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The next major evolutionary step in AI and machine learning will be the large-scale implementation of “adaptive AI.” What exactly is “adaptive AI,” and what will the leap to this new technology mean for fledgling AI companies and startups?

The power of AI is its ability to take in and interpret quite large volumes of data and then accurately generate insights and predictions that can lead to smarter decision-making by the humans leveraging the algorithms. As the name implies, adaptive AI systems take that ability to the next level by being able to “adapt” or continuously respond to new as it becomes available and modify its outputs accordingly.

Adaptive AI dynamically incorporates new data from its operating environment to generate more accurate insights on a real-time basis. It is increasingly regarded as artificial intelligence’s next evolutionary stage. By incorporating a more responsive learning methodology, such as agent-based modeling (ABM) and reinforcement learning (RL) techniques, adaptive AI systems are more reactive to the changing world around them and can thus more seamlessly adapt to new environments and circumstances that were not present during the earlier stages of the AI system’s development.

This kind of almost instantaneous adaptability is certain to prove critical over the coming years, during which the likes of the Internet of things (IoT) and autonomous vehicles are expected to expand greatly in popularity. Such applications must continuously consume massive quantities of data to reflect ongoing changes in the external environment in real time.

Well-known IT Analyst Erick Brethenoux observed in October 2022. “Adaptive AI systems aim to continuously retrain models or apply other mechanisms to adapt and learn within runtime and development environments—making them more adaptive and resilient to change.”

Advancements in adaptive AI will also greatly improve AI applications in healthcare and will likely save lives. The ability to consistently analyze data related to thousands, if not millions, of patient symptoms and vital signs can enable adaptive AI systems to optimize the clinical recommendations they produce.

Over the long term, adaptive AI delivers faster, more accurate outcomes, which should mean that more meaningful insights can be gleaned by any enterprise relying on AI for intuitive decision-making.

IT research and consulting group Gartner has predicted that by 2026, enterprises that have adopted AI engineering practices to build and manage adaptive AI systems will outperform their peers in the time and the number of processes it takes to operationalize AI models by at least 25 percent.

All of this speaks volumes to the opportunities for AI startups that focus their R&D efforts on adaptive AI.

How BigRio Helps Bring Advanced AI Solutions to the Marketplace

Adaptive AI, indeed, will be one of the next big leaps forward in artificial intelligence and machine learning. At BigRio, we are at the leading edge of helping such advancements in AI get to market.

BigRio prides itself on being a facilitator and incubator for these kinds of revolutionary breakthroughs in AI.

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 world 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 advances such as adaptive AI.

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.

Against the backdrop of growing concerns about the skyrocketing increase in the use of generative AI tools such as ChatGPT, the US government is updating its national AI strategy and is asking the IT industry and the public for input on amending national AI policies.

Policymakers worldwide are hastening to craft strategies and enforce regulations that safeguard public safety while asserting national leadership in this transformative field. However, while many countries are developing policies to regulate AI, the US is a clear leader in AI, hosting most of the largest generative AI companies, and any policy document drawn up by the US is likely to have a substantial impact on the field.

On May 23rd, 2023, the White House released an update outlining the Biden-Harris administration’s latest initiatives in AI policy under the banner “Biden-⁠Harris Administration Takes New Steps to Advance Responsible Artificial Intelligence Research, Development, and Deployment.”

A noteworthy addition to the updated National AI R&D Strategic Plan is an emphasis on a “principled and coordinated approach to international collaboration in AI research.” This shift aligns with President Biden’s broader international diplomacy strategy, representing a push to engage global discussion on data privacy, safety, and AI biases.

While there seems to be renewed emphasis on the “responsible and ethical” deployment of AI, overall, the strategies have not changed much from 2016 and 2019, with the latest 2023 update continuing to uphold the previously outlined strategies:

  • Creating effective methods for human-AI collaboration.
  • Addressing the ethical, legal, and societal implications of AI.
  • Ensuring AI systems’ safety and security.
  • Developing shared public datasets and AI training and testing environments.
  • Establishing standards and benchmarks for AI system evaluation.
  • Understanding the national AI R&D workforce needs.
  • Expanding public-private partnerships to speed up AI advances.

The Biden-Harris administration aims to understand AI models, robotics, and hardware’s potential capabilities and constraints in areas like climate change, agriculture, energy, and healthcare. The plan encourages the development of general-purpose systems capable of functioning in real and simulated environments. On a positive note, the plan mentioned the word “healthcare” fifteen times and had several references to the use of AI in drug discovery and medicine.

The updated National AI R&D Strategic Plan, alongside these additional initiatives, signifies the Biden-Harris Administration’s commitment to responsible AI development. The emphasis on international cooperation, the refinement of existing strategies, and the active solicitation of public input illustrate a balanced, future-oriented approach to AI.

How BigRio Helps Bring Advanced AI Solutions to Improve All Industries

As a company dedicated to facilitating advancement in AI across many industries, and particularly in healthcare, BigRio supports the responsible use of AI and hopes that we can use our expertise in bringing AI responsibly to market to offer some input on the revised national AI strategy.

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 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.

Cybersyn, an AI startup that is only one year out from its launch, has announced it has received a $62.9 million influx of capital from some of the most well-known investors in the world.

Cybersyn, a data startup founded in 2022 by Alex Izydorczyk, recently announced that it raised multi-million in capital from Snowflake Inc., Coatue Management, and Sequoia Capital.

According to a press release announcing the huge influx of cash, Cybersyn is “a company that sells proprietary economic datasets to investors, government agencies, and corporate clients.”

Cybersyn plans to use the funding to expand its small team — it has eight employees — and acquire additional proprietary data for expanded growth. In an interview with Reuters, Izydorczyk touched on the future of the company.

“We’re not trying to just be a data broker,” he said. “We’re trying to actually add value to the data we acquire and combine it.”

Among the big-name investors in the data space is Snowflake Inc., a publicly traded company and provider of cloud-based data warehousing solutions. It provides services such as data warehouse modernization, data exchange, and engineering and data science.

Christian Kleinerman, senior vice president of products at Snowflake, added the following:

“Cybersyn is a company that was built for this era of data sharing and moving with agility. We think of the marketplace as a core part of our offering. If someone is willing to be strategically aligned with us, we’re happy to invest.”

To date, Cybersyn has released both free and paid data sets on the Snowflake Marketplace. These data sets have potential buyers across various industries ranging from consumer goods to pharmaceuticals.

What Does the Scale of This Investment Mean for AI Startups?

Data has been described as “digital gold.” Some of the largest brands in the world, like Apple Inc., Meta Platforms Inc., and Amazon.com, Inc., all make much of their billions in the trillion-dollar data market. Amazon’s cloud storage does billions in revenue per year, supporting some of the largest companies in the world, and Meta has an advertising empire at their fingertips. This is likely why these AI startups like Cybersyn, whose solution traffic in Big Data, are having little trouble securing tens of millions despite being relatively new companies.

How BigRio Helps Bring Investors to AI Startups

There is no shortage of innovative young AI startups such as Cybersyn out there. Often the challenge is getting investors to see their potential and get them the capital they need to take their AI and data solutions to the next level.

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 Big Data 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 the marriage of AI and data 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.

New research shows how a machine-learning technique could provide insight into how to find the patients that would benefit the most from treatment for hypertension.

The study, which came out of UCLA, describes how a machine-learning technique known as “casual forest” could determine the hypertension patients that would benefit the most from treatment rather than assuming that the highest-risk patients require the most clinical attention.

According to the Centers for Disease Control and Prevention (CDC), over 670,000 deaths in the US can be attributed annually to hypertension. In addition, while about 47 percent of US adults have hypertension, only 24 percent of this population has the condition under control.

Traditionally, clinicians treating patients with high blood pressure focus on those with the highest risk of poor outcomes, as the assumption is that they will require the highest level of treatment. The researchers set out to see if they could leverage AI to treat patients based on benefit rather than risk for improved outcomes. They found their solution in a new ML technique, coined “casual forest.”

The study included data from 10,672 participants, all of whom were randomized to systolic blood pressure (SBP) targets of either less than 120 mmHg or less than 140 mmHg from two randomized controlled trials.

The researchers used the casual forest technique to create a prediction model of individualized treatment effects related to the control of SBP and its correlation with reductions in adverse cardiovascular outcomes after three years.

They found that 78.9 percent of individuals with an SBP greater than 130 mmHg achieved benefits from intensive SBP control.

“We found that a substantial number of individuals without hypertension benefited from lowering their blood pressure,” said lead author Kosuke Inoue, MD, Ph.D., who undertook the study while an epidemiology graduate student at the UCLA Fielding School of Public Health and is now an associate professor of social epidemiology at Kyoto University, in a press release. “By applying the causal forest method, we found that treating individuals with high estimated benefits provided better population health outcomes than the traditional high-risk approach.”

Further, the researchers noted that high-benefit approaches could increase the efficacy associated with treatment, potentially being more reliable compared to high-risk approaches.

How BigRio Helps Bring Advanced AI Solutions to Healthcare

As the UCLA researchers have discovered, improving disease detection and making better decisions on the allocation of medical resources is an area where AI and machine learning are making a huge impact in healthcare.

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

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 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.

A specialized machine learning algorithm is helping police in Italy to see what criminals who have been on the run for many years probably look like now.

Human artists have traditionally been employed to “age” fugitives that have been in the wind for years or for persons that have been missing for many years. They would use their artistic skills to alter old photos of the suspect – adding wrinkles, hair loss, and other common aspects of aging. More recently, computer programs have been employed to do that kind of thing, but still, these programs had their limitations because they were based on the same kind of generalizations about how people age.

Just look at any two persons who are in their 60s – one could look like a decrepit old man and the other a distinguished movie star. That is because everyone ages differently, and many factors impact facial aging.

The influence of nature and nurture can make it tricky to accurately predict how someone may look in the future – even for a computer. Law enforcement authorities and forensic scientists are now turning to AI to more accurately “age” people and help police track down criminals who have remained at large for many years.

AI goes way beyond traditional artist’s renderings to “age” suspects or missing children and is even better than standard computerized methods of doing so. AI for adding years to a facial image leverages AI’s deep neural networks and machine learning capabilities.

In this case, the algorithms are trained with, or shown, a large sample of pictures in pairs, showing the same person at two different ages, and then they “learn” to do what is called “age-mapping” – producing an older image when they have been given the young one.

Unlike a traditional computer program that can be used to “age-up” a person or photograph by extrapolating the average transformation of a face in terms of age, AI does that, but is also capable of learning much more detail – for example, whether a certain sort of face will age in a particular way.

The Italian police recently arrested Matteo Messina Denaro, the alleged leader of the Sicilian Mafia, who has been on the run since 1993. To aid in the search, the Carabinieri issued just such an AI-generated aged image to show what he might look like now.

The 60-year-old Messina Denaro was a leading figure in Cosa Nostra, the real-life Sicilian crime syndicate depicted in the Godfather movies.

How BigRio Helps Bring Advanced AI Solutions to All Sorts of Industries

The way that the authorities in Italy are using AI to age fugitives on the run is just one way that law enforcement worldwide is starting to embrace AI technologies. This also speaks to how AI and machine learning are finding uses in applications as varied as fighting cancer to catching criminals. As AI improves, there will hardly be any industry that cannot take advantage of its power.

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

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 world we live in, 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 how AI is and will change our world.

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.

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.

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.

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.

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.

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.