Beyond Limits is a pioneering AI company with a unique legacy from the US space program. The company is transforming proven technologies from Caltech and NASA’s Jet Propulsion Lab into advanced AI solutions for forward-looking companies on earth. Beyond Limits delivers AI software capable of tackling complex industrial and enterprise challenges for leading global customers to transform their businesses and industrial operations in areas such as healthcare, oil and gas, finance, transportation and logistics.
Breakthrough cognitive technology goes beyond conventional AI, blending deep learning and machine learning tools together with symbolic AI that emulates human intuition to produce our cognitive intelligence.
AJ Abdallat is CEO of Beyond Limits. AJ Abdallat worked with HP on key NASA/JPL projects. One of the key projects was a collaboration with NASA/JPL Center for Space Microelectronics Technology (CSMT) and Caltech Center for Advanced Computing Research (CACR). The collaboration which Abdallat managed led to the installation of a 256-processor Exemplar supercomputer with a peak performance of one teraflop (one million computations per second). The Exemplar supercomputer at the time was the fastest supercomputer in the world.
In 1998 Caltech hired Dr. David Baltimore as president. Dr. Baltimore vision was to make technology commercialization at Caltech/JPL the hallmark of his administration. In 1998 AJ Abdallat and Dr. Carl Kukkonen (CSMT Executive Director), left to launch a Caltech/JPL startup to commercialize JPL technologies with the support of Dr. Baltimore. In 1999 Dr. Mark James and other JPL scientists joined Abdallat in the Caltech/JPL startup and efforts to commercialize JPL smart sensors and AI technologies. Between 1998 and 2012, Abdallat founded and launched several spin-off companies from Caltech/JPL in the fields of AI, smart sensors, gas sensing, finance and homeland security.
Since 2012, Abdallat has been focused on AI and cognitive reasoning systems from NASA/JPL. In 2014 Abdallat launched Beyond Limits, a NASA/JPL AI and Cognitive Computing startup. He secured Series A investment in 2014 and in early in 2017 closed Series B funding from British Petroleum (BP). Abdallat is currently working on securing Series C investment to accelerate delivery of Industrial-grade AI.
Beyond Limits delivers AI software capable of tackling complex industrial and enterprise challenges for leading global customers to transform their businesses and industrial operations.
The advanced intelligence solutions developed by Beyond Limits magnify human talent, enabling people to apply their attention, experience, and their passions to solving problems that truly matter. Many pioneering JPL scientists now work at Beyond Limits, building solutions for companies in down-to-earth industries, such as oil and gas, healthcare, finance, transportation and logistics.
With more than 40 technologies developed for NASA’s famed Jet Propulsion Laboratory (JPL) Beyond Limits offers cognitive AI and reasoning systems available for the first time for commercial use. Beyond Limits delivers cognitive solutions with the resilience, reasoning, and autonomy required by the harsh environment -of space to improve the performance of industrial and enterprise systems on Earth.
Powered by Beyond Limits innovations, the company’s technology is an evolutionary leap beyond conventional AI to a human-like ability to perceive, understand, correlate, learn, teach, reason and solve problems faster than existing AI solutions.
Who are your competitors?
Beyond Limits has no direct competitors developing AI solutions for healthcare. Competitors may include Troops, SparkCognition, Vicarious and Butter.ai; however, Beyond Limits provides advanced intelligence solutions that go far beyond conventional AI. Our cognitive computing technology mimics human thought processes and provides autonomous reasoning to aid human-like decision-making.
How your company differentiates itself from the competition and what differentiates Beyond Limits?
Our breakthrough cognitive technology goes beyond conventional AI, blending deep learning and machine learning tools together with symbolic AI that emulates human intuition to produce our cognitive intelligence. Unlike “black box” machine learning solutions that cannot explain their results, a Beyond Limits system provides clear explanations of its cognitive reasoning in transparent, evidence-based audit trails. Our systems are both educated and trained, which greatly reduces the amount of data that is needed to make them intelligent. This means we can solve problems that deep learning approaches alone cannot do.
Our goal is to create automated solutions with human-like reasoning powers that magnify the capabilities of people. We pride ourselves as the only AI company that provides solutions for problems that cannot be solved using conventional AI approaches.
Beyond Limits goes beyond conventional AI by delivering advanced intelligence solutions that have been tested and proven in the harshest, most extreme conditions in space and the most demanding conditions here on Earth. We deliver cognitive solutions with the resilience, reasoning, and autonomy required by the massive scale and unimaginable distances of interplanetary space to improve the performance of industrial and enterprise systems on Earth.
Dental health has always been an important aspect of your overall well-being. While most people may perceive dentistry as a means to improve one’s aesthetic, this is but an extra perk of visiting your dentist regularly. There are a wide variety of diseases and they all function the same way —through infection.
When a pathogen is able to gain ingress into your body that is called an infection. And one of the means of ingress are the teeth. A tooth cavity or an abscess are both dangerous in the sense that they are infections waiting to happen.
In the digital age, daily life is enhanced by the technology that we have. For one instance, traditional X-ray images had to be printed on a metal sheet and processed the way you would a camera film. Today, thanks to digital photography, the image is instantly projected onto monitors and saved to a database. There’s no longer the waiting phase. It goes straight to the diagnosis phase.
In previous iterations of the technology, the way that orthodontic diagnostics were performed was that dentists had to make a temporary mold of the patient’s crown (to be replaced) while the permanent mold of the crown would be made back at the lab.
Because of digital photography and 3D printing, dentists simply have to scan the crown that they intend to replace and add it to the database. The computer then simply prints out the replacement crown on the spot.
And while this technology seems impressive, there has been one piece of tech that has been on everyone’s lips for the past few months — artificial intelligence.
It first became publicly known when Google introduced it with its new line of Pixel phones. The artificial intelligence found in these phones was able to significantly improve the photo quality taken by the phone camera. A plethora of phone manufacturers, such as Asus, Huawei, and Oppo, followed suit thereafter.
What most people don’t know is that in the medical field, AI is currently being used to make the process of diagnosis more efficient and more accurate. IBM brought its Watson platform into the picture and it is currently used to help doctors make the best diagnosis and recommend treatment based on the patient’s medical history.
The software is even being further developed for it to be able to schedule medical procedures based on its estimated procedure durations. What this does is that it helps improve the efficiency at which hospitals operate by ensuring that time is used in the best way possible. So, this translates to an overall higher number of patients treated.
The same application can be brought into dentistry. A program known as VisualDX allows dentists and doctors alike to input images onto a computer. The computer is then able to produce a full list of all possible diagnoses.
Dthera digitized reminiscence therapy to enable people with dementia to see and hear their family and friends share familiar stories with them. Our first product, ReminX, is an artificial intelligence-powered consumer health product designed to improve the quality of life in individuals suffering from neurodegenerative diseases, such as dementia and Alzheimer’s disease, as well as seniors experiencing social isolation.
Edward Cox, CEO, and David Keene, CTO, both had an upbringing similar to millions of families around the world – they grew up with a grandparent in the home. The special relationships with their grandparents included time hearing stories from the Greatest Generation – from growing up in humble beginnings to traveling across continents for war, peace, work, love and family. At the time, they didn’t realize they were engaging in reminiscence therapy, but did realize the impact social isolation can have on the elderly, especially those suffering from dementia or Alzheimer’s disease. With ReminX, their goal is to improve the quality-of-life for millions of elderly suffering from dementia by digitizing and proactively advocating reminiscence therapy and making it available to all.
Researchers concluded that ReminX holds great promise for bringing reminiscence therapy to people suffering from dementia. Dthera is exploring additional collaborations with non-profit organizations, medical centers and elder care facilities. ReminX is available for purchase by families, caregivers and administrators at senior assistant living centers through direct response marketing. Complete this form to find out where to purchase ReminiX.
Our target market is the 46.8 million people worldwide living with dementia from Alzheimer’s, as well as from other neurodegenerative conditions. In the US alone, the Alzheimer Association estimated 5.7 million Americans have the disease and the cost to care for Alzheimer’s and other dementias will reach more than $277 billion in 2018. Dthera is focused on creating and delivering digital therapeutics that bring medically- validated treatments, such as reminiscence therapy, to patients suffering from dementia and severe forms of social isolation, to ease symptoms and create a better quality-of-life for them and their caregivers.
Who are your competitors?
In the digital therapeutics space, we are one of the only companies developing products for the elder care market, including dementia patients, but also people suffering from extreme social isolation.
As far as products to reach this group of the elderly, other tablets, social media or photo sharing sites could seem to be competitors with ReminX, but these products are not actually suited to this patient market. Apps and most tablets are too complicated for patients suffering from dementia to use, and none of these vehicles have active involvement of family members in the story-creation process designed into them. ReminX proprietary software includes an AI-interface app that engages family members to upload content and then optimizes it, and proprietary facial recognition software in the tablet provides feedback on what’s most effective.
Dthera designed ReminX with the elderly, their caregivers and families in mind. It automatically creates elegant documentary-like videos and plays stories on demand. There is no interface to learn, simply picking up the tablet starts stories and setting it down stops them.
Big data has arrived, and in healthcare, it has landed on our desks with a resounding thud. The challenge ahead lies in discerning how to analyze information and use it to effectively improve patient outcomes, costs and efficiencies.
Many of us are already influenced by machine learning and artificial intelligence (AI). For example, if buying hiking boots online, items of a similar nature also appear as suggested purchases, like bug spray or sunscreen. The data analytics behind those recommendations includes a wealth of information about the user, including demographics, such as age, gender, education and income level, as well as location and other factors that influence buying decisions. It will only be a matter of time until we are able to apply the same principles to healthcare data.
Imagine a doctor who can review operational and clinical data in real time for a patient who had knee replacement surgery. After the patient goes home, she is given a Fitbit to monitor her step count. If her steps trend downward, it is probably time for someone to intervene because she is potentially in pain or not ambulating correctly. That same physician could also see where she has received care, the cost of the care, and who performed the surgery. Then, the physician could compare her progress against others with similar demographic and health backgrounds by using machine learning and streaming analytics that not only gather relevant data across the entire care continuum—from hospital to rehab facility to home—but draw inferences from that information in real time to truly influence cost and care outcomes. In addition, if the patient had three MRIs that cost $2,000 each and someone with similar demographics and health conditions had one MRI that cost $500—caregivers can explore why that happened and work toward more uniformity.
This idea is inspiring, but a more practical look can be taken for how AI can support the business operations of healthcare as an achievable first step, along with connecting that operational data with remote care, device data and patient EHRs. Here are next steps for creating efficiencies with the power of AI and interoperability:
Step 1: Unlock Human Potential
As a recent Advisory Board report states, “AI works best when paired with humans.” The goal is to use this technology to create efficiencies across the care continuum that not only help staff in their roles, but that free clinicians, caregivers and office staff to focus on more valued activities. AI can help augment and automate human tasks and functions where appropriate, and sooner rather than later it may be able to offer advice, ultimately allowing caregivers to focus entirely on patient care.
Step 2: Optimize the Supply Chain
AI can quickly answer employee queries, buy supply, such as bandages from a certain supplier, and can also track unused supplies to minimize excess inventory. In addition, AI can help alleviate the amount of time—and frustration—nursing and clinical staff spend searching for supplies by not only providing location, but automating future order and delivery.
Step 3: Enhance and Expand Employee Self-Service
For those healthcare employees without regular access to a computer, such as lab technicians, AI can quickly and accurately empower cross-functional self-service. All employees need to do is ask for answers about anything, from paid time off (PTO) balances to company holidays.
Step 3: Automate Financial Processes
AI can augment the payment process, detecting payment, vendor and invoice patterns, and suggesting automating payments for a specific invoice that is approved 99 percent of the time.
The Da Vinci Surgical System (as it’s more properly called) has been one of the most innovative and complicated medical technologies to have been introduced in the past 20 years. The surgical system was the first of its kind to become commercially available in the United States. Since its commercial debut in 2000, there have been 1,700 Da Vinci Surgical Systems installed in hospitals worldwide.
What Does It Do?
These robots essentially make the skills of a physician available for use regardless of distance. As of writing, there have been around 775,000 successful procedures that have been performed with the use of this hi-tech surgical system. In fact, robot-assisted surgery is the most preferred option when it comes to performing prostate cancer-related procedures. Three out of four prostate cancer surgeries are performed with the help of the Da Vinci Medical Robot.
Now, as humans, we are always looking for new ways to solve problems. One problem that the system seeks to solve is the distance between a physician and his patient. Because the robot is able to mimic the precision of the operating physician, the surgeon is, in essence, able to transfer his or her skill and precision where it is most needed — which is often a surgery table that’s hundreds of miles away.
Potential Improvements via AI
There’s a current trend that involves artificial intelligence. It started off with applications in smartphone cameras, and now it’s as viral as a Dengue outbreak. And it should be.
Artificial intelligence is an attempt to help minimize, or even eliminate, the risk of human error (because, let’s face it, no matter how skilled you may be, the best you can do is to minimize the margin of error).
Artificial Intelligence might even allow surgical robots to function autonomously, as long as these robots are given sufficient data to perform these complicated procedures. And that doesn’t seem to be very far off either, as Google and Johnson & Johnson have recently begun working on new surgical robots.
The thought of an autonomous surgical robot will definitely frighten a lot of people, but so has the concept of flying vehicles; now, look around and see how so many people fly on a daily basis.
It’s a fact that all machines are prone to failure. While it was established earlier that these machines were built to minimize the risk of human error, we should never forget that while these machines are designed to be error-free, many things could go wrong during manufacturing and assembly.
There are also risks that involve technology where all sorts of devices are prone to hacking. What if these robots were to be compromised during the crucial moments of a procedure?
The healthcare sector is hopeful for the future, as innovations in the IT sector will continue to provide opportunities to improve the deliverability of crucial services. One thing’s for sure, more and more companies will continue to realize just how big of an impact HITs can bring, and the situation alone is urging companies to invest more on new software and technologies — even as these innovations are still in the works.
Several key innovations in this area, such as 3D printing and artificial organs, are still being tested and developed. It would take time before these breakthroughs can penetrate the market. What’s important, meanwhile, is the fact that AI will continue to drive technological adoption in the healthcare industry.
As technological tools have become increasingly sophisticated, the demands for these tools are also becoming more complex. Still, organizations are in the right when they invest a huge bulk of their resources in AI-based solutions. Apparently, they know all too well that these products are capable of improving the delivery of care and other services.
They help healthcare providers to thrive
End users will certainly reap the benefits that AI entails. If anything, effective software and IT products are being sought by businesses that want to get the most out of their investments. Analytics plays an important role in maintaining the efficiency of an organization, whether it involves using organizational psychology to retain productive employees or managing the workflow of hospital staff.
One thing that makes HITs relevant is the fact that they lighten the workload and that they simplify complex processes. With the use of AI, healthcare organizations can accelerate their services without compromising quality. This would allow healthcare managers to focus on exploring ideas for expanding their bottom lines.
They help in patient outreach
A key trend in HIT is the rise of AI virtual assistants. Doctors normally have their hands full engaging patients with unique histories — considering this, there will always be room for error. This technology can help by automating the way they handle individual cases.
In this case, using automated VAs to organize patient data and notify patients about their appointment schedules and regular medication can ultimately lessen the amount of work doctors will have to handle. As VAs are being developed to become more intelligent and predictive, these innovations will certainly provide ample opportunities to forge stronger patient links.
They make accuracy central
Human error is natural. We are basically prone to make mistakes. But in the healthcare industry, errors can sometimes cost you money or, even worse, a patient’s life.
Indeed, new technologies in the field of diagnostics are helping organizations to identify and analyze diseases more accurately. This, in turn, can help doctors to make the proper prescriptions and suggest the right treatment plans.
In recent years, the public sector has become increasingly aware of the multifaceted potential of big data. These days, government agencies around the world collect vast amounts of data from people’s activities, behaviors, and interactions—a virtual treasure trove of information that the public sector can utilize and turn into actionable insights, and later, into actual solutions.
The big challenge, however, is that government agencies are falling under more and more pressure to find relevant insights from complex data while relying on limited resources and technologies with inadequate capabilities. And with the sheer size of data being generated nowadays, it’s becoming more difficult to extract meaning from what the data hides beyond their colossal façade.
Thankfully, there is one critical technology that is redefining the way public sector agencies study and utilize data, and this is artificial intelligence. Today, artificial intelligence solutions that make use of technologies like machine learning and topological data analysis can automatically process big data and discover patterns and anomalies no matter how complex and seemingly disjointed these different points of data are.
Precisely because of these advantages, artificial intelligence solutions are now being used by numerous public sector agencies and institutions around the world. In this article, we’ll fill you in on the basics of three important areas of the public sector in which AI is currently making waves.
The financial industry is one of the biggest producers and exchangers of data, and as such, it stands to benefit immensely from artificial intelligence technologies. Every day, government-owned banks and other financial institutions buy, borrow, and trade currencies and financial products, generating massive amounts of data from customers, partners, and other stakeholders.
In many jurisdictions over the world, value-based care is being adopted as an alternative healthcare model that focuses more on accountability, and on the type and quality of service provided to patients instead of the volume of care provided. With this increased emphasis on value, government-aligned health providers and insurance systems have begun using artificial intelligence software in order to become more agile and proficient at managing the risks of patient pools.
This way, even with the immensity and complexity of patient data, public sector providers and health payers are able to better understand clinical variations, as well as automatically predict individual and subpopulation risk and health condition trajectories. Through insights gained from these data, clinicians and other personnel across the healthcare spectrum can then better determine the best and most affordable courses of care, in addition to being able to confidently recommend the most appropriate health programs for their governments to implement.
Artificial intelligence is a topic that should interest us all, as it changes the world with every second. And the healthcare system is one of the areas that AI has already started to revolutionize. These are the main ways in which that is happening.
Due to the introduction of personalized diagnosis and precision medicine, now doctors can treat a patient’s condition, by taking into account his/her background, as opposed to merely treating the disease. This is accomplished by using proteomics, which is a type of DNA mapping, as well as advanced AI machine learning.
Killing Occam’s Razor
Occam’s Razor is also known as the Law of Parsimony, and it refers to providing a range of solutions to a given problem. Also, according to this principle, the simplest solution is, most of the time, the correct one. Considering that both machine learning and AI doesn’t have the human assumption element, their capacity of reading and analyzing amounts of data can significantly increase the accuracy of the diagnosis.
Accordingly, this can be really helpful in diagnosing elderly patients, in particular, as they are more likely to suffer from various diseases at the same time.
Google Can Spot Eye Disease
DeepMind is a Google-owned AI company that has come up with a way of diagnosing eye disease. After assessing and attentively analyzing the medical records of a significant number of patients, it has created machine learning technology that should help doctors diagnose eye illness earlier. This merely outlines that, even though AI is innovating almost every field, it still relies on human help.
Automated Cancer Treatment
It appears that AI can also play an important role in treating cancer, which affects more and more people. Accordingly, the CareEdit tool can be utilized by oncologists for crating practice guidelines. To be more specific, the tool analyzes considerable amounts of data such as past treatment regimens, aiming at comprising a clinical decision support system that should help physicians treat each patient. This can significantly enhance the rate of survival, while cutting down the costs associated with the treatments.
Virtual Health Assistant
Interestingly enough, at the time being, there are apps that carry the roles of personal health coaches. This functions the same way as a customer service representative at a call center. What is more, the digital assistant can do as much as take notes, ask questions, even provide specific advice while streaming the information to the healthcare provider. This has the role of simplifying the process.
Vyasa Analytics provides a highly scalable deep learning platform for organizational data, enabling conceptual querying and collaborative analytics to help inform key decisions derived from your most valuable information assets.
Vyasa Analytics provides deep learning software and analytics for life sciences and healthcare organizations
Dr. Christopher Bouton earned his Ph.D. in molecular neurobiology from Johns Hopkins University and sold his first big data software company, Entagen, to Thompson Reuters in 2013. Living in India for four years as a boy, he developed a great respect for Vyasa – an important Hindu figure, storyteller and compiler of information – and believes that AI approaches will help us better compile and gain insights from our data systems. In 2016, he founded Vyasa Analytics to apply AI in life sciences and healthcare.
Vyasa engages with life sciences and healthcare organizations to educate the industry about deep learning technologies, including speaking alongside executives at conferences and events. Dr. Bouton is also a frequent contributor and commentator to industry publications.
In 2016, the pharmaceutical industry spent some $157 billion on research and development. This figure is set to increase to more than $180 billion by 2022. The healthcare analytics market was $8.69 billion by 2016 and is estimated to reach $33.38 billion by 2022.
Vyasa is positioned to capture hundreds of millions of dollars in these markets by allowing organizations to conduct analytics on data relevant to their research. Other analytics companies in the space experiencing rapid growth include Lattice.io (acquired by Apple for $200 million), BenevolentAI (valued at $1.7 billion) and Exscientia (recent deals with GSK for $43 million and Sanofi for $273 million).
Who are your competitors?
While there are many deep learning companies, Vyasa is the only one applying deep learning to life sciences and healthcare specifically.
How your company differentiates itself from the competition?
Focusing in the life sciences and healthcare verticals is a key differentiator for Vyasa. In partnership with life sciences and healthcare organizations, we build software to help design better therapeutics, free up researchers for higher-level thinking and solve problems that matter for humanity.
Business model: Vyasa has a B2B business model. Every project is a blend of software licensing and services, provided to the life sciences or healthcare organization to advance their research goals. We are projecting upwards of $3 million in revenue in 2018.
As we launch into 2018, questions remain about the healthcare policy environment and how it can impact many healthcare initiatives. As Yogi Berra said, “It’s difficult to make predictions – especially about the future.” I feel confident, however, about some fundamental trends in the healthcare landscape. These include a steady shift toward value-based care, an increased focus on data and analytics as a core enabler for digital transformation, and the all-consuming focus on the patient experience.
Here are my four key predictions for the healthcare IT trends that will transform the industry in 2018:
Patient Satisfaction Takes Center Stage
The era of healthcare consumerism is here. Patients are bearing increasing financial responsibility for healthcare costs, and seek improved experiences as a part of the value-for-money equation. In response, providers are taking a 360-degree view of patients, employing better analytics to leverage patient data such as demographic information, lifestyles and individual preferences, to personalize interactions and treatment.
Artificial Intelligence (AI) Becomes Entrenched in Clinical Settings
Despite the overuse of the term AI to describe many types of technology-enabled solutions, the adoption of AI has been steadily gaining ground in a wide range of settings. Deep learning algorithms will increasingly be used in clinical settings to support medical diagnosis and treatment decisions, predict the likelihood of patient re-admissions and help providers better leverage the data that has been accumulating in electronic health records. According to the 2017 Internet Trends Report by venture capital firm Kleiner Perkins, medical knowledge is doubling every three years, and the average hospital is generating more than 40 petabytes of data every year.
While all this accumulated information empowers more informed physicians, the growing range of data and knowledge sources creates a challenge as well, since physicians and clinicians must manage and stay on top of this information on specific conditions, especially in fields such as oncology. AI technologies are enabling time-constrained and overworked physicians to make sense of the vast amounts of data, helping them uncover hidden insights and supporting their medical diagnoses and decisions with timely and relevant input at the point of care.
Open Source Finally Takes Hold
Healthcare organizations have been conservative when it comes to open source technologies, largely due to concerns about data security and privacy. With the growing adoption of cloud-enabled solutions and a gradual shift of enterprise IT workloads to the cloud, they no longer have to worry about risks to the IT environment and can rely on mature cloud service providers, such as Amazon Web Services (AWS) or Microsoft Azure. And, open source architecture can now incorporate robust technology components with rich functionality. Our current collaboration with Partners Healthcare to build a digital platform for clinical care is based on an open source architecture. As the industry shifts rapidly to value-based care, cost pressures will force healthcare enterprises to transform their technology strategies, turning to open source solutions to rapidly build new solutions cost-effectively.