A few days ago, I was invited to speak at a Yale Entrepreneurship Breakfast about about one of my favorite areas of interest, Artificial Intelligence. Here are the slides from the talk — a primer on how AI rose from of the ashes to become a fascinating category for startup founders and venture capitalists. Very much a companion to my earliest post about our investment in x.ai. Many thanks to my colleague Jim Hao, who worked with me on this presentation.
The superb Lending Club success story is what the startup world is all about: a software-based reinvention of massive and inefficient industry; a product that puts consumers first and delivers undeniable benefits ; and an entrepreneurial mega-hit that brings incredible riches and returns to its founder and investors.
In some ways, Lending Club is a classic Silicon Valley story; in some other ways, it is pretty atypical. As a friend of Renaud Laplanche’s for over 20 years, I have had a chance to witness from up close some parts of his journey with Lending Club. It is full of interesting lessons for entrepreneurs and the tech industry in general:
It’s been about 18 months since my original attempt at charting the Internet of Things (IoT) space. To say the least, it’s been a period of extraordinary activity in the ecosystem.
While the Internet of Things will inevitably ride the ups and downs of inflated hype and unmet expectations, at this stage there’s no putting the genie back in the bottle. The Internet of Things is propelled by an exceptional convergence of trends (mobile phone ubiquity, open hardware, Big Data, the resurrection of AI, cloud computing, 3D printing, crowdfunding). In addition, there’s an element of self-fulfilling prophecy at play with enterprises, consumers, retailers and the press all equally excited about the possibilities. As a result, the IoT space is now reaching escape velocity. Whether we’re ready for it or not, we’re rapidly evolving towards a world where just about everything will be connected. This has profound implications for society and how we collectively interact with the world around us. Key concerns around privacy and security will need to be addressed.
For entrepreneurs, the opportunity is massive. Where Web 1.0 connected computers to the Internet and Web 2.0 connected people, Web 3.0 is shaping up to be connecting just about everything else – things, plants, livestock, babies… Each new wave has spun out giant companies (Google and Amazon for Web 1.0, Facebook and Twitter for Web 2.0). Will Web 3.0 create a comparable group of behemoths?
I joined FirstMark as a partner a little over 18 months ago now, and it’s been a thrilling ride. It’s also felt like a steep learning curve: lots of nuances, and lots of institutional memory to absorb. Below is a glimpse into what I’ve seen happening “behind the scenes” on the VC’s side to the table – stuff that was not obvious to me in my former roles as entrepreneur, angel investor or corporate incubator/strategic.
Last night I was invited to speak at the inaugural NYC European Tech Meetup. There are tons of obvious reasons why the NYC and European tech ecosystems should work closely with one another, so a meetup on the topic was long overdue. Congrats to Alban Denoyel and Anthony Marnell for starting it, and thanks for inviting me to speak, was a lot of fun. Below are the slides I used – the presentation was meant to be a “State of the Union” of European tech in NYC, a high level overview fit for an inaugural meetup and get the conversation started.
Many thanks to David Rogg, our newest associate at FirstMark, for helping me with this. I’m sure we missed some companies and people – if so, let us know in the comments, and we’ll update the presentation.
I know, when thinking about hotbeds of startup innovation, France doesn’t exactly jump to mind. Sure, there are interesting things happening in European tech – in London, or Berlin (which I covered here). Or Finland. But France? Ask U.S investors and entrepreneurs, and you’ll hear more or less the same thing: high taxes. Impossible to fire people. Government intervention. Language barrier. Fear of failure. Strikes. The country of the the 35 hour law, where people are prohibited by law to answer email past 6pm.
Yet things have started to accelerate meaningfully in French early stage tech, particularly in the last two or three years. I was fortunate to be recently invited as part of a delegation of US VCs and media guests to spend a few days in Paris to meet with local entrepreneurs and VCs, as well as President Hollande and other senior members of the French government. As a Frenchman who has spent his entire professional career in the US, I’m perhaps more cynical than most about those matters, but I came back from my trip genuinely intrigued by the potential of the French tech scene.
For anyone who cares to look, the fairly obvious conclusion is that there’s a huge gap between perception and reality, when it comes to the French startup ecosystem. Very significant progress has been made on all fronts – more interesting startups, more funding, lots more talent rushing into the sector, improved legistation, etc. – yet the word has not caught on.
Note: This post appeared on VentureBeat, here.
It’s been almost two years since I took a first stab at charting the booming Big Data ecosystem, and it’s been a period of incredible activity in the space. An updated chart was long overdue, and here it is:
(click on the arrows at the bottom right of the screen to expand)
A few thoughts on this revised chart, and the Big Data market in general, largely from a VC perspective:
Getting crowded: Entrepreneurs have flocked to the space, VCs have poured money into promising startups, and as a result, the market is starting to get crowded. Certain categories like databases (whether NoSQL or NewSQL) or social media analytics feel ripe for consolidation or some sort of shakeout (which may have already started in social analytics with Twitter’s acquisitions of BlueFin and GNIP). While there will be always room for great new startups, it seems that a lot of the early bets in the broader infrastructure and analytics segments have been made at this stage, and the bar for success is getting higher – which doesn’t mean that VC money will stop pouring in. In terms of this specific industry chart, we’ve clearly reached the limit of how many companies we can fit one page. I’m sure there are a number of great companies we either missed or didn’t have enough space to include – apologies in advance to those, and I’d love to hear people’s thoughts and suggestions in the comments section about who else should be included.
Still early: Overall, we’re still in the early innings of this market. Over the last couple of years, some promising companies failed (for example: Drawn to Scale), a number saw early exits (for example: Precog, Prior Knowledge, Lucky Sort, Rapleaf, Nodeable, Karmasphere, etc.), and a handful saw more meaningful outcomes (for example: Infochimps, Causata, Streambase, ParAccel, Aspera, GNIP, BlueFin labs, BlueKai). Meanwhile, some companies seem to be reaching significant scale, and have raised spectacular amounts of money (for example, MongoDB has now raised over $230M, Palantir almost $900M and Cloudera $1B). But overall, we’re still early in the curve in terms of successful IPOs (Splunk or Tableau notwithstanding) and large exits, although the big companies are getting more acquisitive in the space (Oracle with BlueKai, IBM with Cloudant). In many segments, startups and large companies are jockeying for position and no obvious leader has emerged.
Hype, meet reality: A few years into a period of incredible hype, is Big Data still a thing? While less press worthy, the next couple of years are going to be hugely important for this market, as corporations start moving Big Data projects from experimentation to full production. While they will lead to rapidly increasing revenues for some Big Data vendors, those deployments will also test whether Big Data can truly deliver on its promise. Meanwhile, the fundamental need for Big Data technology keeps increasing, as the deluge of data keeps accelerating, powered in part by the rapidly emerging Internet of Things industry.
Infrastructure: Hadoop seems to have solidified its position as the cornerstone of the entire ecosystem, but there are still a number of competing distributions – this will probably need to evolve. Spark, another open source framework that builds on top of the Hadoop Distributed File System, is getting a lot of buzz right now because it promises to fill in the places where Hadoop has been weak, namely interactive speeds and good programming interfaces (and early signs seem to point to fulfilling that promise). Some themes (for example, in memory or real time) continue to be top of mind; others are appearing (for example, there’s a whole new generation of data transformation/munging/wrangling tools, including Trifacta, Paxata and DataTamer). Another key discussion is whether enterprise data will truly move to the cloud (public or private), and if so, how quickly. Many will argue that Fortune 500 companies will keep their data (and the software to process it) on premise for years to come; a generation of Hadoop-in-the-cloud startups (Qubole, Mortar, etc.) will argue that all data is moving to the cloud long term.
Analytics: This has been a particularly active segment of the Big Data ecosystem in terms of startup and VC activity. From spreadsheet type interfaces to timeline animations and 3D visualizations, startups offer all sorts of different analytical tools and interfaces, and the reality is that different customers will have different type of preferences, so there’s probably room for a number of vendors. Go to market strategies differ as well – some startups focus on selling tools to data scientists, a group that is still small but growing in numbers and budget. Others adopt the opposite approach and sell automated solutions targeting business users, bypassing data scientists altogether.
Applications: As predicted, the action has been slowly but surely moving to the application layer of Big Data. The chart highlights a number of exciting startups that are fundamentally powered by Big Data tools and techniques (certainly not an exhaustive list). Some offer horizontal applications – for example, Big Data powered marketing, CRM tools or fraud detection solutions. Others use Big Data in vertical specific applications. Finance and ad tech were always early leaders in adopting Big Data, years before it was even called Big Data. Gradually, the use of Big Data is spreading to more industries, such as healthcare and biotech (particularly in genomics) or education. This is only the beginning.
Many thanks for my FirstMark colleague Sutian Dong for doing a lot of the heavy lifting on this chart. My former colleague Shivon Zilis of Bloomberg Beta contributed immensely to prior versions of this chart.
3. Crowdsourced data. From Estimize (which crowdsources analyst estimates) to Premise (which crowdsources macroeconomic data through an army of people around the world equipped with mobile phones), a whole new way of capturing financial data has emerged. Quandl, a financial data search engine, has aggregated over 8 million financial and economic datasets through both web crawling and crowdsourced, community contributions. Once such a data platform has been built, could third party developers add analytic and visualization tools on top, essentially resulting in a crowdsourced “terminal” of sorts that would be reliable enough, at least for non mission critical, non real time use cases?
The field of bioinformatics is having its “big bang” moment. Of course, bioinformatics is not a new discipline and it has seen various waves of innovations since the 1970s and 1980s, with its fair share of both exciting moments and disappointments (particularly in terms of linking DNA analysis to clinical outcomes). But there is something special happening to the industry right now, accelerated by several factors:
• The cost of full genome sequencing has been dropping precipitously, in fact a lot faster than Moore’s law would have suggested. Illumina just released brand new machines that make the $1,000 full genome sequencing a realistic possibility. As a result, an extraordinary amount of data is going to become available at reasonable cost (5.5TB or 6.3 Billion bases… per patient).
• Big Data technology has had its own, separate evolution, and there is now an arsenal of tools to process and analyze massive amounts of data, at a comparatively cheap cost.
• Wet lab work has become a more standardized and increasingly automated process, considerably reducing the “friction” involved in collecting and processing physical samples. The cost of setting up biology labs, while still high, is starting to decrease, and molecular techniques are no longer the limiting step in genomic analysis.
As a result of the above, biology is rapidly evolving from being predominantly driven by traditional life sciences research to being largely driven by software and Big Data. This evolution considerably reduces the capital required to build a successful venture in the space. It also opens up the field to a new generation of startups run by inter-disciplinarian teams that have at least as much of a software and data science background as a biology background. A whole new world of bio-hackers is also emerging, from synthetic biology to personalized medicine, the possibilities are immense and the impact on our lives potentially unparalleled. It is entirely possible that the next generation of great entrepreneurs will be building “biology 2.0” companies, rather than mobile apps.
This opportunity has not been lost on entrepreneurs and the last 3 years or so have seen a rapid acceleration of startup creation, in a wide range of area from diagnostics (Counsyl) to cloud platforms (DNANexus) to lab automation (Benchling, Transcriptic). Interestingly but not surprisingly considering the above, most of those startups are funded by technology, rather than life sciences, venture capital firms.
Today I’m excited to announce that FirstMark is partnering with Recombine, a New York based startup that very much operates at this intersection between software, Big Data and biology, as its lead Series A investor. Recombine’s CEO, Alex Bisignano, symbolizes this new generation of entrepreneurs who have deep knowledge in multiple technical fields. He has built around him a great, multi-disciplinarian team, and benefits from the deep industry knowledge and expertise of co-founder Dr. Santiago Munne, the owner of Reprogenetics and pioneer in pre-implantation genetic diagnosis.
Recombine’s core focus is the field of fertility and reproductive genetics, and it has had a spectacular early start with CarrierMap, its first product, generating a profitable multi-million dollar business with a comparatively small seed investment. The CarrierMap test is the most comprehensive, cost-effective, carrier screen on the market, and has already helped thousands of couples to identify and mitigate the risk of passing on serious illnesses to their children. CarrierMap is sold exclusively through doctors and clinics, it is not a Direct to Consumer product (and therefore falls in a different category than 23andMe).
Beyond this initial focus, Recombine has ambitious plans to fully leverage Big Data technology to help decode the myriad aspects of our genome that are still not well understood. They have already obtained Institutional Review Board (IRB) approval for their first large-scale study, and the company is currently assembling a crack team of data scientists in New York City. If you have deep expertise in data science field, this is an opportunity to help bring about a revolution in personalized medicine. Come join us!
Here’s the video from SIIA’s “IIS: Breakthrough” conference that corresponds to the slides in the previous post. Not necessarily the crispest delivery on this one, but here you go.
I’m doing a talk on the Internet of Things tomorrow at the SIIA’s “IIS: Breakthrough” conference tomorrow, and here are the slides I’ll use. It’s meant to be a high level introduction to the topic, for a broad audience of “information industry” professionals. Also used an earlier version of those slides at the WIN Global Innovator last week, which was fun. Feedback welcome.
Mother (click to view in 3D)
Withings Aura (click to view in 3D)
As the fundamentally important debate over women in technology and entrepreneurship rages on (most recently sparked by what Paul Graham said, or perhaps didn’t say), I’ve been intrigued by the comparatively higher proportion of women who seem to be starting companies in one of my areas of predilection: hardware (broadly defined: open hardware, Internet of Things, wearable computing, 3D printing, etc.).
I don’t have much data here, other than my anecdotal personal experience, both as a VC and as the organizer of Hardwired NYC. But, without having to rack my brain for more than a minute or two, a bunch of names of great female founders and/or CEOs in the general hardware space comes up, including, in no particular order:
- Limor Fried, founder, Adafruit
- Ayah Bdeir, founder and CEO, littlebits (who spoke at Hardwired NYC last November)
- Amanda Peyton, co-founder and CEO, Grand St (see her talk at Hardwired NYC here)
- Jenny Lawton, President, Makerbot (see her talk at Hardwired NYC here)
- Kegan Schowenburg, co-founder and CEO, Sols (speaking at Hardwired NYC next week)
- Helen Zelman, co-founder, Lemnos Labs
- Cheryl Kellond, co-founder and CEO, Bia
- Monisha Perkash, co-founder and CEO, Lumo BodyTech
- Daniela Perdomo, co-founder and CEO, GoTenna
- Mary Huang, co-founder, Continuum Fashion
- Meredith Perry, founder and CEO, uBeam
- Julia Hu, founder and CEO, Lark
- Debra Sterling, founder and CEO, GoldieBlox
And there are many more (both in the U.S and globally), which is exciting.
The question, of course, is why hardware would be an area of particular focus for female entrepreneurs. As a category, hardware is broad, lends itself to all sorts of products, and as a result feels pretty gender-neutral.
Could it be that there are more female role models in hardware, since it is often said that role models are particularly important to female entrepreneurs ? It doesn’t appear that way. Sure, women have run some of the biggest hardware companies in the world (Carly Fiorina and Meg Whitman at HP; Ursual Burns at Xerox) but it’s unclear how much of an inspiration they would be to early stage tech entrepreneurs, and more importantly, a number of software or internet companies have been run by women as well. Perhaps more relevant are female entrepreneurs like Limor Fried, who under her “Lady Ada” moniker has become the closest equivalent to a celebrity in the hardware alpha geek world (and beyond, through her appearance on the cover of Wired in 2011).
What’s interesting is that hardware lends itself particularly well to new entrants – there’s been a big gap in innovation in hardware in the last 10 or 15 years (with some notable exceptions like Apple), and as a result there’s a “missing generation”, and plenty of opportunities for new entrepreneurs to become leaders in what, in some ways, feels like a brand new field.
Curious if anyone can think of an explanation?
Regardless, and to the extent this is indeed a trend, it is particularly exciting and promising, and we should collectively think about how to accelerate it and extend it to other areas of tech entrepreneurship.
Got some great feedback on Twitter, and while my initial goal was not to be comprehensive here, thought it could actually be helpful to start a running list of female hardware founders – perhaps it can become a good resource. Here are the people that were recommended to me, who else should I add? (please add in comments)
|First Name||Last Name||Company||Location|
|Jeri||Ellsworth||Technical Illusions||Bellevue, WA|
|Anastasia||Leng||Hatch||New York, NY|
|Christina||Mercando||Ringly||New York, NY|
|Ezster||Ozsvald||Notch||New York, NY|
|Gauri||Nanda||Toymail||New York, NY|
|Lisa||Fetterman||Nomiku||San Francisco, CA|
|Laura||Berman||Melon||Santa Monica, CA|
|Amanda||Williams||Fabule Fabrications||Montreal, Canada|
|Alexandra||Deschamps-Sonsino||Good Night Lamp||London, UK|
|Becky||Pilditch||Bare Conductive||London, UK|
|Jane||ni Dhulchaoinfi||Sugru||London, UK|
|Ana||Burica||Teddy The Guardian||Zagreb, Croatia|
I recently got a chance to participate in a panel focused on opportunities in hyperlocal at the 2013 StreetFight Summit, along with Ben Siscovick. Since they recorded it, here it is, along with a couple of pics.