Digital Twin Technology May Finally Prove What Sank the Titanic!

A very interesting use of AI and digital twin technology may offer new insights into the infamous sinking of the Titanic.

A digital twin is an AI-driven computer simulation of a real-world object. Cognitive digital twinning or “CDT” technology has been used to create digital twins for the maintenance and diagnostics of everything from sophisticated jet fighters to human organs! Now, CDT may solve one of the most enduring mysteries of modern times, how did the Titanic actually sink?

The RMS Titanic sank to the bottom of the North Atlantic in 1912, but the fate of the ship and its passengers has fascinated the popular imagination for more than a century. Now we have the first full-size 3D digital scan of the complete wreckage—a “digital twin” that captures Titanic in unprecedented detail. Magellan Ltd, a deep-sea mapping company, and Atlantic Productions — which is making a documentary film about the project – conducted the scans over a six-week expedition last summer.

“Great explorers have been down to the Titanic… but actually, they went with really low-resolution cameras, and they could only speculate on what happened,” Atlantic Productions CEO Andrew Geffen told BBC News. “We now have every rivet of the Titanic, every detail, we can put it back together, so for the first time, we can actually see what happened and use real science to find out what happened.”

The ship split apart as it sank, with the bow and stern sections lying roughly one-third of a mile apart.

When the first divers made it to the wreck in 1985, the bow proved to be surprisingly intact, while the stern showed severe structural damage, likely flattened from the impact as it hit the ocean floor. There is a debris field spanning a 5-by-3-mile area, filled with furniture fragments, dinnerware, shoes and boots, and other personal items.

The joint mission by Magellan and Atlantic Productions deployed two submersibles nicknamed Romeo and Juliet to map every millimeter of the wreck, including the debris field spanning some three miles. The result was a whopping 16 terabytes of data, along with over 715,000 still images and 4K video footage. That raw data was then processed to create the 3D digital twin. The resolution is so good one can make out part of the serial number on one of the propellers.

“This model is the first one based on a pure data cloud that stitches all that imagery together with data points created by a digital scan, and with the help of a little artificial intelligence, we are seeing the first unbiased view of the wreck,” historian and Titanic expert Parks Stephenson told BBC News. “I believe this is a new phase for underwater forensic investigation and examination.”

Time is running out for what’s left of the famous shipwreck. Damage from previous salvage operations and deterioration due to iron-munching bacteria feasting on the ship’s hull will mean the wreck may soon be lost to history. These full-size 3D scans will preserve all the minute details for further study, giving researchers fresh insight into what really happened in April 1912—so people can finally have some definitive answers.

Other Applications Benefiting From Digital Twin Technology

In addition to such esoteric applications as providing amazing new insights into unsolved mysteries such as the sinking of the great ship Titanic, AI and digital twinning are revolutionizing many other industries, chief among them transportation. Just as CDT can create a digital duplicate of a ship like the Titanic, 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, and measures and records real-time greenhouse gas emissions, which reduces expensive maintenance costs and avoids lost revenue associated with fleet downtime.

You can read much more about how AI and digital twin technology in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. While the book’s primary focus is on healthcare delivery, it also takes a deep dive into digital twin tech, with an entire chapter devoted to CDT and the development and launch of CarTwin!

Rohit Mahajan is a Managing Partner at BigRio and the President and Co-Founder of Citadel Discovery. He has 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.

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How AI Can Help You Be More Productive at Home

We have written many times on these pages about how AI and machine learning are improving efficiency and productivity in the workplace. But how about at home? Did you know there are many ways that AI can help you be more productive and efficient at running your household as well?

For example, several homemakers recently told The Insider how they use generative AI technology to help them plan and prep meals for their families or dinner parties. Others reported how they are using ChatGPT to generate bedtime stories to read to their children. Some parents say they have used it to create entire “original” books for their kids with corresponding images, also using AI tools, like image generator DALL-E.

Other useful “at home” uses of generative AI tools reported included asking it for help generating emails or general inspiration for creating any type of content. Travel company Expedia has said it could be helpful for people planning trips to suggest tours and itineraries.

Of course, AI-powered personal assistants like Siri, Alexa, and Google Assistant are already being used extensively at home to help manage your daily tasks, set reminders, and provide answers to all sorts of questions. These assistants can also help you control smart home devices, such as thermostats and lights, making it easier to manage your home environment.

Other Uses for Home AI

AI-powered design tools can help you create graphics, logos, and other visual content for your personal use for invitations, events, etc. These tools can provide design suggestions, help with color selection, and even generate designs based on your specifications.

AI-powered entertainment tools can help you discover new music, movies, and TV shows based on your interests. These tools can help you stay engaged and entertained during your downtime, allowing you to recharge and stay productive when you need to.

We have already seen the introduction of “smart” robots of various shapes and sizes, such as the Roomba vacuum and the like, and these robotic assistants will no doubt get smarter and much more sophisticated as AI technology progresses.

Thanks to the Internet of Things (IoT), smart security and smart appliances are already making their way into homes and household kitchens. These new AI appliances are mainly being used to create food and drinks at certain times, such as coffee machines. Some AI Smart Fridges have the technology to tell whether or not food is safe to eat, as well as having the ability to suggest recipes depending on the food in the fridge. Robotic food arms are being used to assist with meal preparation and can help people with disabilities.

There is no doubt that AI is already easing the lifestyle and homebound tasks for everyone, and it will only get better at doing so.

How BigRio Helps Bring Advanced AI Solutions to All Areas of the Market

The idea that AI can help you be more productive at home and make your household run more efficiently is no news to us at BigRio. While we specialize in AI solutions for business and industry, we realize how much of that innovation often spills over into the home. We also support AI initiatives that relate to “smart home” technologies and the interconnectivity of the Internet of Things.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve the digital world.

In fact, 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 out 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 expertise to not only weed out the companies that are not ready for the market, 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 AI investment community.

You can read much more about how AI is redefining the Internet of Things in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. While the book’s primary focus is on healthcare delivery, it also takes a deep dive into AI in general, with specific chapters on IoT and emerging “smart” technologies.

Rohit Mahajan is a Managing Partner with BigRio. He has 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.

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Could AI Robots Fix Recycling’s Biggest Problem?

Recycling is a worthy environmental effort; however, it has always had one big problem, getting a “purity” level of recycled materials that is high enough for them to be reused by manufacturers. The problem is the tedious process of sorting through recycled trash to get the choice of materials, which is now done almost entirely by hand. However, experimental robots driven by AI are offering a solution to what has been one of recycling’s biggest problems.

NBC News recently reported on the AI-robots that are being beta-tested at a materials recovery facility (MRF) in Boulder, CO.

Using machine learning, the sorting robots were able to acquire the ability to distinguish between different materials, accurately identifying pieces of plastic among sheets of paper and then efficiently separating them. This also increases accuracy and speeds while reducing manual labor requirements. By seamlessly integrating AI into recycling processes, this facility is paving the way for more efficient and effective recycling practices.

The automated sorting systems being used in Boulder are from AMP Robotics.

Similar sorting systems have been deployed in MRFs in Michigan that use AI-driven optical technology to provide real-time data about waste stream contaminants — such as too much peanut butter left in a jar — and other metrics that are just being explored. “It’s giving us this data so that we can make better decisions,” says Matt Flechter, recycling market development specialist at the Michigan Department of Environment, Great Lakes, and Energy, which is experimenting with these robotic sorters that are made by Machinex, Glacier an AI-startup that raised $4.5 million in seed funding last year to building a “proprietary AI algorithm that’s capable of recognizing over 90% of recyclables in the waste stream.”

Fletcher says leveraging AI will not only improve recycling on the back end through better sorting, but the data-driven models also will help manufacturers to create more recyclable packaging in the first place.

“The vision will be, we will have real-time data about products to bring to the manufacturer, so they can say, ‘Oh, we created a toothpaste tube that we thought was recyclable, but it turns out at the facilities the robots can’t pick it up,'” Fletcher told Axios.

Recycle Ann Arbor installed a sorting robot from Machinex called the SamurAI at its new MRF in November. The robot took three months to “learn” the shapes, sizes, and densities of the materials before it was put into operation.

How BigRio Helps Bring Advanced AI Solutions to Improve All Industries

The deployment of the Glacier and other proprietary “recycling robots.”

is yet another example of how innovative startups are advancing the ubiquity of AI and particularly how it is creating smarter and more capable industrial robots.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve the digital world.

In fact, 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 out 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 expertise to not only weed out the companies that are not ready for the market, 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 AI investment community.

You can read much more about how AI is redefining the industry in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. While the book’s primary focus is on healthcare delivery, it also takes a deep dive into AI in general, with specific chapters on robotic technologies.

Rohit Mahajan is a Managing Partner with BigRio. He has 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.

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Canadian Lab is Using AI to Better Detect Breast Cancer!

AI has been improving healthcare in many areas, but perhaps one of the disciplines where it is making the largest difference is medical imaging. AI’s ability to detect anomalies in medical images such as x-rays and MRIs that are imperceptible to the human eye are vastly improving the diagnostic capabilities of such imaging technologies.

Now, a Canadian lab has announced that it is using AI to improve breast cancer screenings. A lab out of Waterloo, Ont., is taking breast cancer research to new heights by working to help patients get the most beneficial treatment with AI-enhanced imaging technology.

When patients get breast cancer, they typically undergo a type of imaging, like an MRI, to look for cancerous tumors. The Waterloo lab has created “a synthetic correlate diffusion” MRI that is tailored to capture details and properties of cancer in a way that previous MRI systems couldn’t.

“It could be a very helpful tool to help oncologists and medical doctors to be able to identify and personalize the type of treatment that a cancer patient gets,” Alexander Wong, professor and Canada Research Chair in Artificial Intelligence and Medical Imaging at the University of Waterloo told Canadian news outlet the Global News.

Using “synthetic correlate diffusion imagining data,” the new AI-driven technology predicts whether a patient is likely to benefit from neoadjuvant chemotherapy – or chemotherapy that occurs before surgery, according to Wong.

Though the hardware of the actual MRI machine hasn’t changed in this model, what has altered is the way the technology sends “pulses” through the patient’s body and how it collects data, Wong noted.

“The cancer itself just lights up and really shows the different nuances and characteristics around it, which makes it very much easier to identify not only where the cancer is, the size of the cancer, but also the actual tissue characteristics of the cancer to help doctors make better decisions,” he said.

The AI can then analyze the MRI data to help learn whether breast cancer patients could benefit from chemotherapy before surgery in their treatment process.

“It’s essentially the combination of two types of technologies. One is the new MRI imaging technology to really capture the right information. The other is the AI advancement in terms of a deep neural network.”

Deep neural networks are able to continue improving as more information is captured, said Wong.

“The more examples it sees, the better it gets at really identifying these subtle patterns that differentiate from one another. As we train it with more and more data, it’s able to have higher levels of predictive accuracy,” he said.

As to how accurate the AI algorithm is, in a study of nearly 300 patients, Wong said, “The AI, when using our new form of MRI, was able to identify and predict with over 87 percent accuracy which patients would benefit from chemotherapy.

How BigRio Helps Bring Advanced AI Solutions to Healthcare

This new research into improved breast cancer screenings is just one of the many studies that are proving the powerful predictive power of AI and how it can be leveraged to better treat and even prevent injuries and disease.

In fact, improving disease detection and diagnostics is the area where AI is making one of the technology’s biggest impacts.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve diagnostics.

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.

You can read much more about how AI is redefining healthcare delivery and drug discovery in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI and machine learning are being used to improve healthcare delivery at every touchpoint.

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.

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AI Helps Researchers Find New Antibiotic to Attack “Superbug”

Scientists have used artificial intelligence to identify a new antibiotic that could prove to be quite useful in fighting a deadly drug-resistant bacteria commonly found in hospitals and medical offices.

Researchers report they used an AI algorithm to predict molecules that would neutralize the drug-resistant bacteria Acinetobacter baumannii. Researchers discovered a potential antibiotic, named abaucin, “can effectively suppress” the growth of the stubborn bacteria on the skin of mice, according to a study this week in the journal Nature Chemical Biology.

While the preliminary results on the potential new drug would need to be validated in larger studies, researchers believe the process used to winnow thousands of potential drugs to identify one that may work is an approach that can work in drug discovery.

“There’s a lot of trepidation around AI, and I genuinely understand it,” said Jonathan Stokes, lead author of the paper and an assistant professor of biomedicine and biochemistry at McMaster University in Ontario, Canada. “When I think about AI in general, I think of these models as things that are just going to help us do the thing we’re going to do better.”

Stokes teamed up with researchers from the Broad Institute of MIT and Harvard to screen for potential antibiotics to use on A. baumannii, a superbug that can cause infections in the blood, urinary tract, and lungs. This bacteria usually invade hospitals and healthcare settings, infecting vulnerable patients on breathing machines, in intensive care units, and undergoing operations.

The bug is one of many so-called “drug-resistant” bacteria. It had infected 8,500 in hospitals and killed 700 in 2017, according to the Centers for Disease Control and Prevention.

How Did the Researchers Use AI to Pinpoint A Particular Antibiotic?

In order to specifically target the deadly drug-resistant strain, the researchers evaluated 7,684 drugs and the active ingredients of drugs to find out which ones would be most effective against the bacteria which was grown in the lab.

Stokes said the lab team developed AI models to predict which ones would have the highest likelihood of antimicrobial activity, narrowing the field to 240 drugs or active ingredients. Researchers then narrowed the field again through testing before discovering a molecule RS102895, renamed abaucin, that appeared to be potent against the superbug.

Researchers said they could screen a much larger volume of potential drugs by using the predictive power of AI and machine-learning techniques. The study said while existing high-throughput screening can evaluate a few million drugs or chemical ingredients at once, algorithms developed from machine learning can assess “hundreds of millions to billions” of drug molecules.

Citadel and AI for Drug Discovery

Just as Stokes and his team used AI to find novel molecular formulas for the development of a new antibiotic specifically for combating a particular strain of deadly bacteria, Citadel Discovery was launched in 2021 with the purpose of giving a kind of “open access” to the data and technology that will drive the future of pharma research streamlining and lowering the costs of drug discovery and biological research.

The costs of drug discovery continue to rise, with current estimates exceeding $2 Billion. Not to mention that bringing a drug successfully through all clinical trial phases takes, on average, 10-12 years in research and development. Artificial intelligence and machine learning in drug discovery hold the key to reducing these costs and timelines.

You can read much more about how AI is redefining drug discovery in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI and machine learning are being used to improve healthcare delivery at every touchpoint, with a particular emphasis on drug discovery and Pharma research.

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

Citadel Discovery is dedicated to leveraging AI and MI for the purpose of democratizing access to the data and technology that will drive the future of biological exploration, drug discovery, and health technologies. 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.

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AI Creates New $300,000+ Job Opportunity!

Looking for a new career opportunity? How about a job that pays over $300,000 a year and requires little or no specific previous experience?

The rise of generative AI tools like ChatGPT is creating a need for “prompt engineers,” people who write questions and prose for AI chatbots to test and improve their answers. Some of these roles have salaries as high as $335,000 and don’t require degrees in IT or tech.

Anthropic, an artificial intelligence safety and research company, currently has an open role for a “prompt engineer and librarian” with a salary range between $175,000 and $335,000, as first reported by Bloomberg.

The post says the role involves building “a library of high-quality prompts or prompt chains to accomplish a variety of tasks, with an easy guide to help users search for the one that meets their needs” and building “a set of tutorials and interactive tools that teach the art of prompt engineering to our customers.”

Per the job listing, applicants who have basic programming skills and “a high level” of familiarity with large language models would make a good fit. However, Anthropic says it wants people to apply “even if you do not believe you meet every single qualification.”

Sam Altman, the CEO of OpenAI and the developer of ChatGPT, has spoken about the need for prompt engineers. In February, he tweeted that “writing a really great prompt for a chatbot persona is an amazingly high-leverage skill.”

Anna Bernstein, a prompt engineer at Copy.ai, was a freelance writer and historical research assistant before she started working with AI tools.

“I love the ‘mad scientist’ part of the job where I’m able to come up with a dumb idea for a prompt and see it actually work,” Bernstein told Insider. “As a poet, the role also feeds into my obsessive nature with approaching language. It’s a really strange intersection of my literary background and analytical thinking.”

Despite the apparent opportunities in prompt engineering for people without tech backgrounds, most high-paying roles do require people with more experience and higher levels of education in tech-focused areas, recruiters told Bloomberg.

How BigRio Helps Bring Advanced AI Solutions to the Market

With so many headlines these days about the jobs AI may take away, at BigRio, we prefer to focus on the new opportunities like prompt engineers that AI will create in the job market and for entrepreneurs and startups.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve the digital world.

In fact, 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 out 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 expertise to not only weed out the companies that are not ready for the market, 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 AI investment community.

You can read much more about how AI is redefining markets in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. While the book’s primary focus is on healthcare delivery, it also takes a deep dive into AI in general, with specific chapters on opportunities for AI startups.

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 contact us.

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CHAI Releases a “Blueprint” for Implementing Trustworthy AI for Healthcare

The Coalition for Health AI (CHAI) has recently released its long-awaited Blueprint for Trustworthy AI Implementation Guidance and Assurance for Healthcare. The “blueprint” outlines recommendations to increase trustworthiness and a roadmap to promote high-quality patient care and improved outcomes within the context of AI implementation in the healthcare environment.

The 24-page BlueprintBlueprint is the product of CHAI’s year-long effort to help health systems, AI and IT experts, and other healthcare stakeholders advance health AI while addressing important issues such as health equity and bias.

Brian Anderson, MD, a co-founder of the coalition and chief digital health physician at MITRE, said in a press release detailing the BlueprintBlueprint, “Transparency and trust in AI tools that will be influencing medical decisions is absolutely paramount for patients and clinicians. The CHAI Blueprint seeks to align health AI standards and reporting to enable patients and clinicians to better evaluate the algorithms that may be contributing to their care.”

The report closely aligns with The National Academy of Medicine’s (NAM’s) AI Code of Conduct. NAM’s goal was to align health, healthcare, and biomedical science around a broadly adopted “code of conduct” in AI to ensure responsible AI for the “equitable benefit of all.” The NAM effort will inform CHAI’s future efforts, which will provide robust best-practice technical guidance, including assurance labs and implementation guides to enable clinical systems to apply the Code of Conduct.

CHAI’s technical focus will help to inform and clarify areas that will need to be addressed in NAM’s Code of Conduct. The work and final deliverables of these projects are mutually reinforcing and coordinated to establish a code of conduct and technical framework for health AI assurance.

“We have a rare window of opportunity in this early phase of AI development and deployment to act in harmony—honoring, reinforcing, and aligning our efforts nationwide to assure responsible AI. The challenge is so formidable, and the potential so unprecedented. Nothing less will do,” said Laura L. Adams, senior advisor National Academy of Medicine.

The CHAI Blueprint also builds upon the White House OSTP “Blueprint for an AI Bill of Rights” and the “AI Risk Management Framework” from the U.S. Department of Commerce’s National Institute of Standards and Technology.

“The needs of all patients must be foremost in this effort. In a world with increasing adoption of artificial intelligence for healthcare, we need guidelines and guardrails to ensure ethical, unbiased, appropriate use of the technology. Combating algorithmic bias cannot be done by any one organization but rather by a diverse group. The BlueprintBlueprint will follow a patient-centered approach in collaboration with experienced federal agencies, academia, and industry,” said Dr. John Halamka, president Mayo Clinic Platform and a co-founder of the coalition.

How BigRio Helps Bring Advanced AI Solutions to Healthcare

The CHAI report has presented a detailed roadmap on the best case and most ethical practices for AI implementation in the medical or healthcare setting. For the past several years at BigRio, we have been dedicated to much the same thing.

BigRio prides itself on being a facilitator and incubator for emerging and innovative healthcare AI, as well as helping facilities adapt to and successfully implement such AI solutions seamlessly and effectively into their legacy operations.

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.

You can read much more about how AI is redefining healthcare delivery and drug discovery in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI and machine learning are being used to improve healthcare delivery at every touchpoint, and it discusses many of the same issues raised in the CHAI report.

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.

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Startup Leverages AI to Challenge Google for Search Engine Supremacy!

Search engine technology startup You.com has announced the launch of YouChat 2.0, a groundbreaking new “multimodal conversational AI” system that the company says will take the internet search experience to “a whole new level,” leaving search engine giant Google wondering what happened!

The company says that YouChat 2.0 is the first web search that combines advanced conversational AI with community-built apps, offering a unique and interactive experience with each query. Its blended large language model, known as C-A-L (Chat, Apps, and Links), serves up charts, images, videos, tables, graphs, text, or code embedded in its responses to user queries. The idea is fewer open tabs and less drifting away from your search engine.

“We already have 150+ apps in our main search results page, but we’re now pulling more into the chat world and into this chat interface, which is non-trivial because you basically have to allow the chat model to decide when is best to answer a question by just showing you the facts,” said You.com co-founder and CEO Richard Socher in an interview with VentureBeat. “No one has done this yet — we’re the first to launch it to the world publicly.”

Socher knows a thing or two about groundbreaking advances in natural language processing (NLP), the technology that underpins all popular search engines. According to Google Scholar, Socher is currently the fourth most cited researcher in the field. As former chief scientist (and EVP) at Salesforce and former adjunct professor at Stanford’s computer science department, Socher has built his career on novel NLP applications. He now thinks it’s time to reimagine the way we interact with traditional search engines.

“Google has done incredible research and propelled the field forward in many dimensions in terms of its research, but they are making $150 billion a year by invading your privacy and showing you ads on a search results page,” Socher said, appearing visibly frustrated with the current state of affairs. “So when you develop technology, that would work great if, instead of six ads, you had one ad, but [if] it means you lose $500 million a day, you’re probably not incentivized to launch that new technology into the world.”

“It’s the classic innovator’s dilemma,” he added. “Google is very good at running things not profitably for a long time, like Maps and YouTube, and then pulling ads into it. The problem is this particular technology changes their core product.”

The company invites developers to submit apps to its open platform and work together to create the ultimate chat-search-do engine. Developers can learn more at You.com’s developers page.

How BigRio Helps Bring Advanced AI Solutions to the Internet Experience

The announcement of YouChat 2.0 by You.com is yet another example of how innovative startups are advancing the ubiquity of AI and NLP. AI algorithms are already “running behind the scenes” of most of our internet and social media experiences, and soon they will be little or no separation between Internet of Things applications, chat, and AI, with one very much totally reliant on and integrated with the other.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve the digital world.

In fact, 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 out 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 expertise to not only weed out the companies that are not ready for the market, 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 AI investment community.

You can read much more about how AI is redefining the Internet of Things in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. While the book’s primary focus is on healthcare delivery, it also takes a deep dive into AI in general, with specific chapters on IoT and NLP technologies.

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.

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New AI Solution Uses Pooled Data for More Advanced Automotive Diagnostics

Protech Automotive Solutions’ ID3 solution leverages the idea that many data points are necessary to achieve the most accurate calibrations for automotive safety features that often need to be recalibrated after a vehicle has been involved in a collision.

ID3, which is pronounced “I-D cubed,” was recently unveiled at the 2022 SEMA Show. It uses proprietary artificial intelligence and machine learning algorithms to identify calibration needs for a given automotive repair after a vehicular collision. While that service exists in many forms today, Protech Vice President of Product Development Don Mikrut says that the key difference with ID3 is that instead of merely returning what kind of calibrations might be needed, ID3 is able to use its knowledge base to deliver more accurate assessments almost instantaneously.

“We start to triangulate all that data through the algorithms and the machine learning that we’ve developed, to come back and say, based on your pre-scan, and the estimated damages, and the OE procedures and knowledge base, we’ve been able to triangulate this,” says Mikrut, hinting at the source of the three in ID3’s name. “Every line of that estimate comes back and tells you this is what needs to be calibrated on this vehicle based on the damages.”

And according to Mikrut, all of that happens in “milliseconds.”

The genesis of the development of the ID3 AI solution was driven by all of the new safety features, such as autobraking and proximity sensors and others that are known as ADAS, for Advanced driver-assistance systems. With the advent of ADAS systems, collision shop owners had to devote a significant amount of time to manually research and determine which ADAS systems needed to be recalculated and how to do so. Existing diagnostic scans could reveal what systems were present on the vehicle but not necessarily which ones were impacted by the collision, which left a process that was open to interpretation and judgment calls by repair techs.

ID3 was developed to solve this issue.

The team at Protech leaned on “30-plus years of building a knowledge base,” according to Mikrut, that encompasses Protech’s acquired expertise as well as data from OEs for ID3 to draw on.

The solution was rolled out in 2022, and as of the start of this year, it is being used in over 1200 locations.

“ADAS ID3 builds on our expertise and history in the vehicle diagnostic industry by revolutionizing the identification of calibration and repair needs, thus saving our technicians and partners time and money,” said Chris Gutierrez, Vice President of Technology Innovation, who led the products development team. “Protech’s focus is to fix vehicles the right way the first time.”

AI, the Auto Industry. and CarTwin

Just as ID3 is leveraging AI to advance vehicle diagnostics and repair calibrations, digital twin solutions like those developed by CarTwin are also taking predictive maintenance to new levels all across the transportation industry.

Digital twin technologies 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, and measures and records real-time greenhouse gas emissions, which reduces expensive maintenance costs and avoids lost revenue associated with fleet downtime.

It is very likely in the not-too-distant future, ADAS-type technologies will advance to the point where fully autonomous vehicles will replace human-driven fleets of over-road cargo transportation and taxis and limousine services. No doubt, technology such as CarTwin’s will also be incorporated into the algorithms to keep these self-driving vehicles not only safe but on the road longer.

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.

 

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Can AI Be Used to Predict Suicide Risk?

There has been no lack of news about how AI is redefining healthcare and improving patient outcomes for physical ailments. There has not been that much news, however, on how AI can help in the treatment of emotional or mental disorders.

Until now.

Researchers have just released the results of a study in which they used AI to better predict suicide risk.

The scientists from Worcester Polytechnic Institute (WPI) and Harvard Medical School-affiliated McLean Hospital in Belmont conducted a study assessing the use of AI to predict and gain a better understanding of suicide and the mechanisms and emotional states that drive self-injury.

This particular study targeted women because, according to the CDC, death by suicide is increasing at an alarming rate among women. The group of researchers developed an algorithm that was designed to predict suicide attempts among participants and identify subgroups of patients who were at the highest risk of entering a suicidal mindset.

They then used AI approaches to cluster data to expose any existing patterns. The patterns revealed a broad set of dissociative symptoms, such as the lack of connection between one’s sense of self and the environment. This was often due to trauma, the researchers said.

Following this step, researchers trained an algorithm to distinguish between patients with various dissociation levels and the 30 healthy controls. They found that this tool could zero in on specific dissociative symptoms, predicting previous suicide attempts with an accuracy of nearly 90% percent.

Aside from AI being able to predict thoughts of self-harm and previous suicide attempts accurately, researchers also noted that the study emphasized the need for clinicians to assess patients for dissociative disorder symptoms.

“We’re trying to say that among these hundreds of symptoms and indicators, our results suggest these two or three symptoms may be helpful to focus in on,” said Dmitry Korkin, Ph.D., the Harold L. Jurist ’61 and Heather E. Jurist Dean’s Professor of Computer Science at WPI, one of the lead researchers on the project.

The key takeaway from this study is that it is one of the first to show that AI-driven programs can give clinicians predictive and theoretically preventive tools for mental illnesses, just as they are already doing in practice for many physical disorders.

How BigRio Helps Bring Advanced AI Solutions to Healthcare

The WPI research is one of the few studies that are now showing that AI has predictive value in mental health, just as it has already been put into practice in improving physical conditions. In fact, improving disease detection and diagnostics – whether that be physical, and now we see mental health — is the area where AI is making one of the technology’s biggest impacts.

BigRio prides itself on being a facilitator and incubator for such advances in leveraging AI to improve diagnostics.

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.

You can read much more about how AI is redefining healthcare delivery and drug discovery in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI and machine learning are being used to improve healthcare delivery at every touchpoint.

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.

 

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