Welcome to a HumAIn first look, your exclusive story on how one company in the United States is helping the federal government businesses and the healthcare system confront the Coronavirus known as COVID 19. ElectrifAi is leading the global efforts in COVID 19 with innovative early detection systems, driven by machine learning that can detect COVID 19 in under 20 seconds without pre-trained or annotated data.
Listen into a HumAIn first look, your exclusive on ElectrifAi product release to help prevent the spread of Coronavirus through image recognition of infected lungs. ElectrifAi is open sourcing their technology with the Trump administration, major hospitals and pharmacies for AI for good. This is HumAIn.
Welcome to HumAIn. My name is David Yakobovitch, and I will be your host throughout this series, together we will explore AI through fireside conversations with industry experts, the business executives and AI researchers to leaders who advanced AI for all, HumAIn is the channel to release new AI products to learn about industry trends and to bridge the gap between humans and machines in the fourth industrial revolution. If you liked this episode, remember to subscribe and leave a review.
Listeners, welcome back to the HumAIn Podcast. Today, I have a special guest who is involved in the healthcare industry. His name is Ed Scott, and he’s the CEO of ElectrifAi. I met actually different members of the ElectrifAi team this past November, 2019 in New York city at the AI for healthcare conference, I got to see what their product’s doing in healthcare, and they were doing some amazing work then, but fast forwarding now into 2020, there’s some big breakthroughs that I’m looking for us to share the first unveil on the HumAIn Podcast.
Ed, thanks for being with us.
David is a pleasure to be with you.
Thank you. I’d love to hear whether you’re working on today and why is now an exciting time for ElectrifAi?
Let me begin for the listeners. Just set the table, just a touch and talk about what ElectrifAi is. We really are. The United States is oldest machine learning company that started off in the procurement area and then pivoted to create the first, fully integrated closed proprietary machine learning platform, everything from all the data ingestion and the transformation to the DQM, to the preparation for the models to the scoring, to the insights and so forth.
And a couple of years ago, we got control of the business, which had become a leader, but it sort of, lost its way along the way. And we transitioned that closed proprietary platform into a fully open platform built on the cloud, built on a common spark computational engine with the use of Kubernetes Docker containers and of course notebooks. So we gave all of our customers, are 200 odd customers that we have built up over 15 years in the healthcare industry, in the manufacturing industry, in the financial services industry and the federal practice area.
The reasons to say yes to ElectrifAi in this modern world. And that’s quite a transformation. And part of that transformation, David, as you and I were discussing earlier, is we not only change the entire re architecting to reengineer the entire technology stack, for our customers to make it more modern and open and agile. That’ll tell you what we also shifted from being more of a data science consulting type of company to a fledged world-class machine learning products company.
And that was a big shift. And that’s our competitive position on the landscape. There are cloud players, there were tool players. There are hybrids in between. There are very few that are actually sitting in selling to the C-suite and solving the C-suite problems with regard to revenue and cost reduction and risk reduction from a product perspective, from a SAS product perspective.
And that’s what we’ve done to put all of our products in that way. And this is done by world-class team. And if people want to see it, they can go and visit our website and see our leadership team www.electrifai.net. But I’ll tell you what. Over the course of our 15 years in machine learning and dealing with the fortune two 50 many in the hospital and the payer sector, David we’ve learned an awful lot.
And there’s a lot of benefits to focus. And one of the things that really drives this company is our focus on a certain number of verticals and a certain number of products. We are not all things to everybody. And in that product area is really where you see us shine. And so our products focus on Procurement AI, how does the company spend its money contracts AI, what rights and privileges or obligations as a company have or hidden risks actually, does it have it in its contracts, image, AI, which we’re going to get to a little bit later in the podcast, when we start discussing what we’re doing with data lakes and coronavirus and so forth, customer attention, customer acquisition, retention, and development, which is very important in the healthcare area with regard to patient steerage.
And then finally our revenue capture project where we help hospitals all across the world capture discharges all done in machine. So we are today, a company of 250 world-class data scientists and full stack software engineers spread across Shanghai, Delhi, Jersey city, and San Diego and we are highly focused on, as you point out on the healthcare industry, the financial services industry, the federal sector in TMT and highly focused on our products. And that benefit of focus really lets us get very intimate with our clients and up at the C-suite, where we solve the problems in ML, those chief marketing officers, chief financial officers, and CEOs are sharing with us.
What are their problems? You see the world doesn’t need more bandwidth, storage and compute. There’s eight guys out there doing it. And you and I both know who they are.
And there are a thousand tools companies. What the C-suite is essentially saying is will someone please help me solve my problem? And the problem is widespread. And one of the things that we know about that problem as you and I were talking earlier is that everybody’s data is disparate and it’s disconnected and it’s all over the place. It’s an SAP system, Oracle systems, IBM system Cerner’s systems, Epic systems, Allscripts systems. And there’s no way really to get at that data until now. And that truly is one of the core competencies of ElectrifAi. We are among the three or four best companies in the world with regard to data pipeline competency. I know that the Ft and the wall street journal talk about models and algorithms and all this kind of stuff all the time. But David, that’s not where the rubber hits the road, where the rubber hits the road is really on who can go out and get all that data. Who can bring it in quickly in an automated way who can map all that data in ETL in an automated way to get at that data transformation very quickly and get it into the models without the clean data. There’s no AI, that’s simply the case. And we are seeing it across the world in the most sophisticated enterprise customers. And of course in the hospital and the payer space.
And that’s the big challenge that’s out there in the world. That’s the state of data that no one really wants to talk about. Which is specifically that the data is stuck in all of these data lakes. And what we’re really good at is unfreezing those data lakes quickly and letting those CEOs, and that C-suite have insights that drive their business specifically with regard to cost reduction, risk reduction and revenue improvement. And that’s a little bit about, as we talk about ElectrifAi, that’s a little bit about who we are, but we feel finally, just to, as the final comment on this. Our place over as a machine learning products company, where our products are deep into the workflows of those C-suites, that’s where we live. And we believe that the folks who are closest to the end user customer at the end of the day will be the most successful.
Ed you and I both know that the state of data in the United States is a mess. There are so many platforms and data privacy is the big issue we’re experiencing in 2020 from personally identifiable information to security reviews to data breaches companies have the data and they don’t know how to work with that data.
And you’ve mentioned that now you’re coming up with a solution that Industry agnostic across healthcare, across government, across the federal areas. People are going to be able to better mine that data and extract those insights. What do you think are some of the key action steps that companies can do today to better use their data?
The first thing is, 50% of all of all projects with regard to AI and machine learning fail. David, you’ve been doing this as long as I have. And the reason we see for that is two things. Number one, There has to be leadership and momentum from the C-suite. It has to be driven down that this is incredibly important to our business. I’ll tell you what, once a year, who’s doing a good job of this is Richard Fain at Royal Caribbean. And Richard basically got us the entire group together real quick. It’s a big, obviously big, travel hospitality, cruise line company, massive company. And they got the entire company. Together about six months ago.
And he said, If we’re going to drive AI and ML into every single part of this business, and that’s what has to be done that leadership from the top in the digital world, if you are not embracing digitization in this world, I’ll tell you quite simply, David, your company’s dead, but it’s not enough embracing digitization. Doesn’t let you harness the power of AI and ML. When you look at a comprehensive AI or let’s just say machine learning program, you really have to understand what my objectives are. What are the objectives of the C-suite, the chief procurement officer, the chief marketing officer, the chief financial officer, the CEO, what are the objectives?
And clearly map those objectives, roles, responsibilities, accountability, very well mapped. And the fact is many companies don’t do that. They get the pressure from the board, or they get the pressure from the C-suite. Let’s turn to AI and ML, and it becomes an amorphous journey that ultimately ends in tears. So you need leadership and you need definition and clear scoping and project definition of what are our objectives, how are we going to do it? And who in the organization is going to be responsible? The second thing is, and we touched on this, everybody’s data is a mess. I don’t care what we say, what all of the software companies went out and they did to all of corporate America and to all the hospitals and the payers.
And they said, you got to create a data Lake. And if you create a data Lake, then your data is going to be ready for machine learning and David, you and I both know that is not true, just because you take all the data and you dump it in structured unstructured, whatever does not mean that it is ready to be used. Not by a long shot. That data has to be cleansed. That data has to be normalized. That data has to go through a DQM process. That data has to be crystal clean and ready for a data Mart or a data warehouse where it can then be touched for a specific application. Once again, the success of AI and ML really is contingent upon your capability and your competency in the data pipeline.
We have 15 years of experience in data pipeline experience for the world’s largest corporations and the world’s largest hospitals, you cannot replicate that out in the market. And that is why these corporations and the cloud providers, Google, Databricks, Azure, Oracle others are coming to us because of that competency and taking in massive amounts of data, we process terabytes of data everyday at ElectrifAi for all these companies.
And all of the work is really done. A substantial amount of it is done in that data pipeline arena David’s so you’ve got to have not only the project scope with accountability and responsibility, but then you have to get your data clean. You don’t have a choice and we help companies and hospitals do that each and every day. And it’s a pleasure, but it’s not easy. I will tell you it’s not easy.
I couldn’t agree with you more, a lot of listeners on HumAIn know that I have my data science standards, which is a workflow to productionize data science projects into cloud systems. But even on top of that, I recently came out with my five steps of design thinking for data science projects, and listeners would think that it’s all technical questions, but it cannot be further from the truth. These are business questions and business objectives, because you got to have the business to be successful. You need to have a strong business model so that your technical product can also grow. And from growth perspective, you and I were chatting offline earlier that ElectrifAi growing, you have some new recent hires and global expansion plans. Love to hear more about that.
I’d love to tell you about that, but do you mind if I just pick up on one thing you said, It’s incredibly important. The companies that succeed in the next 10, 20 years will fully embrace digitization, but it’s not enough. You’ve got to go beyond that. You then have to harness the power of AI and now, you have to do all that work on the ETL side as we’ve been discussing, but I’ll tell you something else David, here’s the challenge to corporate America and I’ll lay down that gauntlet. If you, as the CEO or the CFO of your firm, if you do not and cannot express a return on investment or return on invested capital from all the money you spent on data lakes and data marks and all the tools companies that have come, not walking through your door, all the tens of millions of dollars. I’ll tell you what you’re going to be out of a job.
Because you’re going to, you’re going to show the board that you don’t have the competency, the true data competency to organize your company and to participate in the full bouquet of what’s available in the AML world. It’s not enough just to get up in front of the analysts and say, we have made our path and put our path along the digital highway and proceeded along the digitization of our company. No, it’s not enough. You’ve got to actually put the fine point cross those T’s dot those I’s you gotta be able to say going forward. I spent this amount of money with this cloud provider, this amount of money with this tool provider, this amount of money with this ML product company, and this is my return on investment. And if you can’t do that in front of your board of directors, you’re going to be out in the new digital world.
What have we done to prepare for all this you’re right. We are growing leaps and bounds in our areas. Our areas of focus. Once again, our verticals are TMT healthcare, financial services and the federal space, why is that? It’s principally because we have the machine learning products that dial up the revenue, dial down the cost and dial down the risk. So let me give you an example. We run the procurement programs for many of the world’s largest corporations. CVS is one example. They use our machine learning to see exactly where they’re spending the money and what else they do.
Then they connect that spend to the contract so they can see exactly what vendors they’ve been spending, all their money and what the terms and conditions and the relationships with those vendors were contractually. For example, if they spent a hundred million dollars with one vendor, Were they supposed to get a discount of five or 10%?
They didn’t know in the past, today they know this is the power of machine learning to actually use AI and NLP to extract key terms, words, and conditions from contracts to show places like CVS. What’s your risk? What’s your opportunity? How can you reduce the number of suppliers that in doing that gain, leverage with the one that you actually annoyed? How can you reduce the suppliers who are not focused on social issues, social issues like human trafficking or social issues, like proper growing of crops and goods, things of that nature. These things actually now matter in the boardroom and the C-suite and well they should.
And it’s AI in it. Now that sits on top of all these contracts. Suppose these key terms, words, and conditions match it with the span that gives the world’s largest corporations the ability to see what’s going on. So we have built these products on procurement and contract, very focused to help people dial down their costs, dial down their risk and dial up their revenue.
And I’ll tell you, it matters today. It matters an awful lot because what is Coronavirus is not SARS. This is not by any stretch of the imagination. Coronavirus is impacting the entire world and we’re seeing it right now. We’re seeing the stress and the financial markets in the United States, March Friday, March the sixth. We’re thinking not only in the equity markets, we’re seeing in the debt markets with the spiking the CDs spreads and so forth across all of these companies, which is simply a reflection of the risk airlines face this existential moment right now, as a fixed cost business, they cannot survive with the loads and the yields that they’re currently experiencing, and you’re starting to see airlines in Europe, go bankrupt.
You will see that in the United States, the same will occur with hotel companies. The same with cruise line companies, anybody who’s got fixed expenses, transportation companies, when the yields and the loads drop the businesses can’t respond quickly enough, but the real issue there is they do not understand the risk that they are exposed to within their, their contracts, their contractual requirements we have through our contract AI, the ability to lift out those key terms, words, conditions, phrases, clauses, that show the risk that they’re under.
By the same token, what we saw in 2008 with the insurance companies was a massive dislocation. Those are the insurance companies and reinsurers are oftentimes the holders of last resort for risk. We’re now talking to some of the world’s largest insurance companies about what’s in their contracts and the sad and ugly fact about it.
And the same is true in the lending business, across the world, David, they don’t know what’s in the contracts. The money has been moving too quickly over the last 12 years, as you’ve not talked about. No. And so they need a product that can actually show them the risks. Contractor, it shows them the risk. So what we’ve done is built a suite of practical machine learning products, too, that lets the C-suite drive down the cost, drive down the risk and help drive revenue.
And that’s really powerful. And that’s why these cloud providers are beating a path to our door saying let’s partner because it’s gotta be about more than just bandwidth storage feeds and speeds. And that’s what we offer, but we can’t do this without our great team. And it’s not me. I have a team behind us. It’s a team effort here ElectrifAi. We talk about our culture, our culture of urgency, our culture of transparency, our culture of disruption re-invention and self-examination and our culture of teamwork.
That’s what it’s all about. When you look at who we put on the field to execute the shift to a fully fledged world-class machine learning products company. You look at individuals like Blooming Wang, the head of deep learning at Uber and Microsoft. You look at Greg McNulty, the former chief technology officer of CVS Health. You look at Steve Holodeck, the former data officer at CVS Health. You look at Jim McGowan, one of the senior data scientists from Bell Labs.
Data is in our blood, but it’s practical data and practical ML, and that’s why we go back to getting the data prepared and so forth. We couldn’t have made the shifts to this type of company to a world-class machine learning products company, without these folks, additional folks, Michael Fox head of our product from VMware, the NAVI had a program management proposals, presales operations, and pricing from CVS, Nancy Hornberger for IBM Watson, Deb Fahy from EMC and staples.
These are world-class people who have voted were there. They believe in the mission. We are going to change the way the world works in machine learning. They believe that our suite of practical machine learning products will help that C-suite in a very differentiated way. So it’s all done with that team.
So I just, it’s not just me and a vision. It’s a team that executes across the world 24 hours a day. We have 65 people in China, the same in India and the balance of our company here in the United States and every office, 24 hours a day is sharing technology, sharing product information and sharing knowledge.
And we are developing, delivering and selling NL products for our customers, each of the markets, 24 hours a day, we call it ElectrifAi 25 by seven. It’s that little extra digit. That’s the special part of our culture, where we truly understand the linkages between all of our functional areas. We’ve built this, the way you must build first principles X. We said, don’t tell us how it shouldn’t be done through the books. Don’t tell us how we did it in the past. Let’s do what’s right for the ML world and what our customers are going to demand. And we built a beauty.
So it’s amazing to hear how you’ve done this digital transformation and are continuing to grow and scale globally between both the United States and China and the remarks that you have shared Ed, could not have come more timely. As you mentioned, companies are going bankrupt right now because of the Coronavirus. Flybe out in the UK went bankrupt a couple of days ago. United airlines just cut 20% of their supply chain. I’m predicting here on HumAIn right now. We’re going to have the biggest startup bus since the 1999.com bubble.
But I don’t know, maybe I’m being too aggressive in my thoughts. Maybe a solution like ElectrifAi where I understand my contracts can better help me dial down that risk to hedge my bets. The reason I’m saying this is Andreessen Horowitz came out a couple of days ago, telling all the startups in their portfolio expect not to be raising capital through 2021 as a result of the coronavirus. I don’t know. Is it overreaction? Is that fair?
Let’s talk that look, I’ve known the Andreessen Horowitz for 20 years, I built Europe’s largest data center business called interaction over there. I’ve got a lot of respect for Dan and there and I’ll tell you what; they’re exactly right. And, I have to go to Sequoia as well. I noticed the COVID delivered a similar message to its portfolio companies last night. And we were in a once in a hundred year black Swan event here and the difference, principally. And, this is what these guys are thinking. So we have to tip our hat to them. They’re very bright and connected folks and very smart. Then have tremendous vision across the playing field. And I’ll tell you the name of it. The differences we talked to our head of China this morning, a wonderful woman, that incredible data scientist machine soon.
And, Jen and I were talking about this and she said, Ed, I’m really worried. And I’m worried because in this one case, the one thing about China that was effective in the control of COVID-19 was effectively, they could control where 750 million people moved or didn’t move. We cannot do that.
And so therefore the network effect of how this virus spreads will benefit from that inability to control it. And that’s why Ben Instacart, Bennett, Andreessen, and Sequoia, and others are actually pointing to this once in a hundred year black Swan event, because it’s actually real.
And what the world is facing is a massive demand and supply shock. And that’s going to where, It’s going to hurt in the technology business is going to hurt the small companies. And it’s going to hurt into companies that have tremendous fixed costs and they cannot adjust those fixed costs or that risk quick enough. And that’s why, in order to be able to do that, you got to see number one. What am I spending my money on? If I can cut, we got that for procurement AI. And then what’s in my contracts. What am I? Contractual rights and obligations that I have to deal with.
That’s contract AI. So we’re out there talking right now to the world’s largest insurance companies this very morning manufacturing companies, banking companies, hospital companies, payers, etcetera. This is real-time. So I don’t think that you are overstating this right now, simply because this country is not set up, for the, we move so seamlessly across borders, towns, States, etcetera.
No one has ever had to think about staying in place for two weeks. Most families aren’t set up for that. Most corporations are not set up for that. We ElectrifAi, we put a place to work from home policy in place we got to exactly this kind of black Swan event, and that’s all we transferred all of our knowledge and product and technical out to each of our offices in new China, in the US so that one went down.
We could continue to service our customers 24 hours a day, but you’re onto something here. And you’re going to see this pressure in the airline business. We have had a long-term relationship with United airlines. We love United airlines. And, we’re going to stand, we stood by them for five years. We just decided at a very difficult time recently and we’ll do it again. And we’ll help them, get out of here. Yes. And we’ll stand by most of the world’s corporations to do exactly the same, but you cannot have the practical products that help these guys. You look at the most to dial down the risk and that’s pretty filling now.
This is about speeds and feeds and instances and GPU’s and TPS. It’s about, can I get at them? He said, if it’s locked in all these systems, get at it, clean it. Let me see what’s here. Let me see what my risk is. Let me act quickly. My board is going to be demanding it.
It’s great to hear that United’s are up to the challenge with procure AI and the technology you’re offering through ElectrifAi and similar to other companies you’ve mentioned earlier, Ed, there’s real challenges around risk that you’re helping them solve. You mentioned CVS and Royal Caribbean. It’s been in the news that face masks and hand sanitizers are completely sold out. Even in New York city at CVS and Duane reeds, we’ve seen how rural Caribbeans had some of their ships, which have been off the coast of California, Japan, and elsewhere with nothing that they can do because of COVID 19. How are you helping many companies, whether it’s these or others, manage.
Let’s talk about that because, if you’re an airline or you’re a cruise line, What are your principal fixed costs there? Principally let’s take your line is you only really two major costs here in the airline industry, labor and fuel. So you got to know what’s in those contracts, particularly on the fuel side, they have forward bought forward, purchased all their fuel. There may be hedges on that. There may not be hedges on that, and they’re going to seek to get out of those fuel contracts.
And they’re going to do that with firms like Trafigura, Vitol Glencore that are the big traders they’re going to do that specifically with the refinery. Is that the Marathon’s? the Valero’s, the Exxo’s of the world and you are going to have one big catfight and it’s all going to be around what’s in the contract. And what are the terms of forced mature? Do we have it, do we not have it? How is it interpreted all that kind of stuff, but you can’t properly understand your risk. You can’t go as a CEO or CFO. You can’t go in front of the board unless you truly understand the risk.
And unless the only way to understand that risk is to use AI and ML to suck out all the terms, words, and conditions of those contracts, give you a view of all of it, so that you can make sense of that risk and you could begin to act. And this is where ML gets really practical because it saves time, cost, and money, and gets you to the decision point. But I’ll tell you what, we’re not just helping these companies, David is you and I. No, we’re doing our part for COVID-19 and, ElectrifAi, not just about practical machine learning products. We’re also about in addition, we’ve been dealing with the United States government, which is probably all I can say right now. We’ve been dealing with one of the largest hamster institutes and health institutes in the world that has come to us and said, we understand that you have a particular technology that can unlock or can facilitate the detection of COVID 19, and that is true.
We have a substantial, image analytics department here and expertise at ElectrifAi. And what we’ve been able to do is, automate the annotation of libraries of images, and to do that for some of the world’s leading hospitals. So imagine that you are Sloan Kettering, and you have 50 years of cancer images, livers, breast tumors, liver tumors, brain tumors, etcetera. That’s all, David, that’s all unstructured data and it’s very hard for those institutions to actually make sense of for research or other purposes. Anything about that data?
What we’ve been able to do is come up with a way to automate the annotation of that, and then turn all those pixels into ones and zeros and in a sense, mimic SQL and be able to search a database to say over the last 50 years, give the, all the liver tumors and have it come up. That is real power, for NL and it’s spreading into how we do with COVID. We’ve had institutions across the world send us images of infected lungs. We don’t need a lot because our particular system, the way we do this, we don’t require a lot of training data. We don’t require a hundred thousand images of COVID infected lungs. We require 10. That’s it.
And with that 10, we can define and pick out all the features of COVID as it relates to all the other lung and pulmonary related maladies, and be able to detect and tell someone whether you have COVID straight away. Why is that important? I’ll tell you why. Let’s say you’re a JFK or lax or Singapore or Beijing airport or Toronto or Heathrow. Everyone’s getting wanded. If we can see who has a very high temperature, we can get that person into an area. We can get a quick CT scan. We can take the data from that CT scan, run it directly through our model. And within minutes, tell someone whether you have COVID or not. And that’s true.
We can get that person segregated quickly into care versus them going into the cities and spreading it more as they get on the buses, subways, the hotels, the restaurants, etcetera, before they’re really sick. That’s a game changer and people have come to us and said, ElectrifAi, we didn’t know who you are before, but we know who you are now. And your technology is three years out ahead of the market.
This is so meaningful today. We’ve been seeing all over the news that there’s pictures and images of people in Italy, Iran, the United States, China and Korea with these temperature devices that are measuring infrared and seeing if they’re above a certain threshold, but you’re absolutely right. Add the temperature, how I look at it from machine learning and AI, it’s the first step in the process. It’s like a false positive, if my temperature is above a threshold, then that’s great. Let’s move forward with the CT scan. If not, no worries. But the temperature’s not enough to say if you have COVID
It could be the flu. It could be a cold, it could be many other things. And. It’s amazing to see how just in the last four days yourself at ElectrifAi and even Alibaba in China have gotten in on the CT scans, both of your companies over 96% accuracy at texting viral pneumonia, particularly around COVID 19. And it’s fast, as you mentioned, 10 scans are less and less than a minute, maybe even less than 20 seconds. What’s enabling this technology transformation?
I tell you what we have told the Trump and Pence administration is that we will give this technology away, see the United States and get this technology away to the world. And because that’s what AI for the good means. And that’s who ElectrifAi is. And that’s a very powerful statement.
It’s like, what we’ve seen with COVID-19 is that everyone is working together. I don’t think we’ve seen in the last hundred years, researchers collaborate to this extent and modern history, typically research in the medical field has gone to publication and now it’s every other day, Google and deep mind just decentralized the protein foldings yesterday on COVID it’s incredible. And that is such a blessing for history that you’re opening up access to say, we want everyone to be safe from this virus.
This is something we showed to Google and that they were very impressed with. And they said, how’d you guys do this, that’s all part of the secret sauce, which we won’t get into today. But, at the end of the day, it gets back to the discussion we were having. People’s data is either a mess or it’s frozen. That it’s locked and they can’t get at it. And that’s the principle problem in the world. And these data lakes of images are a perfect example of this. David, what we’re doing with the great hospitals of the world to take all of their scans and to automatically annotate those and make them searchable and, in a database. Not with inference, but with precision and if you know your data science and so forth, exactly what I’m talking about on that, to be able to do that with precision is really the key and to make it searchable, this is what practical machine learning means. Unfreeze your frozen data lake. All of these software companies have sold. Y’all the memes and the snake, you put all your data in a data lake and just be fine. It couldn’t be further from the truth.
And then the CFO gets another bill up. You need a data Mart or you need something else or a tool or this or that. And it’s, this is the continual problem we’ve seen in the technology business over the past 30 years. And you and I have seen this probably starting with ERP, coming all the way up to today, but I’ll tell you what you’re right. We haven’t seen, since probably 40, 50, maybe longer the collaboration of the world together to attack this issue. We are not different, we are not Americans, we are not Chinese, we are not French, we are not Indians, we are not Moroccans, we are citizens of the world and we have to solve this problem together and we have to solve it now. And it’s a very exciting time to be here. We’re glad to have been playing at our small part in doing that.
So as we’re continuing to see, as you’ve described the acceleration of COVID-19 globally, it’s now in over a hundred countries as soon there’ll be in every country and we’re not just seeing, different people being infected and quarantines and different processes putting into place, but that’s a whole transformation of what life is like. It’s almost as if we’re going back to the pre-digital days when we were just with horse and carriage, where we’re not able to go out with planes and cars and all these different devices, except we’re enabled by remote work and the future of work.
And, If I see one of the big blessings of COVID-19 it’s, we’re all coming closer together. We’re able to work together with software like Zoom and Slack and set up new policies that quite honestly should have been in place 10 years ago. But now companies are coming to grips with the reality.
Sounds like you’ve been on the forefront of those policies and you’re on the forefront as well on understanding how AI can help prevent the spread of coronavirus before it gets worse or however worse that may be.
That’s right. The great companies can be forced to adapt and they’re going to be forced to adapt and you’re seeing it. I’m looking now out from our position in Jersey city, look across the Hudson river here at Manhattan and the bottom of Manhattan. And I’m looking at all these great banks and many of whom were customers of ours across the river. And they’re going to be forced to adapt in the safety of their to protect the most important assets, which is their people.
And that’s certainly how we feel about our company. Our people are our most important assets and we put in place procedures and policies 60 days ago with regard to travel to India and China. Before this was in one, before this news or in the news, the way it is today. We informed our board, what we were doing, we began to talk about economic impacts to us and to other companies about the COVID-19, which at that time was still called Corona 60 days ago, or so, just to show you how quickly this is happening.
I guess part of the benefit of that is, we had 60, some odd, amazing data science professionals in China. And we lived from what was going on there in December and January, David, we heard from them and got a sense of their fear and talked to them every single day to let them know that we were standing right next to them. One team, one like your bot. We saw what was going on in Shanghai. We saw how families were forced to stay in their apartments. And when food was delivered to families when only one person could go out every two or three days and, to the Chinese people’s credit, they soldiered through that, but, and we saw it and we said, wow, this is occurring in China.
And Chinese new year is upon us. It’s only a matter of time before it’s here in the United States and it’s across Europe and so forth. And, sadly in this case we were right. And, but we put in place protections on travel, a work from home and we could actually shut our office today in Jersey city. And in San Diego, have everybody work from home and continue to deliver, develop and sell for our clients each and every day, 24 seven, no interruption. And I’ll tell you what, that’s a credit to our staff, when you have folks like Greg McNulty, the former CTO of CVS, these are people who think about risk.
We think about these things all the time, and that’s what we’re driven by our primary objective. He is here to make money for our shareholders and to also to continue to deliver for our clients uninterrupted. So we needed to think about this and put these policies and procedures in place well ahead and were ready for it. We’re absolutely ready for it.
And, businesses will adapt and will adjust to the new world of not necessarily conducting business by congregating in the office. But, those that are very adaptable and flexible and purposeful and very customer driven. They’re going to figure out how to organize themselves, remotely with Zoom stack, all these other things you correctly point out that are going to result in continued delivery of services to their clients. We’ll be right there with them to help.
That makes sense. As what you’re describing, the most important thing in 2020 is not that you need to have emotional intelligence EQ or actual intelligence at work IQ but having adaptability, quotient intelligence, or EQ, it’s how adaptable you are to the environment? And we don’t know where it’s going to go.
It’s amazing. This is part of our culture and it’s the heart, we’re on a mission and our mission is to change the way the world and our customers work in machine learning. But our culture, as I said earlier, our culture has been since the day we arrived, we sat down and we wrote what we wanted our culture to be and how to build it. A culture of urgency, transparency, disruption, re-invention, self-examination, we tell our people in our customers today we’ll serve you through ML today. But tomorrow, it might be a completely new technology and we’ll have to adapt. And that adaptability is at the heart of who we are.
It’s in our DNA. It’s what enabled us to make that transition from an amorphous data science company to world-class machine learning products company, which is, David is, they’re really very different, but a little bit of that fear, a little bit of that in that disruption, that urgency, that innovation, adaptability that we are. And if you’re not, if you’re in this particular environment, your company, you’re listening to this podcast, you’ve got, you got a lot of risk and financial contracts.
If you’re in the insurance industry or you got a lot of fixed costs, if you’re in the airline or other industry and contracts you need, you may need to get out of it. You need to understand your risk and rights. You better get out this pretty quickly and, sure we have the products to do that. I’m sure there are others out there as well, but, for those companies and those boards, you’ve got to get out this really quickly because this could go on. This could go on one or two quarters and many companies don’t have the financial wherewithal to survive two quarters.
Now at one of the big questions I want to ask. And a lot of people have been talking about this economist in the news lately is just what you mentioned, do we think it’s going to go on one or two quarters? Is it going to be a little dip which will be like, kind of a recession, but not really. Then the economy comes back. Then there’s a double dip. Obviously we’re not playing hearsay here, but all these things are possibilities.
And some of that’s driven by what we’ve seen in China in the last few days that there’s actually been relapsed cases of COVID 19. And we’re not sure whether that’s because hospitals have release patients back into Wuhan sooner than should be expected. Or if it’s just because the virus is mutating, we’ve seen now over 59 strains of the virus with two significant varieties. It’s incredible how not just the viruses adapt but also how we need to adapt to any situation that could be possible. Everything is game today.
That’s right. I don’t think we know the answer to your question, but I’ll go back to what is ahead of China is as soon said today, we have the week, meaning Jada in her perspective had the ability to actually control the movement of half a billion or three-quarters of a million people for a period of time, it appears that did arrest the rapid spread of the virus, whether it arrests, the second wave spread due to mutation is to be seen. But over here, we don’t have those same luxuries that the Chinese government has to actually control how people will conduct their lives, remove, or, their mobility and so forth.
And that’s just not who we are. And we are going to be faced. With that, I don’t see this actually going away in a quarter or two. I see this as a meaningful 2020 event and something that is going to impact evaluations and survivability of many companies. Ben Horowitz at Andreessen exactly right, my friends at Sequoia are exactly right. This is an existential moment. And, you better get at understanding your risk in your contracts. You better get to have the ability to see what your costs are and to use tools, to reduce that cost pretty quickly.
And you better see where you’re spending money and begin to husband cash as quickly as possible because you’re likely going to need it. And the difference between 2008 and today, there are many differences, that was principally a leverage in a housing and financial services, driven, problem and largely a problem in the credit markets with discipline and all of that as we saw with the fall of the AIG and the assumption of all the banks in defense system, this one’s a little bit different. This is a black Swan event that came out of nowhere.
And the problem is unlike 2008, the Fed and the ECB had the ability to grease the system and restarted by reliquefying and dropping those rates to near zero. And you remember tarp and harp and all these other programs that were out there. We don’t have those right now, David. These interest rates are low. I looked at the 30 year and the 10 year cause I’m an old credit guy coming from Apollo. That 10 years is around the lowest it’s been ever. And, we’ve never seen spreads like this or rates like this. Bond market is essentially telling you that there’s a real crisis out here and the markets and on the equity side, they don’t know what to do.
They’re not sure. And, I been do this for 25 years and this is the first time I can tell you that the smartest guys in the world that I know the control of these funds are telling me they don’t know what they really don’t know what’s going on, but you look at that 10 year and you look at that 30 year and they’re approaching that zero boundary. And every time that happens, or those kinds of shifts occur in the financial markets, the credit markets are much smarter than the equity markets. The equity markets have the upside unbounded credit markets yet you only get your what’s the new contract back. And so the bond market and the credit market analysts generally have a much finer pencil on the analytics and what those markets are telling us is there’s a real problem here.
And we ought to take note and I’ll tell you, I used to work for Leon Black and Mike Milken. And I’ll tell you two of the smartest guys I’ve ever met. Mike always used to say, when you see spreads in the high yield market, blow out, watch out. And, it’s beginning to percolate in the higher market.
So the fixed income markets are telling us there’s trouble for a while. And we ought to, we had to take.
That’s right. Time will tell, and speaking of time, our time is short, but I want to make a bet here on HumAIn that I love always trying to guess who the time person of the year is going to be every year. And, the time person of the year in 2020 will not be a person, but there will be the COVID 19 virus. So that’ll be an interesting bet to see if that comes true.
I’m going to take the other side of bet with that. The other side of that trade. If I might with respect. And I’m going to say that the time 2020 person of the year is humanity, because we’re going to come together as a global family and solve this, AI for the good, my friend.
I was just going to add to that, humans and AI can work together and Ed, I love making long bets, so definitely we’ll go into that long bets.
I appreciate that you’re offering ElectrifAi solution for AI for good as we’re tackling COVID-19. What final call to action would you like to offer to our listeners on HumAIn?
So I’ll tell you if corporations and hospitals and payers and providers, we’re here to help. We’re here to solve the problems, drive revenue, reduce costs, reduce risk. Get us at www.electrified.net or on Twitter at ElectrifAi or find us on LinkedIn. You’ll find our people, anybody ready to help 24 hours a day. We do it for the fortune two 50. We are here to help.
Ed Scott ElectrifAi. Thank you for joining us on the HumAIn Podcast.
David. My pleasure. Have a good evening.
Humans. Thanks for listening to this episode of HumAIn. My name is David Yakobovitch and if you’d like HumAIn, remember to click subscribe on Apple podcasts, Spotify or Luminary. Thanks for tuning in. And join us for our next episode. New releases are every Tuesday.