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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Not to mention help change the world.

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

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

The primary goals of artificial intelligence are:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Most AI professionals:

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

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

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

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

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

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

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

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

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

CHICAGO--(BUSINESS WIRE)--Stats Perform, the revolutionary leader in sports AI and data, announced that Chief Scientist Dr. Patrick Lucey will deliver keynote remarks at the Association for the Advancement of Artificial Intelligence (AAAI-20) Workshop in Team Sport in New York on Saturday, February 8.

Dr. Luceys presentation Interactive Sports Analytics will examine new ways to break down player or team performance using big data and AI software. The presentation will include examples of how coaches can draw up and search for specific plays and, using AI and Stats Performs decades of tracking and multi-agent trajectory data, simulate likely outcomes specific to a particular opponent and the players involved. In addition, Dr. Lucey will demonstrate the capabilities of new body-pose data made possible through Stats Performs state of the art AutoSTATS technology.

We have reached an exciting moment in sports where coaches and analysts can now leverage big data and AI to generate advanced insights on play development and likely outcomes, Dr. Lucey said. Imagine a coach drawing up an Xs and Os play, the same way he would on chalkboard, on an iPad and simulating likely outcomes based on different sets of offensive and defensive opponents in-play. Imagine then being able to search that play and find video of every time a near similar play was run. With AI and big data, we are already making that happen at Stats Perform and I cant wait to meet and discuss this with the illustrious group of researchers at the AAAI Workshop.

The AAAI Workshop in Team Sport is one of the leading conferences for AI in team sports with participation from some of the leading global research institutions. The 34th AAAI Conference will include a research paper and poster track.

About Stats Perform

Stats Perform collects the richest sports data in the world and transforms it through revolutionary artificial intelligence (AI) to unlock the most in-depth insights for media and technology, betting and team performance. With company roots dating back almost 40 years, Stats Perform embraces and solves the dynamic nature of sport be that for digital and broadcast media with differentiated storytelling, tech companies with reliable and fast data to power their innovations, sportsbooks with in-play betting and integrity services, or teams with first-of-its-kind AI analysis software. As the leading sports data and AI company, Stats Perform works with the top global sports media, tech companies, sportsbooks, teams and leagues. For more information, visitStatsPerform.com

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Stats Perform's Chief Scientist of Artificial Intelligence to Deliver Keynote at AI in Team Sports Conference - Business Wire

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.

Read more:
Important role of Artificial Intelligence in education - PC-Tablet

Spending on Artificial Intelligence (AI) is expected to more than double from $35 billion in 2019 to $79 billion in 2022, according to IDC forecasts. But as we enter the fourth industrial revolution powered by AI, technologists have divided themselves into utopian and alarmists camps. Thats a false and dangerous dichotomy. We need to adopt a pragmatic mindset that sees AI as both a risk and a way to manage risk.

From killer robots to racism, todays headlines provide AI alarmists with ample fodder. The risks associated with AI grow as technology improves and proliferates. But unlike other paradigm-shifting technologies like the printing press, mass production, or digital commerce, its the invisible aspects of AI that we most need to worry about: algorithms that learn from patterns and can trigger costly errors and, left unchecked, can pull projects and organizations in entirely wrong directions with catastrophic consequences.

For the first time in history, a single person can customize a message for billions and share it with them within a matter of days. A software engineer can create an army of AI-powered bots, each pretending to be a different person, promoting biased content on behalf of political or commercial interests or worse, attack vulnerable systems.

Read More: How CMOs Succeed with AI-Powered CX

The doomsday scenarios arent a fait accompli, but they do underscore the need for AI systems that engage with humans in transparent ways. Every time a new technology is introduced, it creates new challenges, safety issues, and potential hazards. For example, when pharmaceuticals were first introduced, there were no safety tests, quality standards, childproof caps or tamper-resistant packages. AI is a new technology and will undergo a similar evolution.

To trust an AI system, we must have confidence in its decisions. Increasingly, bankers are asking important questions about how AI will affect consumers. The Defense Department has signaled that it understands the importance of empowering ethicists to guide AI technologies.

Meanwhile, were beginning to include AI in our long-overdue conversations about criminal justice. These are all good signs, but we need to rapidly scale our ethical inquiries by using supervisory AI systems to provide visibility and control over production AI systems.

Read More: Shaped by AI, the Future of Work Sees Soft Skills and Creativity as Essential

AI systems must reflect our values. We can do this through investment, education, and policy. But first, we must dispense with the utopian and alarmist positions. Utopians assume that every AI solution will automatically be an improvement over what came before it, and therefore miss the opportunity to address critical questions about values before deployment.

At the opposite end of the spectrum, alarmists assume the worst and therefore fail to show up to the debate. A pragmatic approach that sees AI as both a risk and a way to manage risk by pairing AI with other AI is the prerequisite mental model for grappling with the issues raised by the fourth industrial revolution.

Read More: Efficient Ways the AI Will Boost Your E-Commerce Sales

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Why Artificial Intelligence is Both a Risk and a Way to Manage Risk - AiThority

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.

Continue reading here:
Love in the time of Artificial Intelligence - Philippine Star

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.

See the rest here:
Intel drops work on one of its AI-chip lines in favor of an other - Network World

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)

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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

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