Researchers Combine AI and the Internet of Things to Track Progression of Movement Disorders

Researchers have combined wearable “Fitbit”-type technology with AI to better track and monitor movement disorders.

In two ground-breaking studies, published in Nature Medicine, a cross-disciplinary team of AI and clinical researchers have shown that by combining human movement data gathered from wearable tech with a powerful new medical AI technology, they are able to identify clear movement patterns, predict future disease progression and significantly increase the efficiency of clinical trials in two very different rare disorders, Duchenne muscular dystrophy (DMD) and Friedreich’s ataxia (FA).

DMD and FA are rare, degenerative genetic diseases that affect movement and eventually lead to paralysis. There are currently no cures for either disease, but researchers hope that these results will significantly speed up the search for new treatments.

Scientists hope that, as well as using the technology to monitor patients in clinical trials; it could also one day be used to monitor or diagnose a range of common diseases that affect movement behavior, such as dementia, stroke, and orthopedic conditions.

Senior and corresponding author of both papers, Professor Aldo Faisal, from Imperial College London’s Departments of Bioengineering and Computing, who is also Director of the UKRI Center for Doctoral Training in AI for Healthcare, and the Chair for Digital Health at the University of Bayreuth (Germany), and a UKRI Turing AI Fellowship holder, said, “Our approach gathers huge amounts of data from a person’s full-body movement—more than any neurologist will have the precision or time to observe in a patient.

“Our AI technology builds a digital twin of the patient and allows us to make unprecedented, precise predictions of how an individual patient’s disease will progress.

“We believe that the same AI technology working in two very different diseases shows how promising it is to be applied to many diseases and help us to develop treatments for many more diseases even faster, cheaper, and more precisely.”

AI, Healthcare, and the Internet of Things

These two studies are just another example of how AI is being combined with the Internet of Things (IoT) for advanced diagnostics, earlier detection of disease, and better patient outcomes.

The Internet of Things (IoT), sometimes also referred to as The Internet of Everything (IoE), is a term used to describe the network of physical objects that we know as the “smart things” which are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet.

In terms of healthcare, it can readily be seen how IoT allows for the interactivity between bedside monitors, smartwatches, fitness trackers, implanted medical devices, and any other “thing” that transmits or receives a signal containing pertinent medical data that can then be accessed or stored from or to anywhere.

In broad terms, IoT is changing the very nature of data acquisition and data analytics as they are applied to healthcare, transforming both into something far deeper and more powerful.

Traditionally, healthcare organizations currently base most of their clinical and financial analytics on conventional data sources like EHRs, insurance claims data, and lab results. But now, thanks to the Internet of Things, they are starting to integrate behavioral data from clients’ credit cards or fitness data from health trackers and smartphone data, including searches for health topics and likes on social media.

Add to that all of the “things” such as remote monitoring from internet-connected prescription bottles, Bluetooth-connected scales, or wearable devices such as in Professor Faisal’s studies, – and it is easy to see how IoT is bringing a vastness and richness of data to healthcare that was never before possible and can improve patient care across the board.

How BigRio Helps Bring Advanced AI Solutions to Healthcare

Like the muscle movement studies, leveraging IoT solutions for medical applications is an area where AI is making one of the technology’s biggest impacts in healthcare.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI and IoT tech to improve healthcare delivery and drug discovery. In fact, we have launched an AI Studio specifically for US-based Healthcare startups with AI centricity. Our mission is to help AI startups scale and gear up to stay one step ahead of the pack and emerge as winners in their respective domains.

AI Startups face numerous challenges when it comes to demonstrating their value proposition, particularly when it comes to advanced AI solutions for pharma and healthcare. We have taken an award-winning and unique approach to incubating and facilitating startups that allow the R&D team and stakeholders to efficiently collaborate and craft the process to best suit actual ongoing needs, which leads to a faster, more accurate output.

We provide:
• Access to a top-level talent pool, including business executives, developers, data scientists, and data engineers.
• Assistance in the development and testing of the MVP, Prototypes, and POCs.
• Professional services for implementation and support of Pilot projects
• Sales and Marketing support and potential client introductions.
• Access to private capital sources.

BigRio excels in overcoming such initial hurdles, which present nearly insurmountable obstacles to a startup operation.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

Microsoft Partners to Develop AI-Based Healthcare Services

Tech giant Microsoft is partnering with Vietnam-based AI conglomerate VinBrain to develop artificial intelligence-based healthcare services.

Under the collaboration, the two companies will work together to work on three areas of healthcare AI — data sharing, cross-product validation, and research and development, according to a recent press release from VinBrain.

VinBrain will also use Microsoft’s Azure Cognitive Services for computer vision to validate new deep-learning models.

The aim of the partnership is to accelerate the development of AI products in the health technology space. According to VinBrain, the AI platform runs on a dataset of over 2 million images sourced from multiple regions – the United States, Asia, and Europe. These data will be shared via Microsoft Azure, which will also ensure privacy and security, manage ever-changing compliance regulations, and improve data governance.

As part of the collaboration, VinBrain will also use Azure Cognitive Services for Computer Vision to validate new deep-learning models, including Microsoft’s latest computer vision model called Florence.

Accroding to the two companies the goal of the collaboration is to leverage AI to be applied to improve medical services in remote areas where there are limited medical facilities. “On the social aspect, this will help speed up the process of resolving [the] increasing number of healthcare issues with a lack of infrastructure, uneven doctor-to-patient ratio, and increased demand for healthcare services,” they said in a joint statement.

For VinBrain CEO Steven Truong, this partnership will deepen the company’s focus on and boost its development of AI products in the health technology space. “Using the latest foundation of AI technology and evaluation, this collaboration with Microsoft will directly impact billions of people through early [disease] detection and workflow productivity,” he added.

Perhaps equally important, the partnership, the first between Microsoft and a major player in the AI space from Vietnam is seen to open up opportunities for Microsoft to expand its presence in Southeast Asia’s healthcare scene.

 

How BigRio Helps Facilitate Investment in AI Startups

Much like the collaboration between Microsoft and VinBrain, BigRio is partnering with startups to develop healthcare initiatives with AI at the core of their solutions.

In fact, we have launched an AI Studio specifically for US-based Healthcare startups with AI centricity. Our mission is to help AI startups scale and gear up to stay one step ahead of the pack and emerge as winners in their respective domains.

AI Startups face numerous challenges when it comes to demonstrating their value proposition, particularly when it comes to advanced AI solutions for pharma and healthcare. We have taken an award-winning and unique approach to incubating and facilitating startups that allow the R&D team and stakeholders to efficiently collaborate and craft the process to best suit actual ongoing needs, which leads to a faster, more accurate output.

We provide:
• Access to a top-level talent pool, including business executives, developers, data scientists, and data engineers.
• Assistance in the development and testing of the MVP, Prototypes, and POCs.
• Professional services for implementation and support of Pilot projects
• Sales and Marketing support and potential client introductions.
• Access to private capital sources.

BigRio excels in overcoming such initial hurdles, which present nearly insurmountable obstacles to a startup operation.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

How Artificial Intelligence Is Improving Telemedicine

Telemedicine or telehealth services were already on the upswing before the arrival of the COVID-19 pandemic. Since the pandemic, as we were forced into quarantine, more patients and many more doctors and healthcare facilities became reliant on telehealth – pushing advancement in telehealth apps. Telemedicine apps needed to become broader, faster, more interactive, more intuitive, and more accurate — a need that was successfully fulfilled by AI.

AI is being increasingly used in telemedicine to allow doctors to make more data-driven, real-time decisions that may improve the patient experience and health outcomes.

According to a study from MIT, 75% of healthcare facilities that utilized AI reported improved capacity to manage illnesses, and 4/5 said that AI aided in reducing employee fatigue. AI in healthcare is a promising strategy for the future of telemedicine applications, given that COVID-19 continues to place a strain on both the volume of patient data analysis and the number of people who need medical attention.

In one example cited in the MIT study, an AI-integrated system was used to help a doctor in India manage his telehealth patient load. The system, which was designed by US-based company Welltok, was able to provide real-time analysis of the doctor’s interactions with patients and make recommendations on how he could improve his care. Telehealth solutions like these lower the burdens on health plans, providers, and employer benefit managers while providing an on-demand customized experience for patients.

According to Welltok, its AI “chatbot” has an accuracy rate of 98 percent and was found to save consumers time by over 60%.

Virtual nursing assistants are another way that AI is being used to deliver improved telehealth services. These assistants use natural language processing (NLP) to understand questions asked by patients and provide answers based on information from their electronic health records.

One example of a virtual nursing assistant is the app NurseWise, which was developed by the American Nurses Association. This app provides nursing advice and guidance to patients 24/hours a day, seven days a week.

Another progressive use of telehealth, also driven by the pandemic, was the increased use of RPM, which stands for remote patient monitoring. RPM is a way to gather and transmit patient health data to medical specialists outside of a doctor’s office or a clinical environment via linked technology. RPM leverages AI and Internet of Things technologies such as the Apple Watch, Google Fit, and other wearables to collect patient information and other vital signs like heart rates, sleep patterns, and physical activity levels.

Thanks to advances in AI, telehealth is becoming more widely available and affordable, making it easier for people to get the care they need without having to ever leave their homes!

How BigRio is Helping to Advance Telehealth

At BigRio, we like to feel that we are doing our part to improve telehealth by using our resources to help existing telemedicine providers and AI startups who are focused on leveraging AI for advanced telehealth applications.

For example, we recently had a client, a tech giant in the healthcare industry known for its telemedicine platform that connects providers, insurers, patients, and innovators to deliver greater access to more affordable, higher quality care. Due to the unprecedented times of the global COVID pandemic, this client needed to strengthen and expand their virtual care platform in order to stay ahead of their competition. We created a proprietary Accelerate Framework in order to meet aggressive deadlines and reduce the risk of market loss. Overall, upon implementation, the client saw three areas of improvement to make their application more competitive for their new market.

1. Improved access and documentation of Patient Care History
2. Migrating data and integrating old data from legacy systems
3. Increasing Security standards and SSO

What we did for them, we could do for you whether you have an existing telehealth application or are in the design and development phase; if you want to learn more about transforming your telehealth offerings, please contact us.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

How AI is Solving Healthcare Administrative Problems

In 2022 readers of these pages saw many reports on the incredible advances AI is creating in diagnostics and patient care. However, there is more to the delivery of healthcare in this country and to improving patient outcomes than direct treatment protocols. As it turns out, AI is tackling those issues as well, solving many of the bottlenecks and other burdens that are placed upon healthcare administration.

“Clinical burnout” is a very real problem among healthcare personnel. Mounds of paperwork and short staff have only increased these pressures in recent years. The more time doctors, nurses, and other clinical staff have to spend on administrative duties, the less time they can spend with patients – overall care at the facility or hospital suffers, and readmission rates increase.

According to the American Academy of Family Physicians, primary care physician appointments take an average of 18 minutes, of which 49% of the time is spent handling electronic health recording.

But a relatively new application of AI in healthcare, known as “computer-assisted physician documentation (CAPD),” can and is changing all of that, so more of the clinician’s time during a visit is spent on patient care and not on administrative tasks.

According to 3M when of the initial implementers of the solutions, “CAPD acts as a scribe and advisor, nudging clinicians with documentation suggestions to make record keeping as thorough as possible. These non-intrusive nudges decrease clinician stress and reinforce accurate billing and reimbursement.”

As AI assists with the capture-to-code process, integrated electronic health record (EHR) systems must work in tandem with cloud-based systems to pass and connect information across departments.

CAPD assistants not only save time but also lower the chances of errors and duplicative work. Information sharing across departments gives transparency to the revenue cycle and provides a complete picture of both the patient story and population health.

“The better the coding is, the better the outcome for the hospital, which enables the hospital to make decisions that will improve their services to patients,” explains Catalin Velescu, 3M area division director of the EMEA region.

How BigRio Helps Facilitate Advancement in Healthcare AI

Like the AI technology being developed and implemented by big IT players such as 3M, BigRio is also helping to foster innovation in AI for healthcare.

In fact, one of our most successful cases was using our resources to create a new cloud-based intuitive model for one of the top 10 EMR/HER providers in the US. The Client realized that their EHR platform needed UI/UX redesign and revision to take advantage of cloud-based integrations and applications. BigRio stepped in to create a modernization roadmap strategy, architecture, execution plan, and prototype to fit the Client’s needs.

We like to think of ourselves as a “Shark Tank for AI.”

If you are familiar with the TV series, then you know that, basically, what they do is hyper-accelerate the most important part of the incubation process – visibility. You can’t get better visibility than getting in front of celebrity investors and a TV audience of millions of viewers. Many entrepreneurs who have appeared on that program – even those who did not get picked up by the sharks – succeeded because others who were interested in their concepts saw them on the show.

At BigRio, we may not have a TV audience, but we can do the same. We have the contacts and the expertise to not only weed out the companies that are not ready, as the sharks on the TV show do but also mentor and get those that we feel are readily noticed by the right people in the biomedical community.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

Artificial Intelligence Moves Heavily Into the NFT Space!

Investors take note, machine learning is beginning to have a powerful impact on generative art non-fungible tokens (NFTs).

NFTs are cryptographic assets on a blockchain with unique identification codes and metadata that distinguish them from each other. Most often, NFTs are used to represent real-world items like artwork and real estate. “Tokenizing” these real-world tangible assets makes buying, selling, and trading them more efficient while reducing the probability of fraud.

With that in mind, AI is becoming increasingly important in the non-fungible token space. “Generative art” – art that has been created by AI — has quickly emerged as one of the main categories of the NFT market, driving innovative projects and investment in astonishing collections. From the works of AI art legends such as Refik Anadol or Sofia Crespo to Tyler Hobbs’s new QQL project, NFTs have become one of the main vehicles to access AI-powered art.

The rise of generative AI has come as a surprise even to many of the early AI pioneers, who mostly saw this discipline as a relatively obscure area of machine learning. Its leap to dominance in the NFT market has largely been driven by gains in computational power and next-gen MI algorithms that can help models learn without requiring a lot of labeled datasets, which are incredibly limited and expensive to build.

One of the most significant of these advances has been “text to image” (TTI). AI-driven TTI programs such as DALL-E and GLIDE allow users to describe in text what they would like the program to render, and it then creates an interpretive image based on the text, with some profoundly remarkable results. Thus making TTI ideal for the creation of unique and marketable NFTs.

There are also similar generative art solutions such as “text-to-video” or “image-to-image,” but TTI, by far, is having the greatest impact on the NFT market because a disproportionate percentage of digital art collectibles are represented as static images.

Throughout the history of technology, there have been many examples of seemingly disparate trends coming together to form a market symbiosis that benefits both. The most recent example is the social-mobile-cloud revolution, in which each one of those trends expanded the market of the other two.

Generative AI and NFTs are starting to exhibit a similar dynamic. Both trends have been able to bring complex technology to mainstream culture. NFTs complement generative AI with digital ownership and distribution models that would be nearly impossible to implement otherwise. Similarly, generative AI is likely to become one of the most important sources of NFT creation now and into the future.

How BigRio Helps Facilitate Investment in AI Startups

Like what is occurring with NFT and AI-generated art, BigRio looks for and helps to facilitate such market symbiosis.

We like to think of ourselves as a “Shark Tank for AI.”

If you are familiar with the TV series, then you know that, basically, what they do is hyper-accelerate the most important part of the incubation process – visibility. You can’t get better visibility than getting in front of celebrity investors and a TV audience of millions of viewers. Many entrepreneurs who have appeared on that program – even those who did not get picked up by the sharks – succeeded because others who were interested in their concepts saw them on the show.

At BigRio, we may not have a TV audience, but we can do the same. We have the contacts and the expertise to not only weed out the companies that are not ready, as the sharks on the TV show do but also mentor and get those that we feel are readily noticed by the right people in the growing AI investment community.

Because we see so many potential AI innovators, we are also ideally suited to create the kind of synergy between concepts and applications such as is occurring with AI, ML and NFTs.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

AI Leverages Nursing Expertise to Improve Patient Outcomes

The know-how and experience of nurses are a critical body of knowledge and expertise about patients and patient care. Wouldn’t it be wonderful if there was a way to pool all of that knowledge into one place for hospitals and health organizations to make better decisions about patients?

There is, and as you might imagine, it involves AI.

Several health systems, led by the Columbia University Irving Medical Center (CUIMC), are testing an AI-driven predictive tool that is attempting to emulate nurses’ seemingly innate ability to pick up cues about patients’ health from subtle changes in behavior and appearance.

According to its developers, CONCERN (COmmunicating Narrative Concerns Entered by RNs) is a predictive tool that extracts nurses’ expert and knowledge-driven behaviors within patient health records and transforms them into observable data that support early prediction of organ failure or other critical conditions in hospitalized patients.

CUIMC is partnering with three hospital systems — Mass General Brigham (MA), Vanderbilt University Medical Center (TN), and Washington University School of Medicine/Barnes-Jewish Hospital (MO) — to test the effectiveness of the CONCERN implementation toolkit, developed to support large-scale adoption of the tool.

This initiative recently received funding from the American Nurses Foundation through the Reimagining Nursing Initiative.

“CONCERN shows what nurses already know: Our risk identification is not simply a subjective clinical hunch,” said Sarah Rossetti, assistant professor of biomedical informatics and nursing at Columbia, in a statement. “We’re demonstrating that nurses have objective, expert-based knowledge that drives their practice, and we’re positioning nurses as knowledge workers with tremendous value to the entire care team.”

Annually, more than 200,000 patients die in US hospitals from cardiac arrest, and over 130,000 patients’ deaths are attributed to sepsis. Many of these deaths could be preventable if patients who are at risk are detected earlier. Prior work from the CONCERN team found that nursing documentation within EHRs contains information that could contribute to early detection and treatment, but these data are not being analyzed and exposed by EHRs to clinicians to initiate interventions quickly enough to save patients.

How BigRio Helps Bring Advanced AI Solutions to Healthcare

Like the CONCERN project, leveraging human expertise and adapting to the predictive power of AI algorithms is an area where AI and machine learning are making one of the technology’s biggest impacts in the healthcare field.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve patient outcomes. In fact, it was my father’s own battle with and eventual death from lung disease that set me on my path to finding ways to use AI to provide earlier detection of serious medical conditions for improved patient care.

Eventually, among our other success stories, we did collaborate with a researcher who is in the process of developing a cognitive digital twin of the human lung. Right now, that technology is being used specifically in the realm of testing inhalers for asthma patients, but like the CONCERN project, it has broader implications for better diagnostics and early interventions to save lives.

We like to think of ourselves as a “Shark Tank for AI.”

If you are familiar with the TV series, then you know that, basically, what they do is hyper-accelerate the most important part of the incubation process – visibility. You can’t get better visibility than getting in front of celebrity investors and a TV audience of millions of viewers. Many entrepreneurs who have appeared on that program – even those who did not get picked up by the sharks – succeeded because others who were interested in their concepts saw them on the show.

At BigRio, we may not have a TV audience, but we can do the same. We have the contacts and the expertise to not only weed out the companies that are not ready, as the sharks on the TV show do but also mentor and get those that we feel are readily noticed by the right people in the biomedical community.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

 

AI Creates Novel Proteins Paving the Way for Radical New Therapies!

An exciting partnership between computing and graphics giant Nvidia and AI startup Evozyne has announced that they have been able to produce novel versions of a human protein that has never been seen in nature — but with “enhanced function” and the same safety as native proteins. The researchers say that the AI breakthrough lays […]

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What is Machine Perception, and Why is It important to AI?

IT Experts Predict The Top Five Advances in AI for 2023!

AI is known for its ability to make very accurate predictions. But often, human prognosticators are pretty good at it too! In this article, we take a look at what leading IT experts say they think will be the top five advances in AI and machine learning in 2023, as compiled by The Enterprisers Project.

1. There Will Be Continue Advancement of AI Applications in Healthcare

“AI will yield tremendous breakthroughs in treating medical conditions in the next few years. Just look at the 2021 Breakthrough Prize winner Dr. David Baker. Dr. Baker used AI to design completely new proteins. This ground-breaking technology will continue having huge ramifications in the life sciences, potentially developing life-saving medical treatments for diseases like Alzheimer’s and Parkinson’s.” — Michael Armstrong, Chief Technology Officer, Authenticx.

2. Continued Merging of AI and Quantum Computing

Phil Tee, Co-founder, and CEO, of Moogsoft, says to, “Watch the crossover from fundamental physics into informatics in the guise of quantum and quantum-inspired computing. While I’m not holding my breath for a practical quantum computer, we will see crossover. The mix of advanced mathematics and informatics will unleash a new generation of engineers uniquely placed to exploit the AI wave.”

3. AI Will Not Replace Humans

Despite dozens of sci-fi movies and novels to the contrary, the experts do not believe that AI will replace humans in 2023 and the years ahead, but instead, they expect to see increased interaction between human and artificial intelligence with an increased synergy between the two. “While there will be growing adoption of AI to enhance our collective user experience at scale, it will be balanced with appropriate human intervention. Humans applying the insights provided by AI will be a more effective combination overall than either one doing it alone. How and where this balance is struck will vary depending on the industry and the criticality of the function being performed. For example, radiologists assisted by an AI screen for breast cancer more successfully than they do when they work alone, according to new research. That same AI also produces more accurate results in the hands of a radiologist than it does when operating solo.” – E.G. Nadhan, Global Chief Architect Leader, Red Hat

4. A Move Towards More Ethical AI and an AI Bill of Rights

As we reported earlier this year, the Biden administration had launched a proposed “AI Bill of Rights” to help ensure the ethical use of AI. Not surprisingly, it is modeled after the sort of patient “bills of rights” people have come to expect as they interact with doctors, hospitals, and other healthcare professionals.
David Talby, CTO of John Snow Labs, says to see continued movement in this direction. “We can expect to see a few major AI trends in 2023, and two to watch are responsible AI and generative AI. Responsible or ethical AI has been a hot-button topic for some time, but we’ll see it move from concept to practice next year. Smarter technology and emerging legal frameworks around AI are also steps in the right direction. The AI Act, for example, is a proposed, first-of-its-kind European law set forth to govern the risk of AI use cases. Similar to GDPR for data usage, The AI Act could become a baseline standard for responsible AI and aims to become law next Spring. This will have an impact on companies using AI worldwide.”

5. AI Will Support Increased and “Smarter” Automation

“Everyone understands the value of automation, and, in our software-defined world, almost everything can be automated. The decision point or trigger for the automation, however, is still one of the trickier elements. This is where AI will increasingly come in: AI can make more intelligent, less brittle decisions than automation’s traditional ‘if-this-then-that’ rules.” – Richard Whitehead, CTO, and Chief Evangelist, Moogsoft.

How BigRio Helps Facilitate the Future of AI

At BigRio, we not only agree with these experts on these top five advances in AI that will likely occur in 2023, but we are also actively trying to facilitate them!
We like to think of ourselves as a “Shark Tank for AI.”

If you are familiar with the TV series, then you know that, basically, what they do is hyper-accelerate the most important part of the incubation process – visibility. You can’t get better visibility than getting in front of celebrity investors and a TV audience of millions of viewers. Many entrepreneurs who have appeared on that program – even those who did not get picked up by the sharks – succeeded because others who were interested in their concepts saw them on the show.

At BigRio, we may not have a TV audience, but we can do the same. We have the contacts and the expertise to not only weed out the companies that are not ready, as the sharks on the TV show do but also mentor and get those that we feel are readily noticed by the right people in the growing AI investment community.

Rohit Mahajan is a Managing Partner with BigRio. He has a particular expertise in the development and design of innovative solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

BigRio is a technology consulting firm empowering data to drive innovation, and advanced AI. We specialize in cutting-edge Big Data, Machine Learning, and Custom Software strategy, analysis, architecture, and implementation solutions. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.

The Enterprisers Project is a community and online publication helping CIOs and IT leaders solve problems and drive business value. The Enterprisers Project, supported by Red Hat, also partners with Harvard Business Review.

Digital Twin Technology Being Used to Create Next-Gen Aircraft

Digital twin technology is becoming more and more mainstream, particularly when it comes to the maintenance and monitoring of complex mechanical systems such as aircraft.

GENEX, an EU-funded startup, has announced the creation of a new digital twin framework that will be used to create “the next generation” of safer and greener composite aircraft.

Launched on Sept. 1, 2022, GENEX is a 42-month, 5.7 million Horizon Europe collaborative research project seeking to develop an end-to-end digital twin-driven framework for optimized manufacturing and maintenance of next-generation composite aircraft structures.

According to the company, “enhanced computational models will embed interdisciplinary knowledge of aircraft components and manufacturing/repair processes to support their optimization as well as enable data management and monitoring across the entire life cycle of the aircraft’s operation.”

GENEX will really ramp up in the New Year. It is projected to run through 2026.

According to a company press release about the initiative, “The core of the GENEX project is based on three [digital twin] blocks focused on different facets of the aircraft use life, which, eventually, will be integrated into a fourth to form the multidisciplinary digital twin.”

Each block is as follows:

     • Block 1 – Manufacturing Process Digital Twin: An automated tape laying (ATL) process, coupled with hybrid-twin simulation methods, will be developed for the eco-efficient and advance manufacture of recyclable thermoplastic composites.

      • Block 2 – Product Usage Digital Twin: Data- and physics-based machine learning (ML) algorithms for damage detection and location, combined with high-performance computing (HPC)-based multi-physics and AI-powered digital twin tools for fatigue life prediction.

      • Block 3 – MRO Digital Twin: Augmented reality tools, together with novel laser-assisted methods for surface cleaning and monitoring, smart monitoring, and in-situ tailored heating of composite repair blankets, will be further developed to provide additional assistance in manual scarf repair operations, increasing the reliability of the repair process, while supporting the modification and virtual certification of MRO practices.

    • Block 4 – Cognitive Digital Twin: Combined integration of blocks 1-3 for the realization of a digital twin-drive framework implemented into a common industrial internet of things (IIoT) platform.

“The aviation industry is facing a two-fold challenge — targeting carbon neutrality while also adopting the digitalization of next-generation aircraft,” Dr. Calvo-Echenique says. “In GENEX, we hope to provide the needed technological impulse to optimize composite components manufacturing, and operation and repair processes using digital twin strategies.”

Other Industries Benefiting from Digital Twin Technologies

As you can see from the GENEX project, AI and digital twinning are revolutionizing many industries, chief among them transportation. Cognitive digital twin technologies are proving invaluable for the predictive maintenance of high-value military vehicles, airplanes, ships, and even passenger cars. Digital twin solutions like those developed by CarTwin extend the lifespan of cars and other vehicles by monitoring the vehicle’s “health” through its “digital twin.”

Basically, CarTwin can provide diagnostic and predictive models for all vehicle systems for which data is available (either directly or indirectly) onboard the vehicle.
Virtually any part of the vehicle that has sensors or that sensors can be developed for can be “twinned.” These data sets are then enhanced and augmented with design and manufacturing data that is already available by the OEM.

Primarily designed for use in fleets of vehicles, in combination with powerful AI models, CarTwin predicts breakdowns, monitors and improves performance, measures and records real-time greenhouse gas emissions, which reduces expensive maintenance costs and avoids lost revenue associated with fleet downtime.

Rohit Mahajan is a Managing Partner at BigRio and the President and Co-Founder of Citadel Discovery. He has a particular expertise in the development and design of innovative AI and machine learning solutions for clients in Healthcare, Financial Services, Retail, Automotive, Manufacturing, and other industry segments.

CarTwin has leveraged AI and Digital Twin technologies to create a digital, cloud-based clone of a physical vehicle designed to detect, prevent, predict, and optimize through AI and real-time analytics. If you would like to benefit from our expertise in these areas or if you have further questions on the content of this article, please do not hesitate to contact us.