Category: Podcast

Introduction to Dr. Daniel Araya

Dr. Daniel Araya is the co-founder of Aion Advisors, an international consultancy and think tank. He is a senior partner with the World Legal Summit, and Senior Fellow at the Centre For International Governance Innovation (CIGI). Dr. Araya is a leading expert at the intersection of artificial intelligence, public policy and governance. He is a regular contributor to Forbes and the Brookings Institution, and his latest books include ‘Augmented Intelligence’, a book on the Future of Work and Learning, published in 2018, and ‘Smart Cities as Democratic Ecologies’ published in 2015.

Daniel has a doctorate from the University of Illinois at Urbana-Champaign and is an alumnus of Singularity University’s graduate program in Silicon Valley.

1. Getting Ready for replacing routine labor with AI & robotics

Daniel believes the level of transformation we’re facing is revolutionary, especially with regard to the government in the United States, mostly because the US anchors the global system. If the US system were to collapse, the whole world economy would likely collapse. With this being said, it is important for US leaders to begin to prepare for radical change, like labor disruption and automation — replacing routine labor with AI and robotics.

As we move into new social policies in the United States, it feeds into massive changes that are occurring outside of the US, like the rise of Asia and China. Asia is now going to be the center of the global trade, especially with China leveraging technology more effectively than the West. We are facing the United States losing its place in the global order to China.

With the majority of people working from home, the companies that are doing well in the new environment are digital companies, such as Amazon and Microsoft. Moving forward, we are only going to see more focus on digitalization and a digital economy, especially as the older industrial economy begins to unravel or decline.

Artificial Intelligence is a general-purpose technology, and it will impact multiple industries in different ways. AI will begin to impact everything from children’s toys, to services, to infrastructure, to smart cities, to automation. It’s not something that old policies will easily manage. But we’re going to need to regulate Artificial Intelligence at a very broad level. The impact of AI will be substantial, and we can anticipate an entirely different civilization with the development of new technologies. We’re going to need a different kind of regulatory and governance system to manage it.

As Elon Musk, Hawking, and many others have suggested, AI can be a very unstable technology if not managed properly. And the world now geopolitically is shifting towards regionalization, in part because new wealth is emerging in other places outside of the West. This could be a very destabilizing problem in the future.

2. Reaching A Hidden Regionalized Economy

With the rise of Asia, China’s potential is huge, and will probably take over mass manufacturing across the board. The question is: if we automate a platform that frees up people to do more advanced work, what would that work be? In Daniel’s opinion, the cultural industry. More people will be interested and involved in the creative arts, way more so than in the past. Work we once thought were valuable will become algorithms, and perhaps even invisible within the platform of manufacturing and distribution of goods. We’re basically going to build a civilization on top of a platform of full automation.

Daniel reiterates we will also see a huge impact on the school system. He believes there is a high chance we will reinvent learning around AI and simulations, for we might not even have a choice. The classroom model formed during the agricultural era is slow and outdated. We need to establish a new system of learning.

3. Interacting with China

With China being very opaque, it’s difficult to gauge their strategy and planning. On the surface, it looks like China is a developing country that just got access to the World Trade Organization. However, Daniel believes that there is something deeper about China, for China knows how to build effective bureaucracies. China also scales better than any other country. Daniel views China not as a huge threat to the west or the north, but rather the global south. There is a chance that China will lead the global South from Africa to Latin America, and parts of Latin America to Southeast Asia.

In Daniel’s opinion, the US needs a new generation of leaders. For example, many Baby Boomers do not have any understanding of technology, and they do not appreciate exponential innovation. Baby Boomers grew up in a factory era, in which the social welfare state was functional. What would be beneficial is a new generation, whether Gen X, Millennials, or Gen Z, to restructure government in the US. A new generation could take the helm and drive the ship in the right direction.

4. Basic Universal Income and Monopolies

Universal income is an expensive adventure and venture, there is not an alternative in the short term. However, Daniel believes that it does not solve all problems in the long term. Basic income is a national project, and something only national governments can provide. Only wealthy countries will be able to afford this concept. And the next question is — where does the tax revenue come from to then redistribute as a basic income?

Daniel thinks capitalism that we’ve taken for granted is going to change. What is happening is tech companies are becoming monopolies, and essentially taking over whole industries. As these companies get bigger and bigger, no one will be able to compete with them. And like Amazon, they use algorithms to improve production efficiency.

What we’re witnessing is the rise of the tech era where market churn begins to slow down and transition more towards the creative industries. People will pay for the arts more in the future when their other needs are met, however, this transition will prove to be a bumpy one.

5. Responsible AI

We must be careful with Artificial Intelligence, even slow in some respects. It is inevitable that mistakes will be made.

An example is the military leveraging AI technologies and transitioning to a different generation of warfare. As we move into a tech driven system of societal, economical, and institutional change, old solutions will not work. We are really going to have to think through new solutions and work through trial-and-error to ensure responsible AI.

Artificial Intelligence is an extension of us. We don’t have to see Artificial Intelligence as an alien machine. We must keep in mind that some people will have better tools to utilize AI than others, which could lead to more inequality. And there are people & companies who will leverage AI not for the greater good. We must be mindful on all accounts as we technologically advance.

6. Advice to World Leaders Post-Pandemic

With Daniel more biased towards technology, he is often labeled as a determinist. He believes we’re entering into an era where software is fundamental to everything and does not feel there will be anything but tech companies in a decade or two. As smart software & robotics take over the world, it’s going to be critical for people to be better educated at every age about both the upside and downside of technology. Everyone will have more of an appreciation for technology that is leverageable for social change, and we should develop a vision about where we want to go. Young people in the context of education should be inspired by the future, not afraid of it. We must leverage these technologies. Part of that is research and looking at the curve around falling costs, which circles back to China. China has the capital and the ambition to build infrastructure in the developing world.

As a whole, we must work on leveraging energy more effectively and efficiently, while using data and analytics to do so.

https://www.danielaraya.com/in-development

Book: Augmented Intelligence: Smart Systems and the Future of Work and Learning

Introduction to Guest

Ashutosh is the CEO and Founder of Eightfold AI – the industry’s first Talent Intelligence Platform, built for enterprises to address Talent Acquisition and Management in a holistic fashion. Eightfold AI is proven to be one of the most effective ways to identify promising candidates, reach diversity hiring goals, and retain top performers.

Ashoutosh graduated from the Indian Institute of Technology and he received his PhD from the University of Illinois in Electrical and Computer Engineering with specialization in AI/Machine Learning. Here he won the ECE Young Alumni Achievement Award for his fundamental contributions to machine learning and its applications to scale personalized search and ranking, and for his bold entrepreneurship. Prior to founding Eightfold, Ashutosh was co-founder and CTO of Bloomreach.

The Call to Adventure

Throughout Ashutosh’s life, he has always been working against the norm. Overcoming obstacles that seemed impossible, challenging the status quo and the standard way of thinking. Back in 2003, Ashutosh came to Silicon Valley to join IBM Research, and later went on to work for Google. In 2008 Ashutosh realized he was working under the constraints set up by large enterprises, which greatly limited his freedom. That year he left his job to start a company, Big Data Machine Learning, using his expertise in AI and data.

Ashutosh understood he did not want to just create any company, but an AI company that helped people while having a massive impact on society. After looking into education and healthcare as fields to assist, Ashutosh was led to HR, and started talking to many leaders in the industry. Through his listening, analyzing, and synthesizing, he got his first ah-ha moment in 2016 where he realized how important employment is for society. One aspect he discovered was, it is “who you know” that gets people employed, especially with big companies. Ashutosh is on a mission to change that using data and AI.

Company Name & Meaning

The name Eightfold AI came about through the philosophy of the Eightfold path to noble truth. It is all about learning and unlearning, to grow, develop, and to achieve the ultimate goal of your life. Ashutosh wants his company to be that Eightfold path for your career.

Finding Product-Market Fit

The technology Eightfold AI built is designed to use Artificial Intelligence to understand how people move through their careers. What the team has built uses many careers paths (more than a billion), all of the information you can understand about someone’s career path, and what makes them successful in their roles. The technology also helps determine what they will do next in their career, the jobs they’ve held, their education, their skills, etc. The algorithms will then take all of this information to understand what makes someone successful. By applying this at scale, Eightfold.AI can turn Artificial Intelligence into an Intelligent Talent Management Platform for the enterprise. The first of these applications that Eightfold AI went to market with was for talent acquisition and recruiting. A recruiting organization can then define its requirements and the AI will take all of the available talent and rank those individuals immediately based on who is the best fit for those roles.

This technology will also surface individuals who might not have jumped off the page if the recruiter quickly glanced at their resume. Eightfold AI has also taken this technology and applied this application for internal talent management. In the same way that the AI can recommend the individuals for a job, you can also recommend jobs available for an individual within the company.

Now Eightfold AI is looking into applying the experience for individuals looking for jobs. This is very impactful for a candidate looking at a career website, where the jobs come to find them rather than having to go and search for the job. Which, let’s be honest, can be frustrating and time consuming.

Another key value-add for using AI is that the technology is non-bias. All of the algorithms are designed to prevent any bias on visible or unknown personal characteristics. For example: age, gender, race, ethnicity, disability status, romantic orientation, etc. Not being considered by the algorithm creates better outcomes and more confidence since bias is avoided.

Getting Enterprise Clients

First, understand whether your solution is genuinely applicable to large enterprises or not. Secondly, ask yourself – are you ready for that? Selling to large enterprises takes a lot of upfront investment. Are you enterprise-ready or not? Eightfold also has security policies, in line with what enterprises will expect. Compliance is a liability of infrastructure. Something to consider.

Advice for Future Entrepreneurs

When you are first starting off, think of the problem that needs to be solved. Once you identify the problem, the first step is talking to key people and industry leaders to get their perception of the problem that needs solving. Second, make sure there is a market, because if there is not a market, nothing else matters. Think about the solution you have in mind, and the solution you will come up with to solve the problem. What is your unique selling proposition? Focus on your strengths in the market. The third component is to make sure your buyer can solve the problem quickly once you provide a product/solution.

Another piece of advice is to think of where the market is going to be in ten years. Make sure you can scale and have room to grow. If you do not pay attention to this aspect, you can easily become stagnant in your business. Make sure you have a strong support network because even on “good” days, anything can happen. You must have enough energy to push through and do not give up on your optimism. Stay grounded and focused. Find a balance between paranoia and optimism.

Introduction to Guest

Rob LoCascio is the founder and CEO of LivePerson, a conversational AI company that connects brands and consumers on the world’s most popular messaging platforms, making life easier for people and brands everywhere. Rob is one of the longest-standing founding CEOs of a tech company today, and LivePerson has grown to about 1,200 employees serving 18,000 clients worldwide, including some of the biggest brands in the world like HSBC, Delta Airlines, and T-Mobile. Rob is also the founder of FeedingNYC, which has packed up and delivered over 80,000 Thanksgiving meals to families in need since it was founded after 9/11.
Rob was born and raised in New York and graduated from Loyola University Maryland.

Call to Adventure

Coming from a family of entrepreneurs, Rob always possessed the desire to start his own business. After losing his first job right out of college, Rob was led on a path working in technology, and eventually became a technology leader and entrepreneur. In 1991, Rob came across the concept of interactive kiosks — touch screen kiosk and digital video — and struck an interest in the idea. This was during a time where there were no digital videos on computers. However, Rob was fascinated by this concept and soon started to think how he could apply his new discovery to his business. This was Rob’s first call to action.

Rob’s first company went under in 1995. He had just moved to New York and did not have enough money for an apartment, let alone an office. In fact, he wound up choosing an office that was four square feet with his bed being a couch. Rob even went to his health club to shower. Even though times were tough, he kept at it. In 1997, Rob began to ponder an idea about his website — “how can you have a conversation with people digitally?” — which was unheard of in the 90s. With this question weighing heavily on Rob’s mind, he invented communication through web chat in 1997. This groundbreaking invention led Rob to filing his first patent in 1998 and receiving his first round of financing in 1999. Rob realized commerce is powered by conversations, which proved to be a necessity to truly fulfill the commerce experience.

Testing the Product & Validating the Market

Over the last 20 years, LivePerson faced a number of crossroads, which included the realization that webchat was never going to get LivePerson to a grand vision of commerce if it’s only powered by digital conversations. 10% of all conversations were via chat, while the remaining 90% through voice calls. Instead, LivePerson decided to leverage messaging tools, creating systems using Facebook Messenger and WhatsApp to communicate with customers.

This was an ah-ha moment for Rob. As consumer behavior moved towards asynchronous messaging and mobile messaging, Rob built a platform to connect the messaging front ends. From this market validation, LivePerson launched their new platform four years ago, called Live Engage.

Rob understood that if you are going to scale conversations, you must have automation running using Artificial Intelligence and Machine Learning. With over a billion conversations in storage from some of the largest brands in the world, LivePerson is able to use AI and machine learning to build conversations that can automate the entire customer care and commerce value chain.

Looking at conversational commerce, retail is a massive market when using automation. In stores across NYC, LivePerson set-up QR codes next to specific products, where through the QR codes you have the ability to ask questions and find out information about each particular item. The retail industry is proving to be a massive part of the conversational commerce experience, especially through using Artificial Intelligence.

On Scaling AI

LivePerson is using a platform called the Conversational Cloud. Early on, Rob realized that AI has been in the hands of technologists, data scientists, and engineers. But if you’re talking about conversational experiences between a consumer and a brand, the people who have those conversations with consumers are contact center agents. They are the people having millions and millions of conversations a day. With that in mind, LivePerson wanted to build a toolset that enables these people to be empowered to develop the automation, deploy the automation, and own the automations — taking their job from agent to conversational designers and bot managers. LivePerson took this approach and built their platform to have this secret weapon, which is taking the agents and getting them involved with AI, and in turn, scaling at a high rate. Rob labels this method the tango human machine working together.

Disrupting Consumer Experience

With their product in major retailers such as David’s Bridal and Chiptole, LivePerson is taking the user experience to a whole new level. Customers are able to have conversations and/or place orders with each company’s particular app. There is no need to speak to someone over the phone or wait for a service in person. With the ease of using Facebook Messenger and WhatsApp, users can easily communicate with their favorite restaurants and retailers, saving everyone time and energy.

Not to mention LivePerson grew revenue 29% in Q2 of 2020, the best quarter in the history of the company.

Advice for Industry Leaders & Future Endeavors

The advice for industry leaders is bring together all teams in your company, especially the care and technology employees with those who work in IT. Set your vision for how conversational commerce will enhance the consumer experience. From there, bring each team together on a path to work with a platform provider, like LivePerson, where the platform can offer precise expertise and technology to advance a company. Make sure you have a backhand system that is available, not a lousy bot that will direct you to a 1-800 number. Get your backend systems exposed so your consumers will have rich conversations, then bring in the care workers to design the conversations and implement them. Make sure you can scale the conversational commerce experience.

Rob predicts in the next five to ten years we will see massive amounts of e-commerce being consumed by c-commerce, a race that has already begun by massive companies such as Facebook, Amazon, WeChat, and Google. LivePerson is confident that they are a huge part of that race.

Advice for Future AI Entrepreneurs

The biggest mistake Rob has seen is many bot companies show up out of nowhere with no real plan, receive funding, and then fail, or they just remain a small business. Playing in the enterprise is really difficult, and quite slow. Rob’s advice is, instead, build something in the consumer space, perhaps an AI platform that you can sell to a company, that will benefit their consumers. Come up with an automation that helps solve consumer use.

Rob also shares that when you hit a low point, you have to go within and listen, for this is when you will learn the most. Do not look at low points as failures, but as gifts. Try to meet more people, listen, and stay open minded. Do your best to lose the ego. When hitting a low point, shift the way of thinking to: “great, now I get to grow as a human.” Know that you are not alone, and this hard moment will give you something greater than you had ever imagined. Also, never quit when you are at the bottom.

Challenges Encountered & Moving Forward

While there has been a plethora of challenges, such as 9/11, the financial crises, and COVID, Rob has never looked back, for massive changes mean massive opportunities. Even during multiple times when LivePerson almost went under, Rob credits surrendering to the higher power and letting go in moving forward. Rob iterates if you’re going to be an entrepreneur, tapping into spirituality is a must, and is a massive reason Rob has found success. The spirituality behind being an entrepreneur begins with the power of creativity, an idea you envision, and bringing that idea into existence. You then must organize people to help you as you pour your heart and soul into this creation, a creation that began in the mind.

When challenges occur, Rob has always asked himself, what can I do to change my trajectory moving forward, and what can I do to be open to understanding? What’s the bigger purpose here?”

When Rob was going through one of the most challenging moments of his life, after he lost his first company at the age of 27, he learned that he was wearing a set of “glasses” which caused him to see the world in a way that was not serving his life. Rob had a vision but his glasses and the way he perceived the world was not in alignment. Rob needed to see the world clearly, so when he met new people and made decisions, he was serving himself. These were all realizations Rob experienced from starting his own business.

Going Within

There was a massive shift for Rob 12 years ago after visiting an ashram in India to learn how to meditate. It was through this moment, finding his inner voice, where his life completely changed. Taking an inner journey is different for everyone, but it is a journey that proves to be life changing. Through Rob’s meditations, he was able to clear out the other voices in his head. The voices of his friends, family, and of society telling him how to live his life. Through his time in India, he learned how to hear his own voice and intuition, especially during challenging times. To this day, Meditation helps Rob make decisions, while providing him tools to tap into his intuition and inner knowing. When Rob feels stressed, he can now find a place of calm through meditation, deactivating any unnecessary noise that might consume him

Rob has lost a lot and failed a lot, yet he has been able to build a massive, successful business, earning himself a name as one of the top technology entrepreneurs in the industry. Rob’s purpose in life is to inspire entrepreneurs to take the journey, but to also understand that the journey to build a business is not a rag to riches story, but a lifelong commitment into one’s self and inner knowing.

https://www.liveperson.com/

Introduction To Guest

David Golan is a co-founder and the CTO of VIZ.AI, a digital healthcare company harnessing deep learning to analyze medical data and improve clinical workflow. VIZ.AI developed the First ever, FDA-approved, AI-powered triage system for stroke. Prior to founding VIZ.AI, David was a Fulbright postdoctoral scholar at Stanford University, working on leveraging deep learning for the analysis of medical imaging and genetic data. David holds a PhD in Statistics and Machine learning from Tel-Aviv University, and has co authored more than 20 scientific papers, including three publications in the Journal Science.

Coming Up With The Idea

David Golan has been working in the AI, machine learning, and data science space for about 18 years, receiving his PhD in Machine Learning. David was content with his career pathway, and was set to return to Israel from the US to take a faculty position and work in academics. However, it was not until an unexpected event in 2015 where David’s life completely changed. He suffered from a suspected stroke that left David unable to move his arm and leg for a period of time. He was also unable to speak. David experienced first hand the massive gaps and wrong-doings in how inefficiently patients were treated. He knew that moment had changed his life and his career path.

The Call To Action

After David’s health scare, he was introduced to his co-founder and now CEO of VIZ.AI, Dr. Chris Mansi. Chris is a neurosurgeon from the UK who moved to the Stanford business school in California. Chris had numerous cases with surgeries that he performed, all which have gone extremely well, but some of the outcomes unfortunately resulted in the patient’s death. When investigating why, David and Chris realized it was because of workflow delays, chaos and inefficiencies, very similar to the same problems David experienced as a patient. Chris suggested automating this workflow by identifying the patients that need expert care and triage them, which quickly sends them to the care of a highly skilled physician. With Chris’ expertise as a neurosurgeon, and David’s extensive background in machine learning, VIZ.AI was born.

VIZ.AI is now a 100 people company, split equally between the US and Israel. The R & D team is almost entirely in Tel Aviv, while the rest of the operations team is based in the United States.

In order to build a successful product, David had to understand both the medical imaging and the different use cases, identifying the exact problem they were trying to solve, while finding the best solution. At the same time, he and his business partner had to understand the financial side of healthcare and how to build a business model that makes sense. They also had to raise money to start building the products, which consisted of pitching to VCs. In order for VIZ.AI to be successful, David and Chris had to work on connecting with people that could support them with getting data – which is critical to power Artificial Intelligence.

David and his team believe that the world needs accelerated acute care, which can be achieved through Artificial Intelligence. VIZ.AI is built to hit three points known as the triangle. One point is the patient, the main incentive behind VIZ.AI. The second point is the physicians, making their lives easier and better. The third point, which is often missed in the healthcare space, is coming up with a solid business case for the financial operators of the hospitals. This is crucial when starting a business in the healthcare industry.

How VIZ.AI Technology Works

When a patient has a stroke, 70-80% of the time they will go to the nearest hospital, typically a smaller hospital, called a primary stroke center. The smaller hospital can provide first line treatment, but they cannot perform a full blown surgical procedure to remove the clot in the brain, which causes the stroke. Once the decision is made that an actual stroke case is present, the patient is moved onwards from a comprehensive stroke sample to a big hospital that has all of the facilities to operate. This back and forth, inefficient coordination between the two hospitals causes massive delays, especially when making decisions. With each minute delay, 4.2 days of disability life accumulates.

When a patient goes into the scanner, the cloud scan is analyzed by AI, identifying whether or not the patient is suffering from a stroke. AI is used to complete the triage. From there, VIZ.AI immediately notifies the entire chain of command, with the team receiving a loud alert noise on their phones. The team can then open the VIZ App, where they not only receive a notification, but receive images and can chat between colleagues, essentially communicating extremely fast. The physicians also have a call center they can access. This process completely flips the system by eliminating the uphill battle. With the most experienced physicians receiving notification calls, the ER can provide the scans quickly, maximizing the workflow to the fullest. This is a revolutionary feat, changing the way acute care workflow is being managed, while at the same time saving lives.

While the company is called VIZ.AI, David believes his company is more as a workflow company, with both Artificial Intelligence and technology being a big part of what they do. Both AI and tech are just as important and useful when focusing on moving the needle to make patients better. VIZ.AI is successfully up and running in over 400 hospitals in the United States.

Challenges Encountered

One of the biggest challenges encountered by VIZ.AI is to understand the business side of the hospitals, while using do-good technology to help patients. It is crucial to implement the technology while also catering to the needs of the administrators and the financial stakeholders in the hospitals.

Another point David makes is how lucky VIZ.AI was to find extremely collaborative, supportive, frontline physicians who helped bring the vision to life. These physicians are able to provide the team with data, feedback, and expertise. However, there were a few challenges while setting up an impressive data collection network. This, at first, was easy, but then proved to be difficult for hospitals who were all connected to the cloud. With scans finding their way to one cloud based app, issues started to arise with the IT security of the hospitals.

David reiterates that from the get go, when operating in healthcare make sure you have a security-first mindset, along with the certifications and credentials to show for it. Invest a lot of effort in making sure your data and scans are secure.

Pivoting Through COVID-19

When the pandemic hit, VIZ.AI was able to pivot to assist patients in need. David and his colleagues were able to create a modified version of their VIZ App to support COVID-19 teams, notifying physicians on positive or suspected cases. This proved to be extremely helpful and successful, with about 20 hospitals now using VIZ services. VIZ.AI is able to deliver even more value to their users.

Another transition, or pivot, VIZ.AI encountered through COVID-19 was when the sales team stopped traveling. The sales department, which consists of nine people, are all now working from home, saving VIZ.AI a lot of money. Interestingly enough, this change did not slow down VIZ.AI’s sales. This realization has caused David to question the traditional methods of operation.

The Future

Two years from now, VIZ.AI envisions it’s product managing every acute case that comes into the hospital. Five years to ten years from now, the company will not be limited to acute care — there will, in fact, be no limitations. Not only will VIZ.AI be providing Artificial Intelligence to add value, but all of their physicians and hospitals will have a fast app that instantly connects everyone, creating a massive generation leap in terms of working together. At the end of the day, the mission of VIZ.AI is to help patients be seen by the right doctors and receive treatment efficiently and effectively. The company wants to make connections for all diagnoses, while eliminating the variability in the level of care across the world. With an AI powered healthcare operating system, a patient can live in a poor neighborhood but has access to the best physicians, possibly located on the other side of the country. More people will have the opportunity to receive the best level of care, regardless of the socialist disadvantage regions and countries of the world.

Advice For Industry Leaders

David’s advice for industry leaders is to stay open to the challenges you are facing, and get clear on your financial model. Find use cases that are both clinically useful and financially viable. While this feat can be challenging, it is crucial in order to have a successful company. In fact, not having this method in place is what causes most healthcare startups to fail. Make sure to keep your thinking progressive. See how you can harmonize trust with hospitals and/or companies in the healthcare space, especially when it comes to security. This will accelerate healthcare transformation as a whole.

www.viz.ai

Introduction To Guest

On this episode of Brains Behind AI, Ari and Natalie met with Bobby Palmer, the President and CEO of PotentiaMetrics, an Austin-based healthcare data and AI company. PotentiaMetrics’ data analytics and artificial intelligence platforms help providers, payers and medical technology companies inform personalized treatment plans by comparing patient-level outcome data related to survival, quality of life and cost of care. These companies use PotentiaMetrics platforms to compare effectiveness, adjust for risk, and track outcomes-based performance metrics.

Bobby has been a business owner and CEO for over 20 years, creating the vision and strategic direction to develop multi-institutional, real-world outcomes registries that enable the creation of unique and personalized AI platforms. Bobby received his MBA from Washington University in St. Louis.

The Call To Action

Bobby first started to work in healthcare – working with a group of cardiac surgeons, developing predictive analytics for cardiac surgery outcomes. During this time, his father was diagnosed with prostate cancer, which quickly spread to his liver. With the cancer spreading at an alarming rate, this was a difficult diagnosis, as Bobby’s father was previously active and healthy. It was also challenging for physicians to accurately diagnose and treat his father’s cancer, leaving Bobby and his family very frustrated and helpless.

Bobby quickly learned that every patient with cancer is unique, and it is tough to know exactly the “right” thing to do when caring for a loved one. After the diagnosis, his father suffered from multiple infections and spent half of his time in surgery. Bobby and his family did what they thought was best using the little information they had, which unfortunately resulted in the passing of his father. After Bobby’s father passed away, he started to evaluate what had happened throughout his downfall, and started to piece together multiple gaps. Bobby soon realized that there was a discrepancy between the outcomes of clinical trials with cancer patients, versus cancer patients who are in the real world — older and racially diverse with underlying health conditions. Clinical trial participants are younger, tightly controlled, and less racially and ethnically diverse. They are also healthier in general. The cancer patients in the real world are on a whole different spectrum, older with different stages of diseases. With this newfound information, Bobby wanted to create a way to give patients the best information available, while providing transparency that was specific to their own individual and unique condition.

Coming Up With The Idea

With Bobby’s new discovery and a desire to spend time on impactful work, he saw a massive opportunity, an opportunity that can save the lives of others. After bringing on a team with clinical understanding, PotentiaMetrics was born. The company soon partnered with multiple academic institutions to access more data, while looking at comparative outcomes over time. They also combined these datasets from multiple institutions from three other nations. The team was able to look at the large data sets, multiple stages of the patients, different treatment choices, and from there start comparing their outcomes. PotentiaMetrics spent a lot of time on fundamental questions when determining their approach, while post-developing the tools that tests and validates externally to prevent additional confusion. For Bobby and his team, transparency is key, and trusting the information is critical to this transparency.

Founding A Team

With Bobby’s background in healthcare, he put together a group of very experienced surgeons, clinicians, oncologists, general practitioners, and doctors. He brought on a team with clinical understanding, who can fully help evaluate massive amounts of patient data.

Validating The Market & Testing The Product

In an era of increasing outcomes transparency, Bobby began PotentiaMetrics as a way for providers to define and demonstrate improved clinical and economic outcomes. PotentiaMetrics also enhances medical evidence with PotentiaMED AI platforms supported by real-world clinical and economic outcomes data. PotentiaMetrics develops analytical platforms to support systematic comparisons of results, measure performance, and enhance improvement.

At the beginning stages, PotentiaMetrics started with academic centers, focusing on a certain group of patients. For example: a newly diagnosed African American runner with breast cancer was one patient who used the platform and provided feedback. Through this stage, PotentiaMetrics had to answer many underlying questions found through these particular studies. Within these findings, Bobby was surprised by the information he uncovered. For example, some patients are scared and only want their doctor to tell them what to do. While there is another group of non-English speaking patients that believe the healthcare system is wired against them and only receive suboptimal care. And if you look at the data and the outcome of these patients, they are incredibly weak. PotentiaMetrics saw race as a factor of prognosis — testing the platform not just from a tool perspective, but also from the usability and uptake perspective, was an important component.

From PotentiaMetrics’ findings, market validation, and testing, customers now possess actionable insights that improve patient outcomes, accelerate contribution margins, and decrease healthcare spending. Information is delivered that enhances the current evidence base, revealing new information and contradicting previous findings, all of which is not available from other sources.

Challenges Encountered

To start, change in general is hard, especially when introducing new information that is not available before. Also, patients might not benefit from the cancer treatment, as 30% of people do not fully benefit and react to the treatment/medication they’re receiving.

In the United States, the system is based upon the volume of treatment and the economics are dependent upon more patients coming through the system. When you introduce PotentiaMetrics’ tool, which focuses on transparency and matching the right treatment for each patient based upon their bodies, this can lead to less treatment, and therefore, less revenue, for the hospitals.

The second challenge is how does PotentiaMetrics relay information to patients in a way that they can consume and understand? Multiple studies show that less than 5% of adult patients with cancer can explain what their prognosis is, and normally once they hear cancer, they think they are not going to live. Even though physicians are doing their best to mitigate these factors and explain the prognosis, patients are still left terrified. The challenge is how do you bridge the gap of over providing information that is fundamentally scary, and in a way that cancer patients can relate, understand, and digest. This will also assist the cancer patients in having deeper, more meaningful conversations with loved ones.

An additional challenge to mention is COVID-19. With a huge focus on taking care of the pandemic and Covid patients, many other health issues are ignored, including cancer. With cancer screenings not occurring at the same level and rate, there is a growing concern worldwide. The sad truth is we will unfortunately witness a bump in mortality rates this year.

Applying Machine Learning

PotentiaMetrics has models for 14 different cancer sites, and covers roughly 80% of all adult cancers. Each one of the models are variables specific to each cancer, and the weighings of those variables are very different depending on the type of cancer. For example, if you look at a patient with prostate cancer and take into account the age stages, it’s used from the avidity of the other diseases that the patient has. From there, you combine those with different treatments or a combination thereof. What PotentiaMetrics is relating on a machine learning basis is: “What are the outcomes of similar patients that have received different treatments over time, so that we can accurately predict a five year survival rate?” The machine learning aspect comes into play when you think about the population of patients changing over time with new treatments needed. In general, patients are getting older and are witnessing different stages of diseases. PotentiaMetrics’ AI models are training and updating based on all these factors coinciding and working hand in hand with each other.

Advice for Industry Leaders

For industry leaders, adapting to new technologies faster, especially with the vast changes in technology, processor speed, and data on a monthly basis is key. Technology is usually available a year before it makes the sale cycle within the hospital system. If we can move towards a faster speed of technology application, we can not only save more money, but also save more lives.

Advice for Aspiring Entrepreneurs

As an aspiring entrepreneur, first look for gaps in the healthcare industry. Second, find areas where gaps are present, yet there is also a clear pathway towards reimbursement. See how you can develop new technology that plays into the existing system where you also generate a return on investment. Many times people are so focused on the clinical need that they gloss over an actual business plan. Make sure you incorporate both the technology and business aspect into your company.

Future Endeavors

PotentiaMetrics is heading in the direction where every patient holding an intricate diagnosis, like cancer, can ask questions and receive credible information, while predicting positive outcomes using different combinations of treatment options. With real world cancer patients possessing additional underlying health conditions and multi-dimensional challenges, many are faced with difficult choices. Where do I live? Can I keep my job? Can I watch my kids and/or grandkids? PotentiaMetrics aims to provide tools that offer answers, not just to survival questions, but answers that take into account one’s values and quality of life. PotentiaMetrics aims to provide deeper information that’s more relevant and critically personalized, especially with new data and technology. Bobby also invisions the company helping people with other complex diagnoses heal and recover.

www.potentiametrics.com

https://www.mycancerjourney.com/

Introduction to Guest

Rohit Ghosh is an IIT Bombay grad and Founding Member of Qure.AI -with a mission to make healthcare more affordable and accessible through the power of Artificial Intelligence. Qure.AI was just ranked by Forbes as one of the top 15 companies that are saving the world from COVID-19.

Previously, Rohit worked as an AI Scientist and was deeply involved in building R&D products in the computer vision area. He also worked as a Data Scientist for ListUp. Rohit has been widely involved in mentoring and teaching data science students. He also has 15+ publications in multiple journals worldwide.

The Call to Action

In 2014, Rohit graduated from IIT Bombay with a very lucrative job offer as an investment banker. An offer that Rohit wound up taking. However, after nine months working for the company, he had an epiphany. Rohit wanted to do something more meaningful with his life, to put forth his time and effort into a project more impactful, and on the edge. Rohit was also given the advice that at a young age, you can afford to take risks and try a few things that you’re interested in, for you had less liabilities. Not fully satisfied with his current situation, Rohit took this advice to heart. He left his job as an investment banker, found two other co-founders, and went all in on Qure.AI

Together with his new teammates, Rohit embarked on the scary, yet exciting, journey of making a huge impact in the healthcare industry.

Coming Up with The Idea

Before founding Qure.AI, Rohit knew deep down in his soul that the company he wanted to create must be impactful and meaningful, something beyond himself. Especially coming from India, Rohit knew he could make a difference, not just for his country, but for the rest of the world. With a vision to work in healthcare, Rohit needed a clearer vision on where to start. After a lot of trial and error, validation, and working on a plethora of different concepts, Rohit narrowed down his focus to radiology. He saw a massive gap in the market.

Rohit was also able to go deeper in computer vision and chest X-ray diagnostics using Artificial Intelligence. In terms of accuracy in AI models, he realized more data is key. Rohit also tested that the value they can generate with their product, and the people they can reach, was way more effective with computer vision and radiology. Radiology was also easier to explain to people and easier for customers to perceive. AI used for computer vision.

A model with limited use was soon brought to life yet constrained to only a few people.

Validating the Market

When they first got started, Qure.AI was seed funded. Rohit and his team took the first two years to dive into good quality research in making their product work, all while eliminating the stress of commercialization. All members of the founding team worked on different models and gathered more data. They published publications in the market to cultivate trust. Rohit stresses that trust is key, especially in the healthcare industry. Rohit built this trust by keeping transparency between what Qure. AI was building and the research they were conducting.

By being extremely honest through keeping all research out in the open, Rohit was able to build that trust needed inthe market.He also talked to a lot of stakeholders -hospital/healthcare providers, government officials, radiologic providers – to learn their pain points. This formula is how he narrowed down his first mission to tackle – Tuberculosis Diagnosis. In India alone, TD is a huge epidemic, there are almost 10 million cases. And in SouthEast Asia (SEA), there is a massive problem with x-rays and delays on scans. Many x-rays don’t even get reported. For example, if someone gets tested for Tuberculosis, they would have to wait an additional 10-15 days for their results. This delay can result in deterioration of health, spreading of the disease, and in worse cases, death.

Despite outsiders discouraging and pessimistic at times, Rohit and his team held their faith, and kept moving forward with their AI product and deep passion to help humanity.

Testing the Product

Rohit started by testing his Qure.AI product in the Philippines. In the Philippines, mobile chest x-rays are apparent, but radiologists on location are scarce. Radiologists travel in and out of the city for testing, then spend time uploading the scans to a cloud. This process takes 2-3 weeks. Not to mention a microbiology test then had to be completed if the patient showed positive Tuberculosis results. The whole process is painfully long and ethically not working.

With people falling out of the tunnel through this process, Rohit & the team found a way to massively speed up the testing. Using Qure.AI, the software can look at a chest x-ray and provide a Tuberculosis diagnosis in 30 seconds, collecting the results right then and there. If the results come back positive, the specialist can conduct a confirmatory microbiological test on the spot. Qure AI took a 15+ day process and drastically reduced the time into four hours. This is really an unbelievable feat, and a huge paradigm shift in what AI software has been able to achieve.

Challenges Encountered

Working in SEA, and many third world countries, the main challenge encountered by Qure is lack of internet. With internet connection scarce, Qure AI cannot rely on the cloud, which turns out to be only the first part of the challenge. The second part is the size of the product, finding a solution for it to fit with a portable X-ray machine. After a lot of hard work, Rohit and his team found a way to shrink the box to the size of a cookie box, making it easily deportable and easy to set up.

Another challenge Qure AI encountered was contacting radiologists in India, which was quite scarce. Unlike places in Europe such as the UK where an at home reporting infrastructure is in place to look at critical cases, India does not have the same system. With radiologists working short number of hours (only on call 8 a.m. to 2 p.m.), and with little WIFI connection, any diagnoses in India that required immediate attention are not looked after. Qure needed to find a way to get a radiologist to look at cases and report them in a much faster fashion. Astonishingly, Qure solved this problem through using WhatsApp.

After their ah-ha moment, Qure.AI software was implemented in hospitals. And at any time, a critical case was reported after 2 p.m., a message would be sent to the WhatsApp group. This completely changed how TD diagnoses are reported. Now, with everyone all in one group, radiologists can look at case comments and act accordingly. Who would have known joining an app such as Telegram or WhatsApp would be a major game changer when saving lives.

Fighting COVID-19

Since starting off with detecting Tuberculosis, Qure.AI has expanded to 28 different abnormalities, along with Covid-19. These abnormalities can include radiological manifestations of Covid-19 as well. When Covid-19 hit hard in March, Rohit knew his product could have a positive impact on diagnosing patients quickly, while tracking their recovery.

Through chest x-rays, Qure’s AI application can see if one’s lungs are improving or deteriorating. Their product has proved helpful in the ICU, where chest x-rays are easily scanned. On the scan, you can look at the percentage of the lung infected and compare the results to previous scans of the infected patient. In turn, monitoring the progression of the patient.

Qure now has a strong user base in many parts of the world such as: Mexico, the UK, Italy, Russia, Australia, and other places that have been hit hard by Covid-19. In less developed countries in SEA where there might be a lack of testing kits, Qure decided that those who are at the highest risk of losing their lives will be tested first. This has proved to be a huge advantage to parts of the world that don’t have enough kits to test people.

Advice for Industry Leaders

When you are creating a company, it is key to have an AI strategy in place with enough leverage to try/do different things. This advice is particularly for those leading organizations. Make sure there is someone within the company or organization who’s responsible for that strategy, while providing them the leverage to experiment. Really pinpoint what works and what doesn’t

Many times, companies fall into the hype of Artificial Intelligence, so make sure you think in terms of how AI will generate value, and how AI can benefit both you and other people.Consider the use cases for everyone listening, or else finding value will be difficult

Advice for Aspiring Entrepreneurs

If you’re young, take the risk now, or it will get more tough to take the risk later on in life. However, before you take the giant leap, begin small if you need to. Start a project on the side, validate the market, and check in with yourself to see if you’re enjoying the potential venture. There is always the chance that starting your own business is not something you’d like in the long run. By keeping your day job, you can still go after your goals, save some money, and gear up to make the giant leap.

Another piece of advice is the ability to learn. Five years ago, Rohit had no idea what machine learning was. His learnings came about from adapting and picking up new skills on the go.

Rohit’s journey, ambition, and ability to help others is incredible — and it is safe to say that he is just getting started. To get in touch with Rohit and/or to learn more about QURE.AI, visit the site: http://qure.ai/

We would also love to hear what you’ve taken away from this week’s inspiring episode.

On the 10th Episode of “Brains Behind AI”, Ari and Natalie had the opportunity to speak with Redouane Ramdani, the Co-Founder and CEO of Snipfeed AI. Snipfeed AI is an AI-powered mobile content discovery platform for the Generation Z. Originally from France, Redouane studied entrepreneurshipat the Haas School of Business at Berkeley, His time in Silicon Valley led him to create Snipfeed, a platform for creators to host and distribute content all in one place. Snipfeed AI targets value added creators with specific niches, while using Artificial Intelligence to categorize and match content to the right audience. Snipfeed AI is not just a place for innovators and creators to showcase their talents, but to generate new streams of income through subscriptions, classes, live stream events, etc.

On the 9th Episode of “Brains Behind AI”, Ari and Natalie sat down to talk with Adit Jain -the Co-Founder and CEO of LEENA.AI. LEENA.AI helps enterprises transform employee experience with conversational AI, in particular, disrupting the way HR is performed. Using high-tech AI technology, we learned how Adit was able to see a window of opportunity in assisting HR companies with hiring new employees. Instead of playing it safe by stepping into a high-paying tech job, Adit and his colleagues decided to take a chance and follow the entrepreneurship path, which later resulted in founding LEENA.AI. Make sure to tune in to hear more on how Adit received funding for his company, how he shadowed large organizations to truly understand the problem that needed to be solved, and his advice for all aspiring entrepreneurs looking to start their own AI business.

Adit email: adit@leena.ai
Twitter: @adit93

Welcome to our 8th Episode of “Brains Behind AI”. In this episode we bring you an exclusive interview with Mohit Garg, the CEO and Co-founder of Oloid. AI, an identification and authentication company using facial recognition. On the show, Ari and Natalie had an open chat with Mohit about his 22+ years of experience building and scaling enterprise products and teams. With Oloid. AI being the second startup Mohit has built, we learn how he and his co-founder aligned with trends, formed the right team, and created the vision to successfully launch and grow his new product. Mohit has assisted many companies through the use of Oloid. AI, implementing touchless technology for contagion prevention, making it simple to ensure security. Starting with high value industries such as big pharma, warehouses and construction, Mohit takes us through his entrepreneurial journey of challenges, successes, and goals for the future.

https://www.oloid.ai/

On our 7th Episode of “Brains Behind AI”, Ari Yacobi and his co-host, Natalie Thomas, dive deep into the Healthcare Industry as they speak with the founder and CEO of Unlearn AI, Charles Fisher. Making massive waves in the pharmaceutical industry, Unlearn.AI is re-imagining clinical trials with Artificial Intelligence, and is the first company to create an intelligent control arm using digital twins. Throughout this episode, Charles takes us through how his interest in developing new machine learning techniques for medical data turned to tapping into a whole new paradigm in executing clinical trials. Unlearn AI’s platform presents the possibility to run clinical trials twice as fast with half as many people. Charles’ insight, knowledge, and expertise in building an AI company is profound, and he even shares his advice on entrepreneurship, it is a must listen for anyone interested in AI in healthcare and life sciences.

INFO:
www.unlearn.ai
Twitter: @charleskfisher