A few days ago, Andreessen Horowitz’s Martin Casado and Matt Bornstein published an interesting piece digging into the world of artificial intelligence (AI) startups, and, more specifically, how those companies perform as businesses. Core to the argument presented is that while founders and investors are wagering “that AI businesses will resemble traditional software companies,” the well-known venture firm is “not so sure.”
Given that TechCrunch cares a lot about startup business fundamentals, the notion that one oft-discussed and well-funded category of venture-backed startup might sport materially less attractive economics than we expected captured our attention.
The Andreessen Horowitz (a16z) perspective is straightforward, arguing that AI-focused companies have lesser gross margins than software companies due to cloud compute and human-input costs, endure issues stemming from “edge-cases” and enjoy less product differentiation from competing companies when compared to software concerns. Today, we’re drilling into the gross margin point, as it’s something inherently numerical that we can get other, informed market participants to weigh in on.
If a16z is correct about AI startups having slimmer gross margins than SaaS companies, they should — all other things held equal — be worth less per dollar of revenue generated; or in simpler terms, they should trade at a revenue multiple discount to SaaS companies, leaving the latter category of technology company still atop the valuation hierarchy.
This matters, given the amount of capital that AI-focused startups have raised.
Is a16z correct about AI gross margins? I wanted to find out. So this week I spoke to a number of investors from firms that have made AI-focused bets to get a handle on their views. Read the full a16z piece, mind. It’s interesting and worth your time.
Today we’re hearing from Rohit Sharma of True Ventures, Jeremy Kaufmann of Scale Venture Partners, Nick Washburn of Intel Capital and Ben Blume of Atomico. We’ll start with a digest of their responses to our questions, with their unedited notes at the end.
We asked our group of venture investors (selected with the help of research from TechCrunch’s Arman Tabatabai) three questions. The first dealt with margins themselves, the second dealt with resulting valuations and, finally, we asked about their current optimism interval regarding AI-focused companies.
Mangrove Capital Partners’ co-founder and CEO Mark Tluszcz is brimming with enthusiasm for what’s coming down the pipe from health tech startups.
Populations armed with mobile devices and hungry for verified and relevant information, combined with the promise of big data and AI, is converging, as he sees it, into a massive opportunity for businesses to rethink how healthcare is delivered, both as a major platform to plugging gaps in stretched public healthcare systems and multiple spaces in between — serving up something more specific and intimate.
Think health-focused digital communities, perhaps targeting a single sex or time of life, as we’re increasingly seeing in the femtech space, or health-focused apps and services that can act as supportive spaces and sounding boards that cater to the particular biological needs of different groups of people.
Tluszcz has made some savvy bets in his time. He was an early investor in Skype, turning a $2 million investment into $200 million, and he’s also made a tidy profit backing web building platform Wix, where he remains as chairman. But the long-time, early-stage tech investor has a new focus after a clutch of investments — in period tracking (Flo), AI diagnostics (K Health) and digital therapeutics (Happify) — have garnered enough momentum to make health the dominant theme of Mangrove Capital’s last fund.
“I really don’t think that there’s a bigger area and a more inefficient area today than healthcare,” he tells us. “One of the things that that whole space is missing is just good usability. And that’s something that Internet entrepreneurs do very well.”
Extra Crunch sat down for an in-depth conversation with Tluszcz to dig into the reasons why he’s so excited about mHealth (as Mangrove calls it) and probe him on some of the challenges that arise when building data-led AI businesses with the potential to deeply impact people’s lives.
The fund has also produced a healthcare report setting out some of its thinking.
This interview has been lightly edited for length and clarity
TechCrunch: Is the breadth of what can fall in the digital health or mHealth category part of why you’re so excited about the opportunities here?
Mark Tluszcz: I think if you take a step back, even from definitions for a moment, and you look around as an investor — and we as a firm, we happen to be thematically driven but no matter who you are — and you say where are there massive pockets of opportunity? And it’s typically in areas where there’s a lot of inefficiency. And anybody who’s tried to go to the doctor anywhere in Europe or around the world or tried to get an appointment with a therapist or whatever realizes how basically inefficient and arcane that process is. From finding out who the right person is, to getting an appointment and going there and paying for it. So healthcare looks to us like one of those arcane industries — the user experience, so to speak, could be so much better. And combine that with the fact that in most cases we know nothing as individuals about health — unless you read a few books and things. But it’s generally the one place where you’re the least informed in life. So you go see your GP and he or she will tell you something and you’re blindly going to take that pill they’re going to give you because you’re not well informed. You don’t understand it.
So I think that’s the exciting part about it. If I now look around and say if I now look at all the industries in the world — and of course there’s interesting stuff happening in financial services, and it continues to happen on commerce, and many, many places — but I really don’t think that there’s a bigger area and a more inefficient area today than healthcare.
You combine that with the power that we’re beginning to see in all these mobile devices — i.e. I have it in my pocket at all times. So that’s factor two. So one is the industry is potentially big and inefficient; two is there’s tools that we have easy to access it. And there has been — I think again — a general frustration on healthcare online I would say of when you go into a search engine, or you go into Web MD or Google or whatever, the general feedback it gives you is you’re about to have a heart attack or you’re about to die because those products are not designed specifically for that. So you as a consumer are confused because you’re not feeling well so you go online. The next day you go see your doctor and he or she says you didn’t go to Google did you, right? I know you’re probably freaked out at this point. So the second point is the tools are there.
Third I’d say is that artificial intelligence, machine learning, which is kind of in the process of gaining a lot of momentum, has made it that we’re able to start to dream that we could one day crunch sufficient data to get new insights into it. So I think you put those three factors together and say this seems like it could be pretty big, in terms of a space.
One of the things that that whole space is missing is just good usability. And that’s something that Internet entrepreneurs do very well. It’s figure out that usability side of it. How do I make that experience more enjoyable or better or whatever? In fact, you see it in fintech. One of the reasons, largely, that these neobanks are winning is that their apps are much better than what you have from the incumbents. There’s no other reason for it. And so I think there’s this big opportunity that’s out there, and it says all these factors lead you to this big, big industry. And then yes, that industry in itself is extremely large — all the way from dieting apps, you might think, all the way to healthy eating apps to longevity apps, to basic information about a particular disease, to basic general practitioner information. You could then break it down into female-specific products, male-specific products — so the breadth is very, very big.
But I think the common core of that is we as humans are getting more information and knowledge about how we are, and that is going to drive, I think, a massive adoption of these products. It’s knowledge, it’s ease of use, and it’s accessibility that just make it a dream come true if we can pull all these pieces together. And this is just speaking about the developed world. This gets even bigger potentially if I go to the third world countries where they don’t even have access to basic healthcare information or basic nutritional information. So I would say that the addressable market in investors’ jargon is just huge. Much more so than in any other industry that I know of today.
Is the fund trying to break that down into particular areas of focus within that or is the fund potentially interested in everything that falls under this digital health/mHealth umbrella?
We are a generalist investment firm. As a generalist investment firm we find these trends and then anything within these trends is going to pique our interest. Where we have made some investments has been really in three areas so far, and we’ll continue to broaden that base.
We’ve made an investment into a company called Flo. They are the number one app in the world for women to help track their menstrual cycles. So you look at that and go can that be big, not big, I don’t know. I can tell you they have 35M monthly active users, so it’s massive.
Now you might say, ‘Why do women need this to help them track their cycles because they’ve been tracking these menstrual cycles other ways for thousands of years?’ This is where, as an investor, you have to combine something like that with new behavioral patterns in people. And so if you look at the younger generation of people today they’re a generation that’s been growing up on notifications — the concept of being notified to do something. Or reminded to do something. And I think these apps do a lot of that as well.
My wife, who’s had two children, might say — which she did before I invested in the company — why would I ever need such an app? And I told her, “Unfortunately you’re the wrong demographic… because when I speak to an 18- year-old she says, ‘Ah, so cool! And by the way do you have an app to remind me to brush my teeth?’ So notifications is what I think what makes it interesting for that younger demographic.
And then curiously enough — this is again the magic of what technology can bring and great products can bring — Flo is a company created by two brothers. They had no particular direct experience of the need for the app. They knew the market was big. They obviously hired women who were more contextually savvy to the problem but they were able to build this fantastic product. And did a bunch of things within the product that they had taken from their previous lives and made it so that the user experience was just so much better than looking at a calendar on your phone. So today 35M women every month use this product tells you that there’s something there — that the tech is coming and that people want to use it. And so that’s one type of a problem, and you can think about a number of others that both males and females will have — for whom making that single user experience better could be interesting. And I could go from that to ten things that might be interesting for women and ten things that might specifically be interesting for men — you can imagine breaking that down. This is why, again, the space is so big. There are so many things that we deal with as men and women [related to health and biology].
Now for me the question is, as a venture investor, will that sub-set be big enough?
And that again is no different than if I was looking at any other industry. If I was in the telecommunications industry — well is voice calling big? Is messaging big enough? Is conference calling big enough? All that is around calling, but you start breaking it down and, in some cases, we’re going to conclude that it’s big enough or that it’s not big enough. But we’re going to have to go through the process of looking at these. And we’re seeing these thematic things pop up all over the place right now. All over Europe and in the U.S. as well.
It did take us a little time to say is this big enough [in the case of Flo] but obviously getting pregnant is big enough. And as a business, think about it: once you know a woman’s menstrual cycle process and then she starts feeding into the system, ‘I am pregnant; I’m going to have a child,’ you start having a lot of information about her life and you can feed a lot of other things to her. Because you know when she’s going to have a child, you can propose advice as well around here’s how the first few months go. Because, as we know, when you have your first child, you’re generally a novice. You’re discovering what all that means. And again you have another opportunity to re-engage with that user. So that’s something that I think is interesting as a space.
So the thematic space is going to be big — the femtech side and the male tech side. All of that’s going to play a big role. One could argue always there are the specific apps that are going to be the winners; we can argue about that. But right now I guess Flo is working very well because those people haven’t found such a targeted user experience in the more generic place. They feel as if they’re in a community of like-minded women. They have forums, they can talk, they have articles they can read, and it’s just a comfortable place for them to spend some time.
So Flo is the first example of a very specific play that we did in healthcare about a year and a half ago. The first investment, in fact, that we made in healthcare.
The second example is opposed to that — it’s a much more general play in healthcare. It’s a company called K Health . Now K Health looked at the world… and said what happens when I wake up at night and I have a pain and I do go to Google and I think I’m going to have a heart attack…. So can I build a product that would mimic, if you will, a doctor? So that I might be able to create an experience when I can have immediacy of information and immediacy of diagnostics on my phone. And then I could figure out what to do with that.
This is an Israeli company and they now have 5 million users in the U.S. that are using the app, which is downloadable from the U.S. app story only. What they did is they spent a year and a half building the technology — the AI and the machine learning — because what they did is they bought a very large dataset from an insurance company. The company sold it to them anonymized. It was personal health records for 2.5 million people for 20, years so we had a lot of information. A lot of this stuff was in handwritten notes. It wasn’t well structured. So it took them a long time to build the software to be able to understand all this information and break it down into billions of data parts that they could now manipulate. And the user experience is just like a WhatsApp chat with a robot.
Their desire is not to do what some other companies are doing, which is ‘answer ten questions and maybe you should talk to a doctor via Skype.’ Because their view was that — at the end of the day — in every developed country there are shortages of doctors. That’s true for the U.K.; it’s true for the U.S. If you predict out to 2030, there’s a huge hole in the number of GPs. Part of that is also totally understandable; who would want to be a GP today? I mean your job in the U.S. and the U.K. is you’re essentially a sausage factory. Come in and you’ve got 3 minutes with your customer. It’s not a great experience for the doctor or the person who goes to the doctor.
So K Health built this fantastic app and what they do is they diagnose you and they say based on the symptoms here’s what K thinks you have, and, by the way, here’s a medicine that people like you were treated with. So there’s an amazing amount of information that you get as a user, and that’s entirely free as a user experience. Their vision is that the diagnostic part will always be free.
There are 5 million people in the US.. using the app who are diagnosing. There are 25 questions that you go through with the robot, ‘K,’ and she diagnoses you. We call that a virtual doctor’s visit. We’re doing 15,000 of those a day. Think about the scale in which we’ve been able to go in a very short time. And all that’s free.
To some extent it’s great for people who can’t necessarily afford doctors — again, that’s not typically a European problem. Because socialized medicine in Europe has made that easy. But it is a problem in the U.S.; it is a problem in Africa, Asia, India and South America. There’s about 4 billion people around the world for whom speaking to a doctor is a problem.
K Health’s view is they’re bringing healthcare free to the world. And then ultimately how they make money will be things like if you want to speak to a doctor because you need a prescription for drugs. The doctor has access to K’s diagnostic and either agrees or disagrees with it and gives you a prescription to do that. And what we’re seeing is an interesting relationship which is where we wanted it to be. Of those 15,000 free doctor visits, less than one percent of those turn into I want to speak to a human and hence pay $15 (that’s the price they’re charging in the U.S. to actually converse with a human). In the U.S., by the way, about a quarter of the population — 75 million people — don’t have complementary insurance. That when they go to the doctor it’s $150. Isn’t that a crazy thing? You can’t afford complementary insurance but you could pay the highest price to go see a doctor. Such madness.
And then there’s a whole element of it’s simple, and it’s convenient. You’re sitting at home thinking, “Okay, I’m not feeling so well” and you’ve got to call a doctor, get an appointment, drive however long it takes, and wait in line with other sick people. So what we’re finding is people are discovering new ways of accessing information…. Human doctors also don’t have time to give empathy in an ever stretched socialized medicine country [such as in Spain]. So what we’re seeing also is a very quick change in user behavior. Two and a half years ago [when K Health started], many people would say I don’t know about that. Now they’re saying convenience — at least in Europe — is why that’s interesting. In the U.S. it’s price.
So that’s the second example; much more general company but one which has the ability to come and answer a very basic need: ‘I’m not feeling well.’
We have 5M users which means we have data on 5M people. On average, a GP in his life will see about 50,000 patients. If you think about just the difference — if you come to K, K has seen 5M people, your GP Max has seen 50k. So, statistically, the app is likely to be better. We know today, through benchmarks and all sorts of other stuff, is that the app is more accurate than humans.
So you look at where that’s heading in general medicine we’ve for a long time created this myth that doctors spent eight years learning a lot of information and as a result they’re really brainy people. They are brainy people but I believe that that learning process is going to be done faster and better through a machine. That’s our bet.
The third example of an investment that we’ve made in the health space is a company called Happify . They’re a company that had developed like a gamification of online treatment if you have certain sicknesses. So, for example, if you’re a little depressive you can use their app and the gamification process and they will help you feel healthier. So so far you’re probably scatching your head saying ‘I don’t know about that…” But that was how they started and then they realized that hang on you can either do that or you can take medicine; you can pop a pill. In fact what many doctors suggest for people who have anxiety or depression.
So then they started engaging with the drugs companies and they realized that these drug companies have a problem which is the patent expiry of their medication. And when patents expire you lose a lot of money. And so what’s very typical in the pharma industry is if you’re able to modify a medicine you can typically either extend or have a new patent. So Happify, what they’ve done with the pharma companies now, is said instead of modifying the medicine and adding something else to it — another molecule for instance — could we associate treatments which is medicine plus online software? Like a digital experience. And that has now been dubbed Digital Therapeutics — DTx — is the common term being used for them. And this company Happify is one of the first in the world to do that. They signed a very large deal with a company called Sanofi — one of the big drug makers. And that’s what they’re going to roll out. When doctors say to their patients I’m diagnosing you with anxiety or depression. Sanofi has a particular medication and they’re going to bundle it now with an online experience — and in all the tests that they’ve done, actually, when you combine the two, the patient is better off at the end of this treatment. So it’s just another example of why this whole space is so large. We never thought we’d be in any business with a pharma business because we’re tech investors. But here all of a sudden the ability to marry tech with medication creates a better end user experience for the patient. And that’s very powerful in itself.
So those are just three areas where we have actually put money in the health space but there are a number of areas that one looks at — either general or more specific.
Yeah it is big. And I think for us at least the more general it stays and it’s seen the more open minded we’re going to be. Because one thing you have to be as an investor, at least early stage like ours, completely open minded. And you can’t bias your process by your own experience. It has to stay very broad.
It’s also why I think clinician led companies and investors are not good — because they come with their own baggage. I think in this case, just like in any other industry, you have to say I’m not going to be polluted by the past and for me to change the experience going forward in any given area I have to fundamentally be ready to reinvent it.
You could propose a Theranos example as a counterpoint to that — but do you think investors in the health space have got over any fallout from that high profile failure at this point?
With that company one could argue who’s fault it really was. Clearly the founder lied and did all sorts of stuff but her investors let her do it. So to some extent the checks and balances just weren’t in place. I’m only saying that because I don’t think that should be the example by which we judge everything else. That’s just a case of a fraudster and dumb investors. That’s going to continue to exist in the future forever and who knows we might come across some of those but I don’t think it’s the benchmark by which one should be judging if healthcare is a good or viable investment. Again I look at Flo, 35M active users. I look at K Health, 5M users in the US who are now beginning to use doctors, order medicine through the platform. I think the simplicity, the ease of use, for me make it that it’s undeniable that this industry’s going to be completely shaken up through this tech. And we need it because at least in the Western world are health systems are so stretched they’re going to break.
Europe vs the US is interesting — because of the existence of public healthcare vs a lack of public healthcare. What difference does that make to the startup opportunities in health in Europe vs the US? Perhaps in Europe things have to be more supplementary to public healthcare systems but perhaps ultimately there isn’t that much difference if healthcare opportunities are increasingly being broken out and people are being encouraged to be more proactive about looking after their own health needs?
Yeah. Take K Health — where you look at it and say from a use example it’s clear that everywhere in the world, including US and Europe, people are going to recognize the simple ease of use and the convenience of it. If I had to spend money to then maybe make money then I would say maybe the US is slightly better because there’s 75M people who can’t afford a doctor and I might be able to sell them something more whereas in Europe I might not. I think it becomes a commercial question more than anything else. Certainly in the UK the NHS [National Health Service] is trying to do a lot of things. It is not a great user experience when you go to the doctor there. But at the end of the day I don’t think the difference between Europe-US makes much of a difference. I think this idea that what these apps want to tend towards — which is healthcare for everybody at a super cheap or free price-point — I think we have an advantage in Europe of thinking of it that way because that’s what we’ve had all our lives. So to some extent what I want to create online is socialized medicine for the world — through K Health. And I learnt that because I live here [in Europe].
Somebody in the US — not the 75M because they have nothing — but all the others, maybe they don’t think there’s a problem because they don’t recognize it. Our view with K Health is the opportunity to make socialized medicine a global phenomenon and hoping that in 95% of the cases access to the app is all you need. And in 5% of the cases you’re going to go the specialists that need to see you — and then maybe there’s enough money to go around for everybody.
And of course, as an investor, we’re interested in global companies. Again you see the theme: Flo, K Health, Happify, all those have a potential global footprint right off the bat.
I think with healthcare there are going to be play that could be national specific and maybe still going to be decent investments. You see in that in financial services. The neo banks are very country specific — whenever they try to get out of their country, like N26, they realize that life isn’t so easy when you go somewhere else. But healthcare I think we have an easier path to going global because there is such a pent up demand and a need for you to just feel good about yourself… Most of the people who go through [the K Health diagnostic] process just want peace of mind. If 95% of the 15k people who go through that process right now just go, “Phew, I feel okay” then we’ve accomplished something quite significant. And imagine if it’s not 15,000 it’s about 150,000 a day, which seems to be quite an easy goal. So healthcare allows us to dream that TAM — in investor terms, target addressable market — is big. I can realistically think with any one of the three companies that I’ve mentioned to you that we could have hundreds of millions of users around the world. Because there’s the need.
There are different regulatory regimes across markets, there are different cultural contexts around the world — do you see this as a winner takes all scenario for health platforms?
No. Not at all. I think ultimately it’s the user — in terms of his or her experience in using an app — that’s going to matter. Flo is not the only menstrual cycle app in the world; it just happens to be by far the biggest. But there’s others. So that’s the perfect example. I don’t think there’s going to be one winner takes it all.
There’s also (UK startup) Babylon Health which sounds quite similar to K Health…
Babylon does something different. They’re essentially a symptom checker designed to push you to have a Skype call with a human doctor…. It answers a bunch of questions, it’ll say, “Well, we think you have this, let’s connect you to a real doctor.” We did not want to invest in a company that ever did that because the real problem is there just aren’t enough doctors and then frankly you and I are not going to want to talk to a doctor from Angola. Because what’s going to happen is there aren’t enough doctors in the Western countries and the solution for those type of companies — Babylon is one, there’s others doing similar things — but if you become what we call lead generation just for doctors where you get a commission for bringing people to speak to a doctor you’re just displacing the problem from in your neighborhood to, broadly speaking, where are the humans? And I think as I said humans, they have their fallacies. If you really want to scale things big and globally you have to let software do it.
No it’s not a winner takes all — for sure.
So the vision is that this stuff starts as a supplement to existing healthcare systems and gradually scales?
Correct. I’ll give you an example in the U.S. with K Health. They have a deal with the second largest insurance company called Anthem. Their go-to-market brand is called Blue Cross, Blue Shield. It’s the second largest one in America… so why is this insurance company interested? Because they know that
So they’re going to be proposing it, in various forms, to all their customers by saying, “Before you go see a doctor, why don’t you try K?”
In this particular case with K there’s revenue opportunities from the insurance companies and also directly from the consumer, which makes it also interesting.
You did say different regions, different countries have different systems — yes absolutely and there’s no question that going international requires work. However, having said that, I would say a European, an Indonesian and a Brazilian are largely similar. There’s sometimes this fallacy that Asians, for instance, are so different from us as Western Europeans. And the truth is not really — when you look at it down into the DNA and the functions of the body and stuff like that. Which you do have to do, though. If we were to take K to Indonesia, for example, you do have to make sure that your AI engine has enough data to be able to diagnose some local stuff.
I’ll give you an example. When we launched K in the U.S. and we started off with New York, one of things you have to be able to diagnose is called Lyme disease which is what you get from a tick that bites you. Very, very prevalent in the Greater New York area. Not so much anywhere else in the States. But in New York, if you don’t have it it looks like a cold and then you get very sick. That’s very much a regional thing that you have to have. And so if we were to go to Indonesia we’d have to have thing like Malaria and Dengue. But all that is not so difficult. But yes, there’s some customization.
There are also certain conditions that can be more common for certain ethnicities. There are also differences in how women experience medical conditions vs men. So there can be a lot of issues around how localized health data is…
I would say that that is a very small problem that is a must to be addressed, but it’s a much smaller problem than you think it is. Much smaller. For instance, in the male to female thing — of course medical sometimes plays differently — but when you have a database of 5 million of which 3 million are women, and 2 million are men, you already have that data embedded. It is true that medications work better with certain races also. But again very tiny, very small examples of those. Most doctors know it.
At the big scale that may look very small but to an individual patient if a system is not going to pick up on their condition or prescribe them the right medicine that’s obviously catastrophic from their point of view…
Which is why, in the healthcare space, when you’re using AI and data-driven tools to do diagnosis there’s a lot of risk — and that’s part of the consideration for everyone playing in this space. So then the question is how do you break down that risk, how do you make that as small as possible and how do you communicate it to the users — if the proposition is free healthcare with some risk vs. not being able to afford going to the doctor at all?
I appreciate that, as a journalist, you’re trying to say this is a massive risk. I can tell you that as somebody who’s involved in these businesses it is a business risk we have to take into consideration but it is, by far, not insurmountable. We clearly have a responsibility as businesses to say: if I’m going to go to South East Asia, I need to be sure that I cover all the ‘weird’ things that we would not have in our database somewhere else. So I need to do that. How I go about doing that, obviously, is the secret sauce of each company. But you simply cannot launch your product in that region if you don’t solve — in this case Malaria and Dengue disease. It doesn’t make sense [for a general health app]. You’d have too many flaws and people will stop using you.
I don’t think that’s so much the case with Flo, for instance… But all these entrepreneurs who are designing these companies are fully aware that it isn’t a cookie-cutter, one-size fits all — but it is close to that. When you look at the exceptions. We’re not talking about I have to redo my database because 30% or 20% — it’s much, much smaller than that.
And, by the way, at the end of the day, the market will be the judge. In our case, when you go from an Israeli company into the U.S. and you have partners like Blue Cross, Blue Shield, they’ve tested the crap out of your product. And then you’re going to say well I’m going to do this now in Indonesia — well you get partners locally who’re going to help you do that.
One of the drawbacks about healthcare is, I would say, making sure that your product works in all these countries. And doesn’t have holes in the diagnostic side of it.
Which seems in many cases to boil down to getting the data. And that can be a big challenge. As you mentioned with K Health, there was also the need to structure the data as well — but fundamentally it’s taken Israeli population data and is using it in the U.S. You would say that model is going to scale? There are some counter examples, such as Google-owned DeepMind, which has big designs on using AI for healthcare diagnostics and has put a lot of effort into getting access to population-level health data from the NHS in the U.K., when — at the same time — Google has acquired a database of health records from the U.S. Department of Veterans Affairs. So there does seem to be a lot of effort going into trying to get very localized data but it’s challenging. Google perhaps has a head start because it’s Google. So the question then is how do startups get the data they need to address these kinds of opportunities?
If we’re just looking at K Health then obviously it’s a big challenge because you do have to get data in a way. But I would say again your example as well you have a U.S. database and does it match with a UK database. Again it largely does.
In that case the example is quite specific because the dataset Google has from the department of Veterans Affairs skews heavily male (93.6%). So they really do have almost no female data.
But that’s a bad dataset. That’s not anything else but a bad dataset.
It’s instructive that they’re still using it, though. Maybe that illustrates the challenge of getting access to population-level healthcare data for AI model making.
Maybe it does. But I don’t think this is one of those insurmountable things. Again, what we’ve done is we’ve bought a database that had data on 2.5 million patients, data over 20 years. I think that dataset equates extremely well. We’ve now seen it in U.S. markets for over a year. We’ve had nothing but positive feedback. We beat human doctors every time in tests. And so you look at it and you say they’re just business problems that we have to solve. But what we’re seeing is the consumer market is saying holy shit this is just such a better experience than I’ve ever had before.
So the human body — again — is not that complex. Most of the things that we catch are not that complex. And by the way we’ve grown our database — from the 2.5M that we bought we now have 5M. So we now have 2.5M Americans mixing into that database. And the way they diagnose you is they say based on your age, your size, you don’t smoke and so on — perhaps they say they have 300,000 people in their database like you and they’re benchmarking my symptoms against those people. So I think the smart companies are going to do these things very smartly. But you have to know what you’re using as a user as well… If you’re using that vs just a basic symptom checker — that I don’t think is a particularly great new user experience. But some companies are going to be successful doing that. At the end the great dream is how do you bring all this together and how do you give the consumer a fundamentally better choice and better information. That’s K Health.
Why couldn’t Google do the same thing? I don’t know. They just don’t think about it.
That’s a really interesting question — because Google is making big moves in health. They’re consolidating all their projects under one Google Health unit. Amazon is also increasingly interested in the space. What do you make of this big tech interest? Is that a threat or an opportunity for health startups?
Well if you think of it as an investor they’re all obviously buyers of the companies you’re going to build. So that’s a long term opportunity to sell your business. On the shorter term, does it make sense to invest in companies if all of a sudden the mammoth big players are there? By the way, that has been true for many, many other sectors as well. When I first invested in Skype in the early days people would say the telecom guys are going to crush you. Well they didn’t. But all of a sudden telecom, communication became the current that the Internet guys wanted — that’s why eBay ultimately bought us and why they all had their own messenger.
What the future’s made of we don’t know, but what we do know is that consumers want just the best experience and sometimes the best experience comes from people who are very innovative and very hungry as opposed to people who are working in very large companies. Venture capitalists are always investing in companies that somehow are competing one way or another with Amazon, Facebook, Google and all the big guys. It’s just that when you focus your energy on one thing you tend to do it better than if you don’t. And I’m not suggesting that those companies are not investing a lot of money. They are. And that’s because they realize that one of the currencies of the future is the ability to provide healthcare information, treatment and things like that.
You look at a large retail store like Wal-mart in America. Wal-mart serves largely a population that makes $50k or less. The lower income category in North America. But what are they doing to make you more loyal to them? They’re now starting to build into every Wal-mart doctor’s offices. Why would they do that? Is it because they actually know that if you make $50k or less there’s a high chance you don’t have an insurance and there’s a high chance that you can’t afford to go see a doctor. So they’re going to use that to say, “Hey, if you shop with us, instead of paying $150 for a doctor, it’ll be cheaper.” And we’re beginning to see so many examples like this — where all these companies are saying actually healthcare is the biggest and most important thing that somebody thinks about every day. And if we want to make them loyal to our brand we need to offer something that’s in the healthcare space. So the conclusion of why we’re so excited it we’re seeing it happen in real life.
Wal-mart does that — so when Amazon starts buying an online pharmacy I get why they’re doing that. They want to connect with you on an emotional level which is when you’re not feeling well.
So no, I don’t think we’re particularly worried about them. You have to respect they’re large companies, they have a lot of money and things like that. But that’s always been the case. We think that some of these will likely be bought by those players, some of those will likely build their own businesses. At the end of the day it’s who’s going to get that user experience right.
Google of course would like us all to believe that because they’re the search engine of the world they have the first rights to become the health search engine of the world. I tend to think that’s not true. Actually if you look at the history of Google they were the search engine of the world until they forgot about Amazon. And nowadays if you want to buy anything physical where do you search first? You don’t search on Google anymore — you search on Amazon.
But the space is big and there’s a lot of great entrepreneurs and Europe has a lot to offer I think in terms of taking our history of socialized medicine and saying how can tech power that to make it a better experience?
So what should entrepreneurs that are just thinking about this space — what should they be focusing on in terms of things to fix?
Right now the hottest are the three that I mentioned — because those are the ones that we’ve put money into and we’ve put money in because we think those are the hottest areas. I just think that anything where you feel deep conviction about or you’ve had some basic experience with the issue and the problem.
I simply do not think that clinicians can make this change — in any sector. If you look at those companies I mentioned none of the founders are clinicians in any way shape or form. And that’s why they’re successful. Now I’m not suggesting that you don’t have to have doctors on your staff. For sure. At K Health, we have 30 doctors…. What we’re trying to do is change the experience. So the founder, for instance. was a founder of a company called Vroom that buys and sells cars online in the States. When he started he didn’t know a whole lot about healthcare but he said to himself what I know is I don’t like the user experience. It’s a horrible user experience. I don’t like going to the doctor. I can change that.
So I would say if you’re heading into that space your first pre-occupation is how am I going to change the current user experience in a way that’s meaningful. Because that’s the only thing that people care about.
How is possible that two guys could come up with Flo? They were just good product people.
For me, that’s the driving factor — if you’re going to go into this, go into it saying you’re there to break an experience and make it just a way better place to be.
On the size of the opportunity I have seen some suggestions that health is overheated in investment terms. But perhaps that’s more true in the U.S. than Europe?
Any time an investor community gets hold of a theme and makes it the theme of the month or the year — like fintech was for ten years — I think it becomes overfunded because everybody ploughs into that. I could say yes to that statement sure. Lot of players, lot of actors. Money’s pouring in because people believe that the outcome could be big. So I don’t think it’s overheated. I think that we’ve only scratched the surface by doing certain things.
Some of the companies in the healthcare space that are either thinking of going public or are going public are companies that are pretty basic companies around connecting you with doctors online, etc. So I think that the innovation is really, really coming. As AI becomes real and we’re able to manage the data in an effective way… But again you’ve got to get the user experience right.
Flo in my experience — why it’s better than anything else — one is it’s just a great user experience. And then they have a forum on their app, and the forum is anonymized. And this is curious right. I think they anonymized it without knowing what it would do. And what it did was it allowed women to talk about stuff that perhaps they were not comfortable talking about stuff if people knew who they were. Number one issue? Abortion.
There’s a stigma out there around abortion and so by anonymizing the chat forum all of a sudden it created this opportunity for people to just exchange an experience. So that’s why I say the user experience for me is just at the core of that revolution that’s coming.
Why should it be such a horrific experience to be able to talk about that subject? Why should women be put in that position? So that’s why I think user experience is going to be so key to that.
So that’s why we’re excited. And of course the gambit is large. You think about the examples I gave — you can think of dietary examples, men’s health examples. When men turn 50 things start happening. Little things. But there’s at least 15 of those things that are 100% predictable… I just turned 50 and given there’s so much disinformation online I don’t know what’s true. So I think again there’s a fantastic opportunity for somebody to build companies around that theme — again, probably male and female separate.
Menopause would be another obvious one.
Exactly… You don’t know who you can talk to in many cases. So that’s another opportunity. And wow there are so many things out there. And when I go online today I‘m generally not sure if I can believe what I read unless it’s from a source that I can trust.
For 50 year old men erectile dysfunction is another taboo — a bit like the abortion taboo is for women. Men don’t even talk to their male friends about it… So if there was a place where you could go and learn about it I think there’s a big opportunity. I don’t think erectile dysfunction is a business, but I think how men age is one.
So it’s opportunities for communities around particular health/well-being issues.
Exactly. Because we’re looking for truths when we’re going through that experience ourselves.
The addressable market is massive. There’s men turning 50 every year and they’re probably all pretty interested to find out what are the ten or 15 things that could go wrong for them. There’s a lot of opportunities. It’s so broad. The challenge is you have to think about building it for people who are 50. You’re not building it for an 18-year-old. So the user experience again has to be somewhat different probably. And the healthcare goes all the way to the seniors. What are you looking for when you’re 75? So you see it treats anywhere from certainly from 18 all the way up across a broad-based spectrum of things. So it’s one of our major themes for the next five to ten years.
And so the idea of it being overheated in investment terms is a bit too abstract because there are specific areas that are very underinvested — like femtech. So it’s a case of spotting the particular bits of the healthcare opportunity that need more attention.
Yes. You’ve described it perfectly. In our more simpleton terms, we look at it and say if I look at the previous hot industry — fintech — you would end up with companies doing credit cards, companies doing bank accounts, companies doing lending, companies doing recovery — so many pieces of the value chain. In this case the value chain is humans.
We are even more complex than financial services have ever been, so I think the opportunities are even broader to break it down and build businesses that are going to satisfy certain sexes, maybe certain demographics, certain ages and all these kind of things that are out there. We are just so different.
TechCrunch Sessions: Robotics + AI brings together a wide group of the ecosystem’s leading minds on March 3 at UC Berkeley. Over 1000+ attendees are expected from all facets of the robotics and artificial intelligence space – investors, students, engineerings, C-levels, technologists, and researchers. We’ve compiled a small list of highlights of attendees’ companies and job titles attending this year’s event below.
STUDENTS & RESEARCHERS FROM:
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We’ve been dropping into the Australian startup scene increasingly over the years as the ecosystem has been building at an increasingly faster pace, most notably at our own TechCrunch Battlefield Australia in 2017. Further evidence that the scene is growing has come recently in the shape of the Pause Fest conference in Melbourne. This event has gone from strength to strength in recent years and is fast becoming a must-attend for Aussie startups aiming for both national international attention.
I was able to drop in ‘virtually’ to interview a number of those showcased in the Startup Pitch Competition, so here’s a run-down of some of the stand-out companies.
Medinet Australia is a health tech startup aiming to make healthcare more convenient and accessible to Australians by allowing doctors to do consultations with patients via an app. Somewhat similar to apps like Babylon Health, Medinet’s telehealth app allows patients to obtain clinical advice from a GP remotely; access prescriptions and have medications delivered; access pathology results; directly email their medical certificate to their employer; and access specialist referrals along with upfront information about specialists such as their fees, waitlist, and patient experience. They’ve raised $3M in Angel financing and are looking for institutional funding in due course. Given Australia’s vast distances, Medinet is well-placed to capitalize on the shift of the population towards much more convenient telehealth apps. (1st Place Winner)
Everty allows companies to easily manage, monitor and monetize Electric Vehicle charging stations. But this isn’t about infrastructure. Instead, they link up workplaces and accounting systems to the EV charging network, thus making it more like a “Salesforce for EV charging”. It’s available for both commercial and home charging tracking. It’s also raised an Angel round and is poised to raise further funding. (2nd Place Winner)
AI On Spectrum
It’s a sad fact that people with Autism statistically tend to die younger, and unfortunately, the suicide rate is much higher for Autistic people. “Ai on Spectrum” takes an accessible approach in helping autistic kids and their families find supportive environments and feel empowered. The game encourages Autism sufferers to explore their emotional side and arms them with coping strategies when times get tough, applying AI and machine learning in the process to assist the user. (3rd Place Winner)
Professional bee-keepers need a fast, reliable, easy-to-use record keeper for their bees and this startup does just that. But it’s also developing a software+sensor technology to give beekeepers more accurate analytics, allowing them to get an early-warning about issues and problems. Their technology could even, in the future, be used to alert for coming bushfires by sensing the changed behavior of the bees. (Hacker Exchange Additional Winner)
Rechargeable batteries for things like cars can be re-used again, but the key to employing them is being able to extend their lives. Relectrify says its battery control software can unlock the full performance from every cell, increasing battery cycle life. It will also reduce storage costs by providing AC output without needing a battery inverter for both new and 2nd-life batteries. Its advanced battery management system combines power and electric monitoring to rapidly the check which are stronger cells and which are weaker making it possible to get as much as 30% more battery life, as well as deploying “2nd life storage”. So far, they have a project with Nissan and American Electric Power and have raised a Series A of $4.5M. (SingularityU Additional Winner)
Sadly, seniors and patients can contract bedsores if left too long. People can even die from bedsores. Furthermore, hospitals can end up in litigation over the issue. What’s needed is a technology that can prevent this, as well as predicting where on a patient’s body might be worst affected. That’s what Gabriel has come up with: using multi-modal technology to prevent and detect both falls and bedsores. Its passive monitoring technology is for the home or use in hospitals and consists of a resistive sheet with sensors connecting to a system which can understand the pressure on a bed. It has FDA approval, is patent-pending and is already working in some Hawaiin hospitals. It’s so far raised $2m in Angel and is now raising money.
Here’s a taste of Pause Fest:
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Yellow, the accelerator program launched by Snap in 2018, has selected ten companies to join its latest cohort.
The new batch of startups coming from across the U.S. and international cities like London, Mexico City, Seoul and Vilnius are building professional social networks for black professionals and blue collar workers, fashion labels, educational tools in augmented reality, kids entertainment, and an interactive entertainment production company.
The list of new companies include:
The latest cohort from Snap’s Yellow accelerator
Since launching the platform in 2018, startups from the Snap accelerator have gone on to acquisition (like Stop, Breathe, and Think, which was bought by Meredith Corp.) and to raise bigger rounds of funding (like the voiceover video production toolkit, MuzeTV, and the animation studio Toonstar).
Every company in the Yellow portfolio will receive $150,000 mentorship from industry veterans in and out of Snap, creative office space in Los Angeles and commercial support and partnerships — including Snapchat distribution.
A year ago, he took the helm of Google’s cloud operations — which includes G Suite — and set about giving the organization a sharpened focus by expanding on a strategy his predecessor Diane Greene first set during her tenure.
It’s no secret that Kurian, with his background at Oracle, immediately put the entire Google Cloud operation on a course to focus on enterprise customers, with an emphasis on a number of key verticals.
So it’s no surprise, then, that the first highlight Kurian cited is that Google Cloud expanded its feature lineup with important capabilities that were previously missing. “When we look at what we’ve done this last year, first is maturing our products,” he said. “We’ve opened up many markets for our products because we’ve matured the core capabilities in the product. We’ve added things like compliance requirements. We’ve added support for many enterprise things like SAP and VMware and Oracle and a number of enterprise solutions.” Thanks to this, he stressed, analyst firms like Gartner and Forrester now rank Google Cloud “neck-and-neck with the other two players that everybody compares us to.”
If Google Cloud’s previous record made anything clear, though, it’s that technical know-how and great features aren’t enough. One of the first actions Kurian took was to expand the company’s sales team to resemble an organization that looked a bit more like that of a traditional enterprise company. “We were able to specialize our sales teams by industry — added talent into the sales organization and scaled up the sales force very, very significantly — and I think you’re starting to see those results. Not only did we increase the number of people, but our productivity improved as well as the sales organization, so all of that was good.”
He also cited Google’s partner business as a reason for its overall growth. Partner influence revenue increased by about 200% in 2019, and its partners brought in 13 times more new customers in 2019 when compared to the previous year.
Last week at Stanford, antitrust officials from the U.S. Department of Justice organized a day-long conference that engaged numerous venture capitalists in conversations about big tech. The DOJ wanted to hear from VCs about whether they believe there’s still an opportunity for startups to flourish alongside the likes of Facebook and Google and whether they can anticipate what — if anything — might disrupt the inexorable growth of these giants.
Most of the invited panelists acknowledged there is a problem, but they also said fairly uniformly that they doubted if more regulation was the solution.
Some of the speakers dismissed outright the idea that today’s tech incumbents can’t be outmaneuvered. Sequoia’s Michael Moritz talked about various companies that ruled the world across different decades and later receded into the background, suggesting that we merely need to wait and see which startups will eventually displace today’s giants.
He added that if there’s a real threat lurking anywhere, it isn’t in an overly powerful Google, but rather American high schools that are, according to Moritz, a poor match for their Chinese counterparts. “We’re killing ourselves; we’re killing the future technologists… we’re slowly killing the potential for home-brewed invention.”
Renowned angel investor Ram Shriram similarly downplayed the DOJ’s concerns, saying specifically he didn’t think that “search” as a category could never be again disrupted or that it doesn’t benefit from network effects. He observed that Google itself disrupted numerous search companies when it emerged on the scene in 1998.
Somewhat cynically, we would note that those companies — Lycos, Yahoo, Excite — had a roughly four-year lead over Google at the time, and Google has been massively dominant for nearly all of those 22 years since (because of, yes, its network effects).
TechCrunch is returning to U.C. Berkeley on March 3 to bring together some of the most influential minds in robotics and artificial intelligence. Each year we strive to bring together a cross-section of big companies and exciting new startups, along with top researchers, VCs and thinkers.
In addition to a main stage that includes the likes of Amazon’s Tye Brady, U .C. Berkeley’s Stuart Russell, Anca Dragan of Waymo, Claire Delaunay of NVIDIA, James Kuffner of Toyota’s TRI-AD, and a surprise interview with Disney Imagineers, we’ll also be offering a more intimate Q&A stage featuring speakers from SoftBank Robotics, Samsung, Sony’s Innovation Fund, Qualcomm, NVIDIA and more.
Alongside a selection of handpicked demos, we’ll also be showcasing the winners from our first-ever pitch-off competition for early-stage robotics companies. You won’t get a better look at exciting new robotics technologies than that. Tickets for the event are still available. We’ll see you in a couple of weeks at Zellerbach Hall.
8:30 AM – 4:00 PM
Registration Open Hours
General Attendees can pick up their badges starting at 8:30 am at Lower Sproul Plaza located in front of Zellerbach Hall. We close registration at 4:00 pm.
10:00 AM – 10:05 AM
10:05 AM – 10:25 AM
The UC Berkeley professor and AI authority argues in his acclaimed new book, “Human Compatible,” that AI will doom humanity unless technologists fundamentally reform how they build AI algorithms.
10:25 AM – 10:45 AM
Maxar Technologies has been involved with U.S. space efforts for decades, and is about to send its sixth (!) robotic arm to Mars aboard NASA’s Mars 2020 rover. Lucy Condakchian is general manager of robotics at Maxar and will speak to the difficulty and exhilaration of designing robotics for use in the harsh environments of space and other planets.
10:45 AM – 11:05 AM
Amazon Robotics’ chief technology officer will discuss how the company is using the latest in robotics and AI to optimize its massive logistics. He’ll also discuss the future of warehouse automation and how humans and robots share a work space.
11:05 AM – 11:15 AM
Live Demo from the Stanford Robotics Club
11:30 AM – 12:00 PM
Join one of the foremost experts in artificial intelligence as he signs copies of his acclaimed new book, Human Compatible.
11:35 AM – 12:05 PM
Can robots help us build structures faster, smarter and cheaper? Built Robotics makes a self-driving excavator. Toggle is developing a new fabrication of rebar for reinforced concrete, Dusty builds robot-powered tools and longtime robotics pioneers Boston Dynamics have recently joined the construction space. We’ll talk with the founders and experts from these companies to learn how and when robots will become a part of the construction crew.
12:15 PM – 1:00 PM
Join this interactive Q&A session on the breakout stage with three of the top minds in corporate VC.
1:00 PM – 1:25 PM
Select, early-stage companies, hand-picked by TechCrunch editors, will take the stage and have five minutes to present their wares.
1:15 PM – 2:00 PM
Your chance to ask questions of some of the most successful robotics founders on our stage
1:25 PM – 1:50 PM
Leading investors will discuss the rising tide of venture capital funding in robotics and AI. The investors bring a combination of early-stage investing and corporate venture capital expertise, sharing a fondness for the wild world of robotics and AI investing.
1:50 PM – 2:15 PM
As robots become an ever more meaningful part of our lives, interactions with humans are increasingly inevitable. These experts will discuss the broad implications of HRI in the workplace and home.
2:15 PM – 2:40 PM
Autonomous driving is set to be one of the biggest categories for robotics and AI. But there are plenty of roadblocks standing in its way. Experts will discuss how we get there from here.
2:15 PM – 3:00 PM
Join this interactive Q&A session on the breakout stage with some of the greatest investors in robotics and AI
Imagineers from Disney will present start of the art robotics built to populate its theme parks.
3:10 PM – 3:35 PM
This summer’s Tokyo Olympics will be a huge proving ground for Toyota’s TRI-AD. Executive James Kuffner and Max Bajracharya will join us to discuss the department’s plans for assistive robots and self-driving cars.
3:15 PM – 4:00 PM
Join this interactive Q&A session on the breakout stage with some of the greatest engineers in robotics and AI.
3:35 PM – 4:00 PM
In 1920, Karl Capek coined the term “robot” in a play about mechanical workers organizing a rebellion to defeat their human overlords. One hundred years later, in the context of increasing inequality and xenophobia, the panelists will discuss cultural views of robots in the context of “Robo-Exoticism,” which exaggerates both negative and positive attributes and reinforces old fears, fantasies and stereotypes.
4:00 PM – 4:10 PM
Live Demo from Somatic
4:10 PM – 4:35 PM
Machine learning and AI models can be found in nearly every aspect of society today, but their inner workings are often as much a mystery to their creators as to those who use them. UC Berkeley’s Trevor Darrell, Krishna Gade of Fiddler Labs and Karen Myers from SRI will discuss what we’re doing about it and what still needs to be done.
4:35 PM – 5:00 PM
The benefits of robotics in agriculture are undeniable, yet at the same time only getting started. Lewis Anderson (Traptic) and Sebastien Boyer (FarmWise) will compare notes on the rigors of developing industrial-grade robots that both pick crops and weed fields respectively, and Pyka’s Michael Norcia will discuss taking flight over those fields with an autonomous crop-spraying drone.
5:00 PM – 5:25 PM
Robotics and AI are the future of many or most industries, but the barrier of entry is still difficult to surmount for many startups. Speakers will discuss the challenges of serving robotics startups and companies that require robotics labor, from bootstrapped startups to large scale enterprises.
5:30 PM – 7:30 PM
Unofficial After Party, (Cash Bar Only)
Come hang out at the unofficial After Party at Tap Haus, 2518 Durant Ave, Ste C, Berkeley
We only have so much space in Zellerbach Hall and tickets are selling out fast. Grab your General Admission Ticket right now for $350 and save 50 bucks as prices go up at the door.
Student tickets are just $50 and can be purchased here. Student tickets are limited.
Startup Exhibitor Packages are sold out!
Google Cloud today announced that its new Seoul region, its first in Korea, is now open for business. The region, which it first talked about last April, will feature three availability zones and support for virtually all of Google Cloud’s standard service, ranging from Compute Engine to BigQuery, Bigtable and Cloud Spanner.
With this, Google Cloud now has a presence in 16 countries and offers 21 regions with a total of 64 zones. The Seoul region (with the memorable name of asia-northeast3) will complement Google’s other regions in the area, including two in Japan, as well as regions in Hong Kong and Taiwan, but the obvious focus here is on serving Korean companies with low-latency access to its cloud services.
“As South Korea’s largest gaming company, we’re partnering with Google Cloud for game development, infrastructure management, and to infuse our operations with business intelligence,” said Chang-Whan Sul, the CTO of Netmarble. “Google Cloud’s region in Seoul reinforces its commitment to the region and we welcome the opportunities this initiative offers our business.”
Over the course of this year, Google Cloud also plans to open more zones and regions in Salt Lake City, Las Vegas and Jakarta, Indonesia.
TC Sessions: Mobility 2020 is gearing up to be a lit event. The one-day event, taking place May 14 in San Jose, has just added Dmitry Shevelenko, co-founder and president of an automatic repositioning startup for micromobility vehicles. Yes, that means we’ll be having autonomous scooters rolling around onstage. #2020
Tortoise, which recently received approval to deploy its tech in San Jose, is looking to become an operating system of sorts for micromobility vehicles. Just how Android is the operating system for a number of mobile phones, Tortoise wants to be the operating system for micromobility vehicles.
Given the volume of micromobility operators in the space today, Tortoise aims to make it easier for these companies to more strategically deploy their respective vehicles and reposition them when needed. Using autonomous technology in tandem with remote human intervention, Tortoise’s software enables operators to remotely relocate their scooters and bikes to places where riders need them, or, where operators need them to be recharged. On an empty sidewalk, Tortoise may employ autonomous technologies, while it may rely on humans to remotely control the vehicle on a highly trafficked city block.
Before co-founding Tortoise, Shevelenko served as Uber’s director of business development. While at Uber, Shevelenko helped the company expand into new mobility and led the acquisition of JUMP Bikes . Needless to say, Shevelenko is well-versed to talk about the next opportunities in micromobility.
Other speakers at TC Sessions: Mobility 2020 include Waymo COO Tekedra Mawakana; Uber’s director of Policy, Cities & Transportation, Shin-pei Tsay; and Argo AI co-founder and CEO Bryan Salesky.
Tickets are on sale now for $250 (early-bird status). After April 9, tickets go up, so be sure to get yours before that deadline. If you’re a student, tickets cost just $50.
Early-stage startups in the mobility space can book an exhibitor package for $2,000 and get four tickets and a demo table. Packages allow you to get in front of some of the biggest names in the industry and meet new customers. Book your tickets here.
As cybercrime continues to evolve and expand, a startup that is building a business focused on endpoint security has raised a big round of funding. SentinelOne — which provides a machine learning-based solution for monitoring and securing laptops, phones, containerised applications and the many other devices and services connected to a network — has picked up $200 million, a Series E round of funding that it says catapults its valuation to $1.1 billion.
The funding is notable not just for its size but for its velocity: it comes just eight months after SentinelOne announced a Series D of $120 million, which at the time valued the company around $500 million. In other words, the company has more than doubled its valuation in less than a year — a sign of the cybersecurity times.
This latest round is being led by Insight Partners, with Tiger Global Management, Qualcomm Ventures LLC, Vista Public Strategies of Vista Equity Partners, Third Point Ventures, and other undisclosed previous investors all participating.
Tomer Weingarten, CEO and co-founder of the company, said in an interview that while this round gives SentinelOne the flexibility to remain in “startup” mode (privately funded) for some time — especially since it came so quickly on the heels of the previous large round — an IPO “would be the next logical step” for the company. “But we’re not in any rush,” he added. “We have one to two years of growth left as a private company.”
While cybercrime is proving to be a very expensive business (or very lucrative, I guess, depending on which side of the equation you sit on), it has also meant that the market for cybersecurity has significantly expanded.
Endpoint security, the area where SentinelOne concentrates its efforts, last year was estimated to be around an $8 billion market, and analysts project that it could be worth as much as $18.4 billion by 2024.
Driving it is the single biggest trend that has changed the world of work in the last decade. Everyone — whether a road warrior or a desk-based administrator or strategist, a contractor or full-time employee, a front-line sales assistant or back-end engineer or executive — is now connected to the company network, often with more than one device. And that’s before you consider the various other “endpoints” that might be connected to a network, including machines, containers and more. The result is a spaghetti of a problem. One survey from LogMeIn, disconcertingly, even found that some 30% of IT managers couldn’t identify just how many endpoints they managed.
“The proliferation of devices and the expanding network are the biggest issues today,” said Weingarten. “The landscape is expanding and it is getting very hard to monitor not just what your network looks like but what your attackers are looking for.”
This is where an AI-based solution like SentinelOne’s comes into play. The company has roots in the Israeli cyberintelligence community but is based out of Mountain View, and its platform is built around the idea of working automatically not just to detect endpoints and their vulnerabilities, but to apply behavioral models, and various modes of protection, detection and response in one go — in a product that it calls its Singularity Platform that works across the entire edge of the network.
“We are seeing more automated and real-time attacks that themselves are using more machine learning,” Weingarten said. “That translates to the fact that you need defence that moves in real time as with as much automation as possible.”
But nonetheless, its product has seen strong uptake to date. It currently has some 3,500 customers, including three of the biggest companies in the world, and “hundreds” from the global 2,000 enterprises, with what it says has been 113% year-on-year new bookings growth, revenue growth of 104% year-on-year, and 150% growth year-on-year in transactions over $2 million. It has 500 employees today and plans to hire up to 700 by the end of this year.
One of the key differentiators is the focus on using AI, and using it at scale to help mitigate an increasingly complex threat landscape, to take endpoint security to the next level.
“Competition in the endpoint market has cleared with a select few exhibiting the necessary vision and technology to flourish in an increasingly volatile threat landscape,” said Teddie Wardi, MD of Insight Partners, in a statement. “As evidenced by our ongoing financial commitment to SentinelOne along with the resources of Insight Onsite, our business strategy and ScaleUp division, we are confident that SentinelOne has an enormous opportunity to be a market leader in the cybersecurity space.”
Weingarten said that SentinelOne “gets approached every year” to be acquired, although he didn’t name any names. Nevertheless, that also points to the bigger consolidation trend that will be interesting to watch as the company grows. SentinelOne has never made an acquisition to date, but it’s hard to ignore that, as the company to expand its products and features, that it might tap into the wider market to bring in other kinds of technology into its stack.
“There are definitely a lot of security companies out there,” Weingarten noted. “Those that serve a very specific market are the targets for consolidation.”
Microsoft announced a major update to its Dynamics 365 product line today, which correlates to the growing amount of data in the enterprise, and how to collect and understand that data to produce better customer experiences.
This is, in fact, the goal of all vendors in this space including Salesforce and Adobe, who are also looking to help improve the customer experience. James Philips, who was promoted to president of Microsoft Business Applications just this week, says that Microsoft has also been keenly focused on harnessing the growing amount of data and helping make use of that inside the applications he is in charge of.
“To be frank every single thing that we’re doing at Microsoft, not just in business applications but across the entire Microsoft Cloud, is on the back of that vision that data is coming out of everything, and that those organizations that can collect that data, harmonize it and reason over it will be in a position to be proactive versus reactive,” Philips told TechCrunch.
For starters, the company is adding functionality to its customer data platform (CDP), a concept all major vendors (and a growing group of startups) have embraced. It pulls together all of the customer data from various systems into one place, making it easier to understand how the customer interacts with you with the goal of providing better experiences based on this knowledge. Microsoft’s CDP is called Customer Insights.
The company is adding some new connectors to help complete that picture of the customer. “We’re adding new first- and third-party data connections to Customer Insights that allow our customers to understand, for example audience memberships, brand affinities, demographic, psychographic and other characteristics of customers that are stored and then harnessed from Dynamics 365 Customer Insights,” Philips said.
All of this, might make you wonder how they can collect this level of data and maintain GDPR/CCPA kind of compliance. Philips says that the company has been working on this for some time. “We did work at the company level to build a system that allows us and our customers to search for and then delete information about customers in each product group within Microsoft including my organization,” he explained.
The company has also added new sales forecasting tools and Dynamics 365 Sales Engagement Center. The first allows companies to tap into all this data to better predict the customers who sales is engaged with that are most likely to turn into sales. The second gives inside sales teams tools like next best action. These are not revolutionary by any means in the CRM space, but do provide new capabilities for Microsoft customers.
The operations side is related to what happens after the sale when the company begins to collect money and report revenue. To that end, the company is introducing a new product called Dynamic 365 Finance Insights, which you can think of as Customer Insights, except for money.
“This product is designed to help our customers predict and accelerate their cash flow. It’s designed specifically to identify opportunities where to focus your energy, where you may have the best opportunity to either close accounts payables or receivables or the opportunity to understand where you may have cash shortfalls,” Philips said.
Finally the company is introducing Dynamics 365 Project Operations,which provides a way for project-based business like construction, consulting and law to track the needs of the business.
“Those organizations, who are trying to operate in a project-based way now have with Dynamics 365 Project Operations, what we believe is the most widely used project management capability in Microsoft Project being joined now with all of the back-end capabilities for selling, accounting and planning that Dynamic 365 offers, all built on the same Common Data Platform, so that you can marry your front-end operations and operational planning with your back-end resource planning, workforce planning and operational processes,” he explained.
All of these tools are designed to take advantage of the growing amount of data coming into organizations, and provide ways to run businesses in a more automated and intelligent fashion that removes some of the manual steps involved in running a company.
To be clear, Microsoft is not alone in offering this kind of intelligent functionality. It is part of a growing movement to bring intelligence to all aspects of enterprise software, regardless of vendor.
European Union lawmakers have set out a first bundle of proposals for a new digital strategy for the bloc, one that’s intended to drive digitalization across all industries and sectors — and enable what Commission President Ursula von der Leyen has described as ‘A Europe fit for the Digital Age‘.
It could also be summed up as a “scramble for AI,” with the Commission keen to rub out barriers to the pooling of massive European data sets in order to power a new generation of data-driven services as a strategy to boost regional competitiveness vs China and the U.S.
Pushing for the EU to achieve technological sovereignty is a key plank of von der Leyen’s digital policy plan for the 27-Member State bloc.
Presenting the latest on her digital strategy to press in Brussels today, she said: “We want the digital transformation to power our economy and we want to find European solutions in the digital age.”
The top-line proposals are:
The full data strategy proposal can be found here.
While the Commission’s white paper on AI “excellence and trust” is here.
Next steps will see the Commission taking feedback on the plan — as it kicks off public consultation on both proposals.
A final draft is slated by the end of the year after which the various EU institutions will have their chance to chip into (or chip away at) the plan. So how much policy survives for the long haul remains to be seen.
At a press conference following von der Leyen’s statement Margrethe Vestager, the Commission EVP who heads up digital policy, and Thierry Breton, commissioner for the internal market, went into some of the detail around the Commission’s grand plan for “shaping Europe’s digital future”.
The digital policy package is meant to define how we shape Europe’s digital future “in a way that serves us all”, said Vestager.
The strategy aims to unlock access to “more data and good quality data” to fuel innovation and underpin better public services, she added.
The Commission’s digital EVP Margrethe Vestager discussing the AI whitepaper
Collectively, the package is about embracing the possibilities AI create while managing the risks, she also said, adding that: “The point obviously is to create trust, rather than fear.”
She noted that the two policy pieces being unveiled by the Commission today, on AI and data, form part of a more wide-ranging digital and industrial strategy with additional proposals still to be set out.
“The picture that will come when we have assembled the puzzle should illustrate three objectives,” she said. “First that technology should world for people and not the other way round; it is first and foremost about purpose The development, the deployment, the uptake of technology must work in the same direction to make a real positive difference in our daily lives.
“Second that we want a fair and competitive economy — a full Single Market where companies of all sizes can compete on equal terms, where the road from garage to scale up is as short as possible. But it also means an economy where the market power held by a few incumbents cannot be used to block competition. It also means an economy were consumers can take it for granted that their rights are being respected and profits are being taxed where they are made”
Thirdly, she said the Commission plan would support “an open, democratic and sustainable society”.
“This means a society where citizens can control the data that they provide, where digit platforms are accountable for the contents that they feature… This is a fundamental thing — that while we use new digital tools, use AI as a tool, that we build a society based on our fundamental rights,” she added, trailing a forthcoming democracy action plan.
Digital technologies must also actively enable the green transition, said Vestager — pointing to the Commission’s pledge to achieve carbon neutrality by 2050. Digital, satellite, GPS and sensor data would be crucial to this goal, she suggested.
“More than ever a green transition and digital transition goes hand in hand.”
On the data package Breton said the Commission will launch a European and industrial cloud platform alliance to drive interest in building the next gen platforms he said would be needed to enable massive big data sharing across the EU — tapping into 5G and edge computing.
“We want to mobilize up to €2BN in order to create and mobilize this alliance,” he said. “In order to run this data you need to have specific platforms… Most of this data will be created locally and processed locally — thanks to 5G critical network deployments but also locally to edge devices. By 2030 we expect on the planet to have 500BN connected devices… and of course all the devices will exchange information extremely quickly. And here of course we need to have specific mini cloud or edge devices to store this data and to interact locally with the AI applications embedded on top of this.
“And believe me the requirement for these platforms are not at all the requirements that you see on the personal b2c platform… And then we need of course security and cyber security everywhere. You need of course latencies. You need to react in terms of millisecond — not tenths of a second. And that’s a totally different infrastructure.”
“We have everything in Europe to win this battle,” he added. “Because no one has expertise of this battle and the foundation — industrial base — than us. And that’s why we say that maybe the winner of tomorrow will not be the winner of today or yesterday.”
On AI Vestager said the major point of the plan is “to build trust” — by using a dual push to create what she called “an ecosystem of excellence” and another focused on trust.
The first piece includes a push by the Commission to stimulate funding, including in R&D and support for research such as by bolstering skills. “We need a lot of people to be able to work with AI,” she noted, saying it would be essential for small and medium sized businesses to be “invited in”.
On trust the plan aims to use risk to determine how much regulation is involved, with the most stringent rules being placed on what it dubs “high risk” AI systems. “That could be when AI tackles fundamental values, it could be life or death situation, any situation that could cause material or immaterial harm or expose us to discrimination,” said Vestager.
To scope this the Commission approach will focus on sectors where such risks might apply — such as energy and recruitment.
If an AI product or service is identified as posing a risk then the proposal is for an enforcement mechanism to test that the product is safe before it is put into use. These proposed “conformity assessments” for high risk AI systems include a number of obligations Vestager said are based on suggestions by the EU’s High Level Expert Group on AI — which put out a slate of AI policy recommendations last year.
The four requirements attached to this bit of the proposals are: 1) that AI systems should be trained using data that “respects European values and rules” and that a record of such data is kept; 2) that an AI system should provide “clear information to users about its purpose, its capabilities but also its limits” and that it be clear to users when they are interacting with an AI rather than a human; 3) AI systems must be “technically robust and accurate in order to be trustworthy”; and 4) they should always ensure “an appropriate level of human involvement and oversight”.
Obviously there are big questions about how such broad-brush requirements will be measured and stood up (as well as actively enforced) in practice.
If an AI product or service is not identified as high risk Vestager noted there would still be regulatory requirements in play — such as the need for developers to comply with existing EU data protection rules.
In her press statement, Commission president von der Leyen highlighted a number of examples of how AI might power a range of benefits for society — from “better and earlier” diagnosis of diseases like cancer to helping with her parallel push for the bloc to be carbon neutral by 2050, such as by enabling precision farming and smart heating — emphasizing that such applications rely on access to big data.
Artificial intelligence is about big data,” she said. “Data, data and again data. And we all know that the more data we have the smarter our algorithms. This is a very simple equation. Therefore it is so important to have access to data that are out there. This is why we want to give our businesses but also the researchers and the public services better access to data.”
“The majority of data we collect today are never ever used even once. And this is not at all sustainable,” she added. “In these data we collect that are out there lies an enormous amount of precious ideas, potential innovation, untapped potential we have to unleash — and therefore we follow the principal that in Europe we have to offer data spaces where you can not only store your data but also share with others. And therefore we want to create European data spaces where businesses, governments and researchers can not only store their data but also have access to other data they need for their innovation.”
She too impressed the need for AI regulation, including to guard against the risk of biased algorithms — saying “we want citizens to trust the new technology”. “We want the application of these new technologies to deserve the trust of our citizens. This is why we are promoting a responsible, human centric approach to artificial intelligence,” she added.
She said the planned restrictions on high risk AI would apply in fields such as healthcare, recruitment, transportation, policing and law enforcement — and potentially others.
“We will be particularly careful with sectors where essential human interests and rights are at stake,” she said. “Artificial intelligence must serve people. And therefore artificial intelligence must always comply with people’s rights. This is why a person must always be in control of critical decisions and so called ‘high risk AI’ — this is AI that potentially interferes with people’s rights — have to be tested and certified before they reach our single market.”
“Today’s message is that artificial intelligence is a huge opportunity in Europe, for Europe. We do have a lot but we have to unleash this potential that is out there. We want this innovation in Europe,” von der Leyen added. “We want to encourage our businesses, our researchers, the innovators, the entrepreneurs, to develop artificial intelligence and we want to encourage our citizens to feel confident to use it in Europe.”
The European Commission has been working on building what it dubs a “data economy” for several years at this point, plugging into its existing Digital Single Market strategy for boosting regional competitiveness.
Its aim is to remove barriers to the sharing of non-personal data within the single market. The Commission has previously worked on regulation to ban most data localization, as well as setting out measures to encourage the reuse of public sector data and open up access to scientific data.
Healthcare data sharing has also been in its sights, with policies to foster interoperability around electronic health records, and it’s been pushing for more private sector data sharing — both b2b and business-to-government.
“Every organisation should be able to store and process data anywhere in the European Union,” it wrote in 2018. It has also called the plan a “common European data space“. Aka “a seamless digital area with the scale that will enable the development of new products and services based on data”.
The focus on freeing up the flow of non-personal data is intended to complement the bloc’s long-standing rules on protecting personal data. The General Data Protection Regulation (GDPR), which came into force in 2018, has reinforced EU citizens’ rights around the processing of their personal information — updating and bolstering prior data protection rules.
The Commission views GDPR as a major success story by merit of how it’s exported conversations about EU digital standards to a global audience.
But it’s fair to say that back home enforcement of the GDPR remains a work in progress, some 21 months in — with many major cross-border complaints attached to how tech and adtech giants are processing people’s data still sitting on the desk of the Irish Data Protection Commission where multinationals tend to locate their EU HQ as a result of favorable corporate tax arrangements.
The Commission’s simultaneous push to encourage the development of AI arguably risks heaping further pressure on the GDPR — as both private and public sectors have been quick to see model-making value locked up in citizens’ data.
Already across Europe there are multiple examples of companies and/or state authorities working on building personal data-fuelled diagnostic AIs for healthcare; using machine learning for risk scoring of benefits claimants; and applying facial recognition as a security aid for law enforcement, to give three examples.
There has also been controversy fast following such developments. Including around issues such as proportionality and the question of consent to legally process people’s data — both under GDPR and in light of EU fundamental privacy rights as well as those set out in the European Convention of Human Rights.
Only this month a Dutch court ordered the state to cease use of a blackbox algorithm for assessing the fraud risk of benefits claimants on human rights grounds — objecting to a lack of transparency around how the system functions and therefore also “insufficient” controllability.
The von der Leyen Commission, which took up its five-year mandate in December, is alive to rights concerns about how AI is being applied, even as it has made it clear it intends to supercharge the bloc’s ability to leverage data and machine learning technologies — eyeing economic gains.
Commission president, Ursula von der Leyen, visiting the AI Intelligence Center in Brussels (via the EC’s EbS Live AudioVisual Service)
The Commission president committed to publishing proposals to regulate AI within the first 100 days — saying she wants a European framework to steer application to ensure powerful learning technologies are used ethically and for the public good.
But a leaked draft of the plan to regulate AI last month suggested it would step back from imposing even a temporary ban on the use of facial recognition technology — leaning instead towards tweaks to existing rules and sector/app specific risk-assessments and requirements.
It’s clear there are competing views at the top of the Commission on how much policy intervention is needed on the tech sector.
Breton has previously voiced opposition to regulating AI — telling the EU parliament just before he was confirmed in post that he “won’t be the voice of regulating AI“.
While Vestager has been steady in her public backing for a framework to govern how AI is applied, talking at her hearing before the EU parliament of the importance of people’s trust and Europe having its own flavor of AI that must “serve humans” and have “a purpose” .
“I don’t think that we can be world leaders without ethical guidelines,” she said then. “I think we will lose it if we just say no let’s do as they do in the rest of the world — let’s pool all the data from everyone, no matter where it comes from, and let’s just invest all our money.”
At the same time Vestager signalled a willingness to be pragmatic in the scope of the rules and how they would be devised — emphasizing the need for speed and agreeing the Commission would need to be “very careful not to over-regulate”, suggesting she’d accept a core minimum to get rules up and running.
Today’s proposal steers away from more stringent AI rules — such as a ban on facial recognition in public places. On biometric AI technologies Vestager described some existing uses as “harmless” during today’s press conference — such as unlocking a phone or for automatic border gates — whereas she stressed the difference in terms of rights risks related to the use of remote biometric identification tech such as facial recognition.
“With this white paper the Commission is launching a debate on the specific circumstance — if any — which might justify the use of such technologies in public space,” she said, putting some emphasis on the word ‘any’.
The Commission is encouraging EU citizens to put questions about the digital strategy for Vestager to answer tomorrow, in a live Q&A at 17.45 CET on Facebook, Twitter and LinkedIn — using the hashtag #DigitalEU
— European Commission (@EU_Commission) February 18, 2020
There is more to come from the Commission on the digital policy front — with a Digital Services Act in the works to update pan-EU liability rules around Internet platforms.
That proposal is slated to be presented later this year and both commissioners said today that details remain to be worked out. The possibility that the Commission will propose rules to more tightly regulate online content platforms already has content farming adtech giants like Facebook cranking up their spin cycles.
During today’s press conference Breton said he would always push for what he dubbed “shared governance” but he warned several times that if platforms don’t agree an acceptable way forward “we will have to regulate” — saying it’s not up for European society to adapt to the platforms but for them to adapt to the EU.
“We will do this within the next eight months. It’s for sure. And everybody knows the rules,” he said. “Of course we’re entering here into dialogues with these platforms and like with any dialogue we don’t know exactly yet what will be the outcome. We may find at the end of the day a good coherent joint strategy which will fulfil our requirements… regarding the responsibilities of the platform. And by the way this is why personally when I meet with them I will always prefer a shared governance. But we have been extremely clear if it doesn’t work then we will have to regulate.”
Internal market commissioner, Thierry Breton
Over the past four years, TechCrunch has brought together some of the biggest names in robotics — founders, CEOs, VCs and researchers — for TC Sessions: Robotics + AI. The show has provided a unique opportunity to explore the future and present of robotics, AI and the automation technologies that will define our professional and personal lives.
While the panels have been curated and hosted by our editorial staff, we’ve also long been interested in providing show-goers an opportunity to engage with guests. For this reason, we introduced the Q&A stage, where some of the biggest names can more directly engage with attendees.
This year, we’ve got top names from SoftBank, Samsung, Sony’s Innovation Fund, Qualcomm, Nvidia and more joining us on the stage to answer questions. Here’s the full agenda of this year’s Q&A stage:
11:30 – 12:00 Russell Book signing
1:15 – 2:00 Founders
Sebastien Boyer (FarmWise)
Noah Campbell-Ready (Built Robotics)
3:15 – 4:00 Building Robotics Platforms
Steven Macenski (Samsung)
Claire Delaunay (Nvidia)
$345 General admission tickets are still on sale — book yours here and join 1,000+ of today’s leading minds in the business for networking and discovery. The earlier you book the better, as prices go up at the door.
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A new startup called Arize AI is building what it calls a real-time analytics platform for “observability” in artificial intelligence and machine learning.
The company is led by CEO Jason Lopatecki, who has also served as chief strategy officer and chief innovation officer at TubeMogul, the video ad company acquired by Adobe. TubeMogul’s co-founder and former CEO Brett Wilson is an investor and board member.
And it has already made an acquisition: a Y Combinator -backed startup called Monitor ML. The entire Monitor ML team is joining Arize, and its CEO Aparna Dhinakaran (who previously built machine learning infrastructure at Uber) is becoming Arize’s co-founder and chief product officer.
Lopatecki and Dhinakaran said that even when they were leading two separate startups, they were trying to solve similar problems — problems that they both saw at big companies.
“Businesses are deploying these complex models that are hard to understand, they’re not easy to troubleshoot or debug,” Lopatecki said. So if an AI or ML model isn’t delivering the desired results, “The state of the art today is: You file a ticket, the data scientist comes back with a complicated answer, everyone’s scratching their head, everyone hopes the problem’s gone away. As you push more and more models into the organization, that’s just not good enough.”
Similarly Dhinakaran said that at Uber, she saw her team spend a lot of time “answering the question, ‘Hey, is the model performing well?’ And diving into that model performance was really a tough problem.”
To solve it, she said, “The first phase is: How can we make it easier to get these real-time analytics and insights about your model straight to the people who are monitoring it in production, the data scientist or the product manager or engineering team?”
Lopatecki added that Arize AI is providing more than just “a metric that says it’s good or bad,” but rather a wide range of information that can help teams see how a model is performing — and if there are issues, whether those issues are with the data or with the model itself.
Besides giving companies a better handle on how their AI and ML models are doing, Lopatecki said this will also allow customers to make better use of their data scientists: “[You don’t want] the smallest, most expensive team troubleshooting and trying to explain whether it was a correct prediction or not … You want insights surfaced up [to other teams], so your head researcher is doing research, not explaining that research to the rest of the team.”
He compared Arize AI’s tools to Google Analytics, but added, “I don’t want to say it’s an executive dashboard, that’s not the right positioning of the platform. It’s an engineering product, similar to Splunk — it’s really for engineers, not the execs.”
Lopatecki also acknowledged that it can be tough to make sense of the AI and ML landscape right now (“I’m technical, I did EECS at Berkeley, I understand ML extremely well, but even I can be confused by some of the companies in this space”). He argued that while most other companies are trying to tackle the entire AI pipeline, “We’re really focusing on production.”
Robotic process automation — the ability to automate certain repetitive software-based tasks to free up people to focus on work that computers cannot do — has become a major growth area in the world of IT. Today, a startup called Aisera that is coming out of stealth has taken this idea and supercharged it by using artificial intelligence to help not just workers with internal tasks, but in customer-facing environments, too.
Quietly operating under the radar since 2017, Aisera has picked up a significant list of customers, including Autodesk, Ciena, Unisys and McAfee — covering a range of use cases from “computer geeks with very complicated questions through to people who didn’t grow up in the computer generation,” says CEO Muddu Sudhakar, the serial entrepreneur (three previous startups, Kazeon, Cetas and Caspida, were respectively acquired by EMC, VMware and Splunk) who is Aisera’s co-founder.
With growth of 350% year-on-year, the company is also announcing today that it has raised $50 million to date, including most recently a $20 million Series B led by Norwest Venture Partners with Menlo Ventures, True Ventures, Khosla Ventures, First Round Capital, Ram Shriram and Maynard Webb Investments also participating.
(No valuation is being disclosed, said Sudhakar.)
The crux of the problem that Aisera has set out to solve is that, while RPA has identified that there is a degree of repetition in certain back-office tasks — which, if that work can be automated, can reduce operational costs and be more efficient for an organization — the same can be said for a wide array of IT processes that cover sales, HR, customer care and more.
There have been some efforts made to apply AI to solving different aspects of these particular use cases, but one of the issues has been that there are few solutions that sit above an organization’s software stack to work across everything that the organization uses, and does so in an “unsupervised” way — that is, uses AI to “learn” processes without having an army of engineers alongside the program training it.
Aisera aims to be that platform, integrating with the most popular software packages (for example in service desk apps, it integrates with Salesforce, ServiceNow, Atlassian and BMC), providing tools to automatically resolve queries and complete tasks. Aisera is looking to add more categories as it grows: Sudhakar mentioned legal, finance and facilities management as three other areas it’s planning to target.
Matt Howard, the partner at Norwest that led its investment in Aisera, said one of the other things that stands out for him about the company is that its tools work across multiple channels, including email, voice-based calls and messaging, and can operate at scale, something that can’t be said in actual fact for a lot of AI implementations.
“I think a lot of companies have overstated when they implement machine learning. A lot of times it’s actually big data and predictive analytics. We have mislabeled a lot of this,” he said in an interview. “AI as a rule is hard to maintain if it’s unsupervised. It can work every well in a narrow use case, but it becomes a management nightmare when handling the stress that comes with 15 million or 20 million queries.” Currently Aisera said that it handles about 10 million people on its platform. With this round, Howard and Jon Callaghan of True Ventures are both joining the board.
There is always a paradox of sorts in the world of AI, and in particular as it sits around and behind processes that have previously been done by humans. It is that AI-based assistants, as they get better, run the risk of ultimately making obsolete the workers they’re meant to help.
While that might be a long-term question that we will have to address as a society, for now, the reward/risk balance seems to tip more in the favour of reward for Aisera’s customers. “At Ciena, we want our employees to be productive,” said Craig Williams, CIO at Ciena, in a statement. “This means they shouldn’t be trying to figure out how a ticketing tool works, nor should they be waiting around for a tech to fix their issues. We believe that 75 percent of all incidents can be resolved through Aisera’s technology, and we believe we can apply Aisera across multiple platforms. Aisera doesn’t just make great AI technology, they understand our problems and partner with us closely to achieve our mission.”
And Sudhakar doesn’t feel that obsolescence is the end game, either.
“There are billions of people in call centres today,” he said in an interview. “If I can automate [repetitive] functions they can focus on higher-level work, and that’s what we wanted to do. Those trying to solve simple requests shouldn’t. It’s one example where AI can be put to good use. Help desk employees want to work and become programmers, they don’t want to do mundane tasks. They want to move up in their careers, and this can help give them the roadmap to do it.”
Tesla and SpaceX CEO Elon Musk is once again sounding a warning note regarding the development of artificial intelligence. The executive and founder tweeted on Monday evening that “all org[anizations] developing advance AI should be regulated, including Tesla.”
Musk was responding to a new MIT Technology Review profile of OpenAI, an organization founded in 2015 by Musk, along with Sam Altman, Ilya Sutskever, Greg Brockman, Wojciech Zaremba and John Schulman. At first, OpenAI was formed as a non-profit backed by $1 billion in funding from its pooled initial investors, with the aim of pursuing open research into advanced AI with a focus on ensuring it was pursued in the interest of benefiting society, rather than leaving its development in the hands of a small and narrowly-interested few (i.e., for-profit technology companies).
All orgs developing advanced AI should be regulated, including Tesla
— Elon Musk (@elonmusk) February 17, 2020
At the time of its founding in 2015, Musk posited that the group essentially arrived at the idea for OpenAI as an alternative to “sit[ting] on the sidelines” or “encourag[ing] regulatory oversight.” Musk also said in 2017 that he believed that regulation should be put in place to govern the development of AI, preceded first by the formation of some kind of oversight agency that would study and gain insight into the industry before proposing any rules.
In the intervening years, much has changed – including OpenAI. The organization officially formed a for-profit arm owned by a non-profit parent corporation in 2019, and it accepted $1 billion in investment from Microsoft along with the formation a wide-ranging partnership, seemingly in contravention of its founding principles.
Musk’s comments this week in response to the MIT profile indicate that he’s quite distant from the organization he helped co-found both ideologically and in a more practical, functional sense. The SpaceX founder also noted that he “must agree” that concerns about OpenAI’s mission expressed last year at the time of its Microsoft announcement “are reasonable,” and he said that “OpenAI should be more open.” Musk also noted that he has “no control & only very limited insight into OpenAI” and that his “confidence” in Dario Amodei, OpenAI’s research director, “is not high” when it comes to ensuring safe development of AI.
While it might indeed be surprising to see Musk include Tesla in a general call for regulation of the development of advanced AI, it is in keeping with his general stance on the development of artificial intelligence. Musk has repeatedly warned of the risks associated with creating AI that is more independent and advanced, even going so far as to call it a “fundamental risk to the existence of human civilization.”
He also clarified on Monday that he believes advanced AI development should be regulated both by individual national governments as well as by international governing bodies, like the U.N., in response to a clarifying question from a follower. Time is clearly not doing anything to blunt Musk’s beliefs around the potential threat of AI: Perhaps this will encourage him to ramp up his efforts with Neuralink to give humans a way to even the playing field.