions to various industries such as manufacturing, general process, discrete, F&B, and packaging industries. The company offers Ailytic Advanced Scheduler, which simplifies tasks such as importing, optimizing, and selecting the best sequence of orders for a production environment.
Analytical Flavor Systems
Analytical Flavor Systems has created the platform Gastrograph AI, to help producers in the F&B industry make data-based decisions. The company offers Gastrograph AI platform, which helps in improving the production and sales of products.
Deepnify
Deepnify offers machine-learning powered demand forecasts to help in supply chain management. The company offers Deepnify solutions that use machine learning and deep learning algorithms to help end-users improve on metrics such as product availability, inventory turns, customer order fill rate, and margin.
ImpactVision
ImpactVision offers non-invasive and real-time ImpactVision product for the replacement of destructive sample tests, subjective visual inspections, and lab tests to provide more accurate data. The product can be easily integrated into production facilities and distribution centers.
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Global Artificial Intelligence (AI) Market in Food and Beverage (F&B) Industry: Application Outlook (Revenue, USD Million, 2017-2021)
Global Artificial Intelligence (AI) Market in Food and Beverage (F&B) Industry: Regional Outlook (Revenue, USD Million, 2017-2021)
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Artificial Intelligence Is Critical In Today’s Workflow Solutions – Yahoo Finance
For companies operating in the transportation marketplace, speed and accuracy are paramount. Carriers and shippers alike are continually on the lookout for ways to be faster, less expensive and more efficient to the point where standard delivery seems to mirror expedited shipping.
As the industry moves faster and faster, the documents and data generated grow at an exponential rate. Managing these documents often requires manual processes that are time-consuming and can bring any efforts to maximize efficiency to a standstill. The answer isn't to work harder but to work smarter. To avoid wasting time and resources on document processing, it is crucial for every transportation company to update document and data management strategies.
The transportation industry is in the midst of an artificial intelligence (AI) renaissance. Everything from workflow solutions to fleet management and financial decisions can be streamlined using an AI-based automated content management system (CMS).
A CMS is a software application that is used to manage a company's digital content. Transportation companies rely on a CMS to upload, process and distribute the countless documents and data involved in the shipping process. These software applications must be able to interpret data quickly without compromising accuracy.
"Transportation organizations need to start applying more technology to manage and react to data," said Larry Kerr, president and CEO of EBE Technologies. "In many cases, having the data and not reacting is worse than not having the data at all."
EBE Technologies provides automated workflow solutions for the transportation and logistics industry. The East Moline, Illinois-based company's SHIPS enterprise business process management solution is utilized by more than 600 transportation companies.
It goes without saying that everyone in transportation wants to achieve efficiency, reduce unnecessary costs and improve billing accuracy, but not all believe they have the power to upgrade. The truth, however, is that it's never been easier for transportation companies to utilize an AI-powered CMS.
Convincing companies to adopt AI workflow solutions is not difficult, according to Kerr.
"Recently, many of our clients have been affected by rising insurance costs," Kerr said. "Rates have been softer, which means the additional revenue to cover such costs must come from improvements in operating efficiencies."
However, simply using any CMS isn't sufficient to manage workflows effectively. Some transportation companies are unaware of the additional operating costs associated with the use of their current systems. Many such systems lack the ability to provide interoperability among companies' critical systems. In fact, market research firm IDC estimates that companies lose 20-30% in revenue every year due to inefficiencies related to process and content management.
The use of a CMS does save employees a tremendous amount of time from the often tedious process of manually routing documents and entering data. However, these systems may still require each transaction to be manually processed, ensuring it's routed safely to the proper department or critical system. According to an EBE Technologies white paper, a CMS with the power of AI workflows allows transportation providers to work by exception. Through this process, only out-of-standard transactions require staff intervention. AI allows providers to staff for exception levels, not 100% of the transaction levels.
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The AI-based work-by-exception process is further enhanced by optical character recognition (OCR) technology that possesses the ability to collect data by "reading" documents. Recognized OCR technology scans and automatically indexes a wide range of documents, including bills of lading, proof-of-delivery documents and invoices. A truly effective CMS, however, is incomplete without unstructured OCR processing, which converts unstructured text and optical marks into data and provides the catalyst for interoperability among critical systems, according to the white paper.
Utilizing both AI and OCR technology allows employees to focus their attention on completing out-of-standard transactions and determining the root cause for the failure. Once determined, the AI engine can be configured to manage such exceptions going forward. As a result, overhead costs and time to completion are reduced while data accuracy is greatly improved.
A CMS powered by AI workflows has a dramatic impact throughout the enterprise. As an example, it is not unheard of for companies relying on a traditional CMS to take upward of a week to gather and process the information needed to submit an invoice. The use of an AI-powered CMS with automated workflows has transportation providers benchmarking their invoice processing time to less than half an hour from the time of delivery, according to EBE.
"With AI managing the required documents and how they should be delivered, the possibility of human error is eliminated, which improves your billing functions," Kerr said. "When you provide the right documents to your customer quickly, hopefully you'll get your payment faster. With many shippers enforcing carrier scorecards regarding document and data availability, AI is now a requirement to meet shippers' expectations without additional labor."
According to EBE, utilizing a CMS powered by AI has advantages beyond improved data accuracy and working by exception to lower costs within a transportation organization. In the accounting department, carriers no longer find themselves paying duplicate invoices, net 10 terms are realized and fees for late payments are eliminated. In recruiting, AI allows carriers to respond to and onboard qualified candidates more quickly. In the safety department, data from disparate systems can be analyzed to identify at-risk driver behavior and provide corrective action automatically. In addition, the expiration of Department of Transportation documents and endorsements can be managed through automated processes. These are just a few examples of how an AI-powered CMS eliminates revenue leaks in operations and mitigates potential incidents and fines within the safety department.
Many transportation companies have embraced AI as a functional requirement, but not everyone is on board. As Kerr explained, the use of AI in the back office, as well as interoperability between systems, has only become viable in the last couple of years.
According to Kerr, in the past many systems lacked the ability to integrate with one another, resulting in redundant labor tasks. He noted that those barriers have now been broken, thanks to standard API interfaces among databases allowing for interoperability using AI. The API standardization greatly lowered the cost and risk associated with implementing an AI-based CMS.
EBE possessed the foresight to understand the critical relationship between the data within disparate systems. Through the open architecture of EBE solutions, the company was able to develop a robust AI-powered CMS solution, building upon its prior releases. This solution helps carriers achieve work-by-exception staffing levels, improve data integrity among systems and deliver a superior customer experience.
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Artificial Intelligence Is Critical In Today's Workflow Solutions - Yahoo Finance
Artificial Intelligence Saved Over $260M in Fraud, Waste in 2019 – HealthITAnalytics.com
February 04, 2020 -Highmark Inc.s Financial Investigations and Provider Review (FIPR) department has leveraged artificial intelligence to generate over $260 million in savings associated with fraud, waste, and abuse in 2019, and has saved over $850 million in the last five years.
The insurance organization is using advanced AI tools to detect indicators of fraudulent activity much faster than before. Highmark is also employing strategies to limit financial exposure of their customers. In 2020, FIPR is utilizing AI to further enhance the companys ability to identify, prevent, and stop fraudulent activities.
We know the overwhelming majority of providers do the right thing. But we also know year after year millions of health care dollars are lost to fraud, waste and abuse, said Melissa Anderson, executive vice president and chief audit and compliance officer, Highmark Health. By using technology and working with other Blue Plans and law enforcement, we have continually evolved our processes and are proud to be among the best nationally.
FIPR uses an internal team made up of registered nurses, investigators, accountants, former law enforcement agents, clinical coders, and programmers. The team performs audits to detect unusual claims, coding reviews, and investigations that evaluate the appropriateness of provider payments.
Highmarks Payment Integrity program deploys twenty-eight unique initiatives to help ensure claims payment accuracy. Fifteen of these initiatives are embedded within our FIPR department and aim directly at addressing instances of fraud, waste and abuse. Healthcare claims go through rigorous reviews, including automated AI algorithms as well as manual assessments, said Kurt Spear, vice president of financial investigations and provider review for Highmark Inc.
Although just recently implemented, were already seeing positive results from our AI software. The goal of AI is to adapt quickly to changing behavior and to help predict aberrancies earlier than traditional tools that often rely on established rules to catch suspicious behavior. We know it is much easier to stop these bad actors before the money goes out the door then pay and have to chase them.
Recently, Change Healthcare conducted a review of Highmark Inc.s Payment Integrity programs, including FIPR. The review showed that Highmarks program outperforms the industry standard and saves approximately ten percent of medical claims for group customers, and nearly 33 percent more savings than other national payers.
We have known for some time that our programs have substantial return on investment and were top notch. This external review proves that we are among the best in the nation, and that means real savings for our Highmark regional and national customers, said Jeff Bernhard, senior vice president of national and commercial markets, Highmark Inc.
This is also a benefit to our Sales teams when out competing to win business. They can share this information with our prospective customers and truly benchmark Highmark, and show it superiority around fraud and waste controls, compared to other insurance carriers.
AI has emerged as a viable, innovative way to reduce fraud and waste in the healthcare system. In a recent Optum survey of health industry leaders, 43 percent said they believe that AI will help detect fraud, waste, or abuse in reimbursement.
Health IT experts have increasingly recognized that AI can help identify which patients need testing for certain conditions, decreasing healthcare spending.
Low risk patients are getting over-tested, and high risk patients arent getting tested enough, Ziad Obermeyer, MD, Assistant Professor of Emergency Medicine at Brigham and Womens Hospital, said at the 2018 World Medical Innovation Forum.
The fact that nobody is getting this balance right is the key to seeing how an algorithm can do so much better.If an algorithm was making the decisions, we could cut tests by about 40 percent and still find about as many patients who will go on to have cardiovascular interventions.
CMS has also adopted AI and other advanced technology in an effort to reduce Medicare fraud, waste, and abuse. In October 2019, the agency unveiled a new five-pillar approach to detecting fraudulent activity based on prevention and technology.
As our programs become more complex, program integrity risks become increasingly difficult to recognize, Seema Verma, CMS Administrator wrote in a blogpost.
As the healthcare industry seeks new and advanced ways to improve care quality and streamline processes, AI tools will continue to permeate payer and provider landscapes.
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Artificial Intelligence Saved Over $260M in Fraud, Waste in 2019 - HealthITAnalytics.com
Artificial Intelligence (AI) in the Global Freight Transportation Industry, Forecast to 2025 – Yahoo Finance
NEW YORK, Feb. 4, 2020 /PRNewswire/ --
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 till 2025. 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 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.
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Author: Suriya Anjumohan
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Artificial Intelligence (AI) in the Global Freight Transportation Industry, Forecast to 2025 - Yahoo Finance
Global Artificial Intelligence in Agriculture Market Expected to Grow in Value Over the Coming Years, with a CAGR of 38.3% – ResearchAndMarkets.com -…
DUBLIN--(BUSINESS WIRE)--The "Artificial Intelligence in Agriculture Market Research Report: By Type, Technology, Application, Geographical Outlook - Global Industry Analysis and Growth Forecast to 2024" report has been added to ResearchAndMarkets.com's offering.
According to a report by the publisher, the global AI in agriculture market generated revenue of $584.0 million in 2018 and is predicted to witness a CAGR of 38.3% in the coming years.
As per the United Nations (UN) report, the world population, which is currently 7.7 billion, is predicted to reach 8.6 billion by 2030. This surge in the population is sure to increase the demand for agricultural products. This demand is primarily rising in countries including India, China, Brazil, and the U.S. because of the rapid urbanization, changing consumption habits of the populace, and increasing disposable income. With the increasing population, the current sources of agricultural production will not be enough, due to which there is a growing need for increasing the productivity. For this reason, the key agricultural product-producing countries are incorporating artificial intelligence (AI) into their agricultural practices.
AI, the imitation of human intelligence, empowers machines, especially computer systems, with capabilities such as self-correction, learning, and reasoning. In the agricultural sector, AI can be implemented for farming and gardening, in order to increase the precision and efficacy in maintaining, planting, and harvesting the crops. The major applications of AI in the agricultural sector include drone analytics, agricultural robots, livestock monitoring, and precision farming. Among these, the highest demand for AI was created by the precision farming application in 2018, and it is also going to be at the top in the coming years. This is because of the rising popularity of precision farming among the agrarian community, as there is a surging need for optimum yield using the limited available resources, which will eventually result in a reduction in the cost of crop production.
Among the above-mentioned applications, the demand for drone analytics in agricultural farms is projected to grow significantly in the near future. This is because drones that are enabled with AI are able to fly autonomously in an obstacle-filled environment. Moreover, drones are increasingly being used in the agricultural sector for assisting in irrigation schedules, estimating yield data, scanning soil health, and applying fertilizers. For instance, there is a rising demand for drones in the Xinjiang province of China for spraying pesticides in cotton fields, as by using drones, over 1,544 square miles of cotton fields can be sprayed at once, making the process time-efficient and improving the agricultural output. Because of all these advantages, several government initiatives are encouraging the adoption of drones for modernizing agricultural practices.
The demand for AI in the agricultural sector is also increasing due to the growing use of robotics in the field. Due to the increasing population and lack of skilled farm workers, the automation of agricultural processes has resulted in easier, modernized, and sophisticated farming practices via the deployment of robots. Furthermore, agricultural stakeholders are majorly focusing on refining the productivity using advanced farming practices and reducing the carbon footprint created by the entire agricultural process. Due to these factors, manufacturers in the robotics niche are coming up with offerings, which are equipped with AI, for operating in the dynamic and unstructured agricultural environment.
Key Topics Covered:
Chapter 1. Research Background
1.1 Research Objectives
1.2 Market Definition
1.3 Research Scope
1.4 Key Stakeholders
Chapter 2. Research Methodology
2.1 Secondary Research
2.2 Primary Research
2.3 Market Size Estimation
2.4 Data Triangulation
2.5 Assumptions for the Study
Chapter 3. Executive Summary
Chapter 4. Introduction
4.1 Definition of Market Segments
4.2 Value Chain Analysis
4.3 Market Dynamics
4.3.1 Trends
4.3.2 Drivers
4.3.3 Restraints
4.3.4 Opportunities
4.4 Porter's Five Forces Analysis
Chapter 5. Global Market Size and Forecast
5.1 By Type
5.1.1 By Product
5.1.2 By Service
5.2 By Technology
5.3 By Application
5.4 By Region
Chapter 6. North America Market Size and Forecast
Chapter 7. Europe Market Size and Forecast
Chapter 8. APAC Market Size and Forecast
Chapter 9. LATAM Market Size and Forecast
Chapter 10. MEA Market Size and Forecast
Chapter 11. Competitive Landscape
11.1 Analysis of Key Players in the Market
11.2 List of Key Players and Their Offerings
11.3 Competitive Benchmarking of Key Players
11.4 Global Strategic Developments of Key Players
Chapter 12. Company Profiles
12.1 International Business Machines (IBM) Corporation
12.2 Microsoft Corporation
12.3 Bayer AG
12.4 Deere & Company
12.5 A.A.A Taranis Visual Ltd.
12.6 AgEagle Aerial Systems Inc.
12.7 AGCO Corporation
12.8 Raven Industries Inc.
12.9 Ag Leader Technology
12.1 Trimble Inc.
12.11 Google LLC
12.12 Gamaya SA
12.13 Granular Inc.
For more information about this report visit https://www.researchandmarkets.com/r/iyfkca
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Global Artificial Intelligence in Agriculture Market Expected to Grow in Value Over the Coming Years, with a CAGR of 38.3% - ResearchAndMarkets.com -...
‘More than human’: How neural implants, robotics and artificial intelligence are redefining who we are – Genetic Literacy Project
When you hear the word cyborg, scenes from the 1980s films RoboCop or The Terminator might spring to mind. But the futuristic characters made famous in those films may no longer be mere science fiction. We are at the advent of an era where digital technology and artificial intelligence are moving more deeply into our human biological sphere. Humans are already able to control a robotic arm with their minds. Cyborgshumans whose skills and abilities exceed those of others because of electrical or mechanical elements built into the bodyare already among us.
But innovators are pushing the human-machine boundary even further. While prosthetic limbs are tied in with a persons nervous system, future blends of biology and technology may be seen in computers that are wired into our brains.
Our ability to technologically enhance our physical capabilitiesthe hardware of our human systems, you could saywill likely reshape our social world. Will these changes bring new forms of dominance and exploitation? Will unaltered humans be subjected to a permanent underclass or left behind altogether? And what will it mean to be humanor will some of us be more than human?
Initial answers may be closer than we think.
Physicist Max Tegmark, MIT professor and president of the Future of Life Institute, considers the recent advances in artificial intelligence and technology through an evolutionary lens to imagine us as more than human. He categorizes all life into three levels. In his view, the vast majority of lifefrom bacteria to mice, iguanas to lobstersfalls into what he calls Life 1.0. These creatures survive and replicate, but they cannot redesign themselves within their lifetime. They evolve and learn over many generations.
Moving up, somewhere between Life 1.0 and 2.0, Tegmark classifies animals such as some primates, cetaceans, and corvids that have the ability to intermesh biology and culture. These animals are able to learn complex new skills, like how to use tools. Humans take this to an extreme, and Tegmark categorizes humans as Life 2.0. Through extensive language, social intelligence, and culture, Life 2.0 individuals can jump into new environments independently of genetic constraints. (If you missed it, we wrote about how body modification, as one example, makes us more socially human in part I, Your Body as a Map, of this pair of posts.)
Just think about how our ability to learn a new language within our lifetime is a bit like adding a software package to a computer. We can add an infinite number of self upgrades during our lifetime and pass our knowledge on to future generations. We also can manipulate other life forms to our own ends on a grand scalefrom cattle farming to harnessing bacteria in the preparation of fermented foods like cheese.
But with the leaps were seeing in artificial intelligence, neuroscience, and biotechnology, our concept of animal and human could compete with the most imaginative Hollywood film. Life 3.0 doesnt yet exist on Earth, but Tegmark argues that in the future, we will see a technological life-form that can design both its hardware (which neither 1.0 or 2.0 can do) and its software (which currently only 2.0 can do).
Even in the near future, humans may be somewhere in between life-forms 2.0 and 3.0. In 2016, Elon Musk, CEO of Tesla and SpaceX, co-founded Neuralink, a company that aims to develop a braincomputer interface. Musk says his goal is to help human beings merge with software and be in sync with advances in artificial intelligence.
Whether people will volunteer to have a robot insert wires into their brain that are attached to a tiny chip implant remains to be seen. But humans across cultures have embraced a variety of technologies in surprising ways.
Today over 5 billion people have access to mobile phones. By 2025, around 71 percent of the worlds population is expected to be connected. The thought that virtually every aspect of a persons day might be influenced by a smartphone or something like it once seemed like science fiction. But as the number of digital natives grows, our relationship with technology does too.
Some of us readily anthropomorphize our gadgets and give our apps and devices names such as Siri or Alexa. We talk to them, allow them to control our surroundings, finances, shopping, and schedules. Yet many hesitate when it comes to embedding technology in our bodies if we are otherwise physically healthy.
Take, for example, microchips inserted under the skin, which can be used to pay for your shopping as well as a bus ride home. This is little different from a credit card in your back pocket, save for the convenience of not having to remember to take it with you.
Our resistance may be influenced by the yuck factor of new or different technologies or cultural shifts. But over time, what we think of as disgusting or offensive may become normalized. Lab-grown meat, for example, has gone from being a scientific and economic fantasy to something that might well be in stores by 2022. Similarly, eating insects, for those unused to the idea in the West, has become more accepted as a sustainable source of protein.
Even if more of us grow to accept the idea of implants, is Life 3.0 a genuine possibility? For now, mindcontrolled prosthetics are the closest innovation that hints at a Neuralink-type future. Such prosthetics are still in relatively early stages of development and not universally available. Nonetheless, as far as Musk is concerned, many of us are already cyborgs, with an indepth digital version of ourselves in the form of social media, email, and much more. His team, or others, may well inch us toward a version of Life 3.0.
Other early signs of how technologically integrated lives might function and impact our individual lives and societies are visible in places such as Scandinavia, where checks and cash are on their way out. In Denmark, for example, the majority of citizens make payments using their mobile phones. The absence of cash has had a direct effect on homeless people. Without smartphones of their own, homeless individuals were unable to receive payments for the newspapers they sold to earn money.
The solution was to provide homeless people with smartphones (and thus mobile payment methods). No longer a luxury, mobile phones became a basic tool vital for anyone engaging in modern society in Denmark.
As soon as we move into the idea of integrated technology as a social essential, we recognize a thorny possibility: a world where a new path to social or class dominance emergesperhaps a division between those who can and those who cannot afford to interface with technology. It begins to sound like the plot of the 20th-century dystopian novel Brave New World.
In that new world, would the Life 2.0 human without enhancements be relegated to a servile underclass? Perhaps this reflects a false dichotomy. After all, millions of people living in relatively remote regions around the planet have been able to fast-track to mobile technology, effectively skipping over earlier versions of the telephone and other communication technologies.
Nonetheless, developers of integrated technologies involving invasive surgery would be wise to consider the social ramifications of their work. Today we can accurately reconstruct the wealth distribution of an entire nation based on individual phone records. Can we predict the negative social impacts of a future Life 3.0? If contemporary clues are any answer, yes, we can. But whether we choose to ameliorate those impacts or not still lies within our control.
Matthew Gwynfryn Thomas is a data scientist and anthropologist working in the nonprofit sector in London, U.K. His current work combines machine learning and social science to address the needs of people in crisis. He has also written popular science articles for a variety of outlets, includingBioNews, SciDev.Net, and the Wellcome Trust Blog. Follow him on Twitter@matthewgthomas
Djuke Veldhuis is an anthropologist and science writer based at Monash University in Australia, where she is a course director in the B.Sc. advancedglobal challenges degree program. Her Ph.D. research examined the effects of rapid socioeconomic change on the health and well-being of people in Papua New Guinea. She has written for a series of popular science outlets, including SciDev.Net,Asia Research News, andNew Scientist. Follow her on Twitter@DjukeVeldhuis
A version of this article was originally published at the Conversation and has been republished here with permission.
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'More than human': How neural implants, robotics and artificial intelligence are redefining who we are - Genetic Literacy Project