What the Integration of Cognitive Digital Twin Tech and IoT Will Mean for Consumers and Industry

The integration of cognitive digital twin technology with the Internet of Things (IoT) has the potential to revolutionize the marketplace by providing companies with valuable insights into their products and processes.

What is Cognitive Digital Twin Technology?

Cognitive digital twin technology is a virtual model of a physical system that uses data and artificial intelligence (AI) to simulate and predict the behavior of that system. This technology combines data from sensors and other sources with machine learning algorithms to create a digital representation of a physical system.

A cognitive digital twin model can be used to monitor and analyze the behavior of a system in real-time, and it can be used to simulate the behavior of that system under different conditions. By using this technology, companies can gain insights into the performance of their products, optimize their operations, and reduce maintenance costs.

What is the Internet of Things (IoT)?

The Internet of Things (IoT) is a network of physical devices, vehicles, home appliances, and other items that are embedded with sensors, software, and other technologies that enable them to connect and exchange data with other devices and systems over the Internet.

IoT devices can collect data from their environment, such as temperature, humidity, and pressure, and transmit that data to other devices or systems for analysis. By using IoT devices, companies can monitor their products and processes in real-time and gain insights into how they are performing.

The Impact of Integrating Cognitive Digital Twin Technology With IoT?

Cognitive digital twin technology can be integrated with IoT by using data from IoT devices to create a digital twin model of a physical system. IoT devices can provide data about the performance of a product or process, which can be used to create a digital twin model.

The digital twin model can then be used to simulate the behavior of the physical system under different conditions and to predict how the system will behave in the future. By using IoT data to create a digital twin model, companies can gain insights into the performance of their products and processes, and they can optimize their operations to reduce costs and improve efficiency.

There are several benefits to integrating cognitive digital twin technology with IoT, including:

  1. Predictive Maintenance: By using a cognitive digital twin model, companies can predict when maintenance is required on their products or processes, reducing downtime and maintenance costs.
  2. Improved Efficiency: By monitoring the performance of their products and processes in real-time, companies can optimize their operations to improve efficiency and reduce costs.
  3. Reduced Waste: With CDT, companies can reduce waste by identifying areas where resources are being wasted.
  4. Enhanced Product Design: By using a cognitive digital twin model, companies can simulate the behavior of their products under different conditions and make design changes in the earlier stages of R&D to improve performance, reduce costs, and cut time from POC to market.
  5. Improved Customer Experience: By monitoring the performance of their products in real-time, companies can improve the customer experience by identifying and addressing issues before they become major problems.

How the Market is Already Benefiting from Digital Twin and IoT Technologies

Many industries are already benefiting from the kinds of integration between CDT and IoT technologies. Chief among these is the transportation industry.

Cognitive digital twin technologies coupled with IoT are already proving invaluable for predictive maintenance of high-value military vehicles, airplanes, ships, and even passenger cars. For example, 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, as well as IoT, 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 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.

What Is Adaptive AI and What Could it Mean for AI Startups?

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.

Well Known UK Biotech Company Leverages Open AI Technology for Drug Discovery

UK Biotech innovator e-Therapeutics says it intends to integrate Open AI’s GPT technology into its efforts to develop novel RNAi medicines.

The company has long been at the forefront of computational drug discovery; now, chief executive Ali Mortazavi has signaled e-Therapeutics’ intent to use Open AI’s GPT large language model (LLM) to further automate the quest to find new drug targets, notably in the area of gene silencing.

According to a company press release, specifically, he wants to transform and leverage its current technology HepNet using artificial intelligence.

“By placing LLMs at the core of our computation and harnessing GPT-4’s capabilities, we can now create specialized LLM ‘agents’ which will transform HepNet into a dynamic knowledge resource,” Mortazavi said in the release.

“GPT-4 and LLM integration will provide a unifying framework from which to drive every aspect of our pipeline and position e-Therapeutics as a global leader in hepatocyte biology and related diseases.

“Our long-term vision is to fully automate the preclinical drug discovery process, using GPT-4 and LLMs to access real-time information and interface with external applications, ultimately accelerating the development of life-saving treatments.

In the same press release, e-Therapeutics said it had a busy year, having made significant strides in its RNAi strategy, developing an expanding in-house pipeline of early candidates using the HepNet computational platform. The company said it is actively addressing high-need medical areas, with a focus on cardiometabolic diseases.

Citadel and AI for Drug Discovery

Similar to the way that e-Therapeutics is using Open AI’s GPT LLM to better determine RNAi drug targets, 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.

Our platform provides an alternative framework for early drug discovery by leveraging our access to DNA-Encoded Libraries (DELs) to rapidly and cost-effectively generate readouts on tens of millions of small molecules that are used to train custom, project-specific AI models.

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.

The University Of Southern California Launches $1 Billion-plus Initiative to Advance Quantum Computing

The University of Southern California (USC) has announced that it has launched the single largest comprehensive academic initiative in the university’s history — Frontiers of Computing. The initiative integrates computing throughout education and research to enhance digital literacy for all students as the university aims to hold its lead as a top provider of tech professionals.

USC President Carol L. Folt says that quantum computing and AI will be a big part of the $1 billion-plus initiative. In addition to a focus on AI and machine learning, Folt said that “data science, augmented and virtual reality, robotics, gaming, and blockchain” will all be part of the initiative.

“I want every student who comes through our programs, whether they are in science, business, the humanities, or the arts, to have a solid grounding in technology and the ethics of the work that they do,” Folt said. “We will integrate digital literacy across disciplines to create responsible leaders for the workforce of the future.”

Seeded with a $260 million gift from the Lord Foundation of California, USC Frontiers of Computing encompasses a multipronged effort to push the boundaries of computing into a new era.

USC leaders began developing Frontiers of Computing three years ago, before the recent rise of artificial intelligence and generative AI.

USC already is the leading provider of tech talent for the nation. More than 1,300 students per year graduate with bachelor’s, master’s, and PhDs in computer science.

“We all know the world is changing very fast right now,” Folt said. “We need to take that momentum of change — and couple it with USC’s history of innovation — to create what has never been done before. And we’re going to do it.”

How Big Rio Can Help

Much like the USC initiative, one of BigRio’s ultimate goals is to help foster the next generation of IT innovators with our focus on the support of startups in AI and quantum computing.

Quantum computing is still very much an emerging technology with large-scale and practical applications still a way off. However, the technology is steadily graduating from the lab and heading for the marketplace. In 2019, Google announced that it had achieved “quantum supremacy,” IBM has committed to doubling the power of its quantum computers every year, and numerous other companies and academic institutions are investing billions toward making quantum computing a commercial reality.

Quantum computing will take artificial intelligence and machine learning to the next level. For example, quantum computing’s ability to process and manipulate vast amounts of data simultaneously can enhance data processing capabilities in AI systems. This is particularly beneficial for handling big data applications, where quantum computers can provide faster data analysis, more efficient data clustering, and improved data compression techniques.

The marriage between the two is an area to pay very close attention to for startups as well as for where Big Tech will be going over the next five to ten years, and wherever this road can take us, BigRio will be there to help get startups and society as a whole to its ultimate destination.

You can read much more about how quantum computing will redefine AI and machine learning in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI is being used to improve healthcare and society as a whole.

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.

The US Government Calls for Updates to Its National AI Policies

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.

Startup Reveals Unprecedented Quantum Computer Chip!

Quantum computer startup SEEQC has just unveiled a quantum digital chip that can operate at super-cold temperatures.

The New York-based startup said in a recent press release that it has developed a digital chip that can operate at temperatures colder than outer space so it can be used with quantum processors that are often in cryogenic chambers.

Quantum computers, which leverage the properties of quantum physics, can complete some calculations millions of times faster than conventional computers. This makes them essential to the ongoing evolution of artificial intelligence.

One challenge is that quantum processors, unlike conventional computer chips, often need to be stored at very cold temperatures near zero Kelvin, or -273.15 Celsius. It has been very hard to find chips that can operate in that kind of environment and process the qubits that need to be in close proximity to the main processors in order for the “quantum entanglements” upon which quantum computing relies to work.

Before the announcement by SEEQC, in most quantum applications, hard wires connect the quantum processor in the freezing chamber to classical computers nearby but at room temperature, but the temperature change can slow the speed and cause other issues.

SEEQC seems to have solved that issue by developing a chip that can operate in the super-cold environment. The first such chip, which it unveiled recently, resides directly under the quantum processor and controls the qubits and reads out the results.

At least two other chips still under development will be in a slightly warmer part of the cryogenic chamber. These could further process the information needed for quantum computing.

The technology could make it easier to build more powerful quantum computers as each cryogenic chamber would be able to support a larger number of qubits, said John Levy, co-founder, and CEO of SEEQC. Today’s superconducting quantum computers have hundreds of qubits, but some estimate thousands or even a million could be needed to create a quantum computer to run next-gen AI algorithms.

The SEEQC digital chips are made at SEEQC’s fabrication facility in Elmsford using silicon wafers but do not use transistors, Levy said.

SEEQC was founded in 2018 and has raised a total of $30 million from investors, including Merck’s M Ventures and LG Tech Ventures.

How is This Discovery Relevant to AI?

Quantum computing will take AI and machine learning to the next level. The marriage between the two is an area to pay very close attention to for startups such as SEEQC as well as for where Big Tech will be going over the next five to ten years.

Consider this. We are at the limits of the data processing power of traditional computers, and the data just keeps growing. It has been estimated that we produce 2.5 exabytes (one exabyte = 1 billion GB ) of data every day. That’s equivalent to 250,000 Libraries of Congress or the content of five million laptops!

In order to handle this ever-increasing volume of data, there’s a race from the biggest leaders in the industry to be the first to launch a practical quantum computer. Only a quantum computer will be powerful enough to process all of this Big Data and be able to solve increasingly complex problems in order for AI to reach its full potential.

How Big Rio Can Help

Quantum computing is still very much an emerging technology with large-scale and practical applications still a ways off. However, the technology is steadily graduating from the lab and heading for the marketplace. In 2019, Google announced that it had achieved “quantum supremacy,” IBM has committed to doubling the power of its quantum computers every year, and numerous other companies and academic institutions are investing billions toward making quantum computing a commercial reality.

Quantum computing algorithms will allow us to enhance what’s already possible with machine learning and AI. BigRio will be there to help get startups and society as a whole to AI’s ultimate destination.

You can read much more about how quantum computing will redefine AI and machine learning in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI is being used to improve healthcare and society as a whole.

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.

Oracle and John Snow Collaborate With FDA to Enhance AI Tools for Drug Discovery

The FDA’s Sentinel Innovation Center has chosen Oracle’s Cerner Enviza and John Snow Labs to help develop innovative AI tools for drug safety and real-world evidence studies. The two AI innovators are now helping support the federal agency’s drug safety Sentinel Initiative. By developing AI tools aimed at extracting critical information from clinical notes within electronic health records (EHR), Oracle and John Snow will aid the FDA in better understanding the effects of medicines on large populations.

Specifically, while looking at the asthma drug montelukast and its possibility of mental health side effects, this two-year project will demonstrate how the use of AI and machine learning along with natural language processing (NLP) technology to analyze “unstructured data” such as handwritten notes can help fill gaps in knowledge.

Cerner Enviza leverages decades of life sciences expertise spanning commercial, real-world, clinical, and regulatory research. This includes working with a broad range of Oracle provider networks to help accelerate the discovery, development, and deployment of health insights and therapies. John Snow Labs is known for its AI and NLP in healthcare and is the developer of the Spark NLP library. Together, Cerner Enviza and John Snow Labs will develop a new methodology to enhance computerized queries, or phenotyping, of digital patient data and clinical notes to support pharmacoepidemiology.

Cerner Enviza, who will lead the team, was chosen by the Sentinel Innovation Center, which is headed by Mass General Brigham and Harvard Pilgrim Health Care Institute.

“Development and evaluation of tools that can enhance our ability to utilize unstructured EHR data is a key strategic priority for the Sentinel Innovation Center. We look forward to this new relationship and exciting initiative led by Cerner Enviza,” said Rishi Desai, Ph.D., Mass General Brigham executive leadership team member, Sentinel Innovation Center.

Traditional manual methods for analyzing clinician notes can often be a bottleneck for fully understanding the symptoms and outcomes that patients experience at the population level. However, advances in AI offer a scalable and transportable NLP processes.

“This is an incredible opportunity to work with these exceptional leaders to use Oracle’s de-identified EHR data to help transform unstructured clinical notes into validated and useable data for physicians and researchers,” said Mike Kelly, global head Cerner Enviza. “Connected technologies and unified data can accelerate innovation and, in turn, help providers realize better recommendations and outcomes for their patients.”

The truth is, particularly if you are researching something novel like new drug targets or emerging diseases like COVID-19, the vast majority of biomedical information out there is in unstructured formats that are in their raw form, such as doctor’s notes, hospital admission records, coroner’s reports, patent applications and so and so on. AI, when coupled with these kinds of NLP algorithms, offers a powerful solution to this problem. With NLP, AI algorithms are being written that can analyze any kind of document and other datasets and identify biologically relevant text elements such as the names of genes, proteins, drugs, clinical manifestations of a particular disease, and anything else relevant to a given drug discovery team’s target. NLP is one of the most powerful tools leveraged by AI for drug discovery, and this announcement by Sentinel Innovation Center shows that the FDA recognizes this.

This particular collaboration project, known as the Multi-source Observational Safety Study for Advanced Information Classification Using NLP (MOSAIC-NLP), is also supported by the participation of Children’s Hospital of Orange County, National Jewish Health, and Kaiser Permanente Washington Health Research Institute who, will provide clinical expertise and consulting.

Citadel and AI for Drug Discovery

Just as the FDA’s collaboration with Oracle and John Snow is targeted at leveraging AI to enhance Pharma research and improve drug discovery, 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 a 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.

One-Year-Old AI Startup Secures Over 60 Million From Investors!

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.

IBM And EY Form Strategic Alliance to Expand Into Quantum Computing

The EY organization and IBM recently announced that EY Global Services Limited will be joining the IBM Quantum Network, further enabling EY teams to explore solutions with IBM that could help resolve some of today’s most complex business and global challenges.

The EY organization established its own Global Quantum Lab last year with a mission to “harness quantum value in the domains of trust, transformation, and sustainability.” Under the new alliance, EY will gain access to IBM’s fleet of quantum computers over the cloud and will become part of the IBM Quantum Network’s community of organizations working to advance quantum computing.

Quantum computing is a rapidly emerging technology that harnesses the laws of quantum mechanics to solve problems that even today’s most powerful supercomputers cannot solve. EY teams will leverage their access to the world’s largest fleet of quantum computers to explore solutions to enterprise challenges across finance, oil and gas, healthcare, and government.

Leveraging IBM’s quantum technology, EY teams plan to conduct leading-class research to uncover transformative use cases, including but not limited to the reduction of CO2 emissions from classical computing, the improvement of safety and accuracy of self-driving cars, and most critically, integrate quantum benefits into organizations’ mainstream systems for data processing and enterprise decision making.

In a press release announcing the EY/IBM alliance Andy Baldwin, EY Global Managing Partner, said, “Quantum, in terms of importance to business, society, and the EY organization, is akin to what AI represented years ago. This alliance puts the EY organization at the forefront of technology. As we invest in this level of quantum computing access, we accelerate our own position and depth of knowledge and capabilities in this space and deepen our rich relationship with our IBM alliance teams.”

Jay Gambetta, Vice President IBM Quantum, added, “IBM’s vision is to deliver useful quantum computing to the world. We value partners like the EY organization that can introduce emerging technology to a wide ecosystem of public and private industry. This will help EY facilitate the exploration of quantum computing’s potential for use cases that matter in their industry.”

How is This Alliance Relevant to AI?

If the is any limit at all on what AI can achieve to improve healthcare, education, research, the economy, and society as a whole, it is the processing power of conventional computers. The marriage of AI and quantum computing will help AI fulfill all of its potential promise, and alliances like this one will help get us there.

Membership in the IBM Quantum Network is part of a broader effort by the EY organization to invest and develop robust capabilities in emerging technologies, which already include artificial intelligence.

How Big Rio Can Help

Quantum computing is still very much an emerging technology with large-scale and practical applications still a way off. However, the technology is steadily graduating from the lab and heading for the marketplace. In 2019, Google announced that it had achieved “quantum supremacy,” IBM, as can be seen in this venture with EY, is fulfilling on its commitment to doubling the power of its quantum computers every year, and numerous other companies and academic institutions are investing billions toward making quantum computing a commercial reality.

Quantum computing will take artificial intelligence and machine learning to the next level. The symbiosis between the two is an area to pay very close attention to for startups as well as for where Big Tech will be going over the next five to ten years, and where ever this road can take use BigRio will be there to help get startups and society as a whole to its ultimate destination.

You can read much more about how quantum computing will redefine AI and machine learning in my new book Quantum Care: A Deep Dive into AI for Health Delivery and Research. It’s a comprehensive look at how AI is being used to improve healthcare and society as a whole. There is an entire chapter devoted to quantum computing and 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.

How Machine Learning Can Help Improve Blood Pressure Treatment

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.