We are on the brink of a major disruption, which we think might be bigger than the industrial revolution. At BootstrapLabs we are focusing heavily on a major shift that is impacting almost every sector: Artificial Intelligence – AI.
AI has reached an inflection point, where it can now be applied to quickly drive efficient returns, and in our book, is ripe for building startups that will disrupt major markets and their incumbents.
Let’s go back: The Industrial Revolution & Apple
During the Industrial Revolution, the steam engine enabled a major technological shift as a large amount of manual labor was now able to be automated. Yet, few know that the first version of the steam engine was actually built the 1st century CE and was called Aeolipile. It was not until much later, in 1712, when Thomas Newcomen developed a commercially viable version of the steam engine that applied to “mechanical work” that serious increases in productivity started to take place. But, this major shift did not reach its full disruptive potential until 1781 when James Watt designed a model that provided a stronger and continuous rotary motion, resulting in an order of magnitude better output/cost ratio and allowed the technology to spread across applications and sectors, spurring the Industrial Revolution.
As always with technology and its applications, it is a combination of factors that create an inflection point.
The Garages of Silicon Valley: A similar pattern and iterative process emerged in the garages of Silicon Valley, and eventually spawned the likes of Apple, Hewlett Packard, etc. This is a recurring pattern of how innovation emerges. The inflection point is always triggered by a number of factors, not just the main innovation of the steam engine or the silicon-based CPU chips (or COTS components to build a computers for that matter).
The Rear-Mirror Effect: These inflection points are often hard to spot. First there is disbelief, then some excitement. Then the general public tends to be disappointed by the slow(er) pace of adoption vs. their expectations, yet slowly but surely, additional improvements and iterations of the original breakthrough take place, quietly, unnoticed. Even additional breakthroughs building on the prior ones create an unstoppable wave of change that often catches people by surprise and most realize that the inflection point really happened a few year ago, when looking in the rear-mirror (and they are too late to the game).
The rise of Applied Artificial Intelligence (Applied AI)
Today we have reached a similar inflection point with Applied AI and we believe it will have a significant disruption potential on many established industries, and our society at large. Today smart software can process massive amounts of data to derive knowledge and conclusions that humans simply cannot.
AI methods and algorithms are not new, they have been around for quite some time, but there are a number of factors that are creating an inflection point for AI to be applied in a much wider sense, across applications and industry verticals that were not feasible before. Additionally, more recent approaches and methodologies like deep learning have yielded an order of magnitude better results than prior approaches.
Ability to compute, store and transfer data
- We are buying twice the amount of CPU processing for each $1 every 18 months.
- We are buying twice the amount of storage for each $1 every 12 months.
- We are buying twice the amount of communications bandwidth for each $1 every 9 months.
More data recorded in last 18 months than the entire history of mankind
The vast majority of all information ever created by mankind was created, transferred, and stored in the past 18 months alone. There is a massive amount of data (and knowledge/information to be extracted from it), and it is growing exponentially.
Also multi-dimensional correlations add a massive opportunity. Take for example fitness trackers, such as JawBone and FitBit, that are tracking activities like movement and sleep. In just a few years they harvested more research data and conclusions (using machine learning) of how physical exercise and sleep are tied together than any research facility ever had in history (and at a fraction of the cost).
Oh – and they also track where (geographic position) exercise is happening, which adds another dimension to this information.
In another example, one of our portfolio founders is exploring how to connect your emotional state of being with what you read in your social communications channels, event calendar, etc., and have the machine learn and guide you on ways to improve your mental well being.
Cost to build keeps going down
The cost to build startups keeps going down, which is true for building AI at scale too, through hosted infrastructure, cost of hardware and open source software (backed by Google, Facebook, Yahoo!, OpenAI, etc.) AI is being applied right now in garages around the world where startups are being built. The hardware needed today is so commoditized that it is all more or less a software play (which increases the pace of innovation and efficiencies).
This all means that innovation by applying Artificial Intelligence is exploding and happening everywhere, not just in the large R&D labs and research facilities anymore.
It holds the keys to our future
All this data, that can now be stored and computed cost efficiently using smart software (AI), holds answers to everything from optimizing your retirement savings, global economic flux, health, education, and answers of how to mitigate climate change today and tomorrow.
The most exciting things are yet to come, but let me give you a few examples of what is already happening:
- AngelList uses massive amounts of data and interaction patterns with machine learning to improve matching and interaction in their global network of Angel investors.
- 23andMe uses machine learning and big data to find, in 20 minutes of compute time, the answers that took the CDC up to 7 years and a $100M study to accomplish.
- George Hotz, the San Francisco “hacker” known for being the first to unlock the iPhone, has built a self-driving car in a month, using mostly off the shelf components, and using deep learning methodologies, resulting in potential self-installation kits costing less than $1,000 a pop.
- JawBone has conducted the biggest sleep study in history (no company or research organization has had access to that much sleep data before).
As with building any startup today, the hardest thing is Scalable Product Market Fit, which is also why it is so hard for incumbents to tackle the innovation that comes out of startups (Innovators Dilemma).
The large and well funded R&D organizations are still good at cracking hard innovation with long time frames, often called “Moon Shots”, but much less so for finding new Scalable Product Market Fit. This is where startup innovation shines, and when the off the shelf components can be assembled quickly, innovation flourishes.
There is an unbundling of the big corporations, and we think that the key disruption driver for the winners is going to be their ability to apply Artificial Intelligence, and build better, more efficient products that scale.
So what are we doing about it at BootstrapLabs?
We are, of course, focusing our entire Venture Building platform toward the discovery of the best Applied AI innovation globally, and empowering the founders behind them to build globally disruptive companies from Silicon Valley.
We are vetting over a thousand startups per a year from Silicon Valley, Europe, and Asia, and are seeing some very exciting innovators (which you will read more about soon!) who are applying AI such as machine learning, image recognition, and deep learning.
Our upcoming seed fund will invest in Applied AI software startups with a focus on FinTech, IoT, and Future of Work verticals (with the ability to expand into areas like logistic, education, commerce, eHealth, etc.)
We are also bringing together the global AI community of hackers and builders at hackers.ai and hosting the biggest Applied AI focused conference in Silicon Valley on May 25th.
He wheeled 175 huge books with over 260 thousand pages, each filled with A, G, T and Cs, containing the entire DNA of Craig Venter.
Predicting (and preventing) health issues. He turned the page and read a sequence of 8 letters that represent Craig Venter’s eye color – blue.
And then he turned to another page, where if just two letters were in the wrong order, it would mean he has cystic fibrosis.
Predicting physical attributes from DNA
Using machine learning, he is now able to predict things like height, eye color, skin color, and even facial structure based on a person’s genome. Pretty amazing.
The application areas for this are massive, with the right prediction models (and later simulation models) we are going to be able to be able to not only predict but prevent many major health issues.
When we founded BootstrapLabs eight years ago, we set out to create a company that would empower some of the world’s best technology entrepreneurs to build disruptive companies from Silicon Valley.
In our quest to build an efficient and scalable process to empower entrepreneurs, we transformed BootstrapLabs into a world class Venture Builder platform and brought together 3 critical elements for the success of any entrepreneurial endeavor:
- Human Capital: Beyond access to our Core team, Global Venture Partners, and Experts in Residence, we have created BootstrapWorks, a proprietary platform that allows founders to find, vet, and compensate top advisors and experts in Silicon Valley and beyond, while removing the friction of contracts, vetting, etc.
- Venture Capital: Because entrepreneurs need fuel to accelerate the growth of their ventures, we invest in our portfolio companies from our investment funds at the Seed and early Series A round stages. We have also built a great network of top-tier Silicon Valley co-investors and follow-on investors for our companies.
- Global Community: Over the years, we have nurtured and grown a large and international community of like-minded entrepreneurs, investors, and executives that further reinforce our platform and deal flow.
BootstrapLabs recognizes that talented entrepreneurs have many choices when it comes to accessing capital, but money is only the tip of the iceberg. Experienced founders know that the human capital part of the equation is often the difference between breakout success and failure. For this reason, we strive to provide founders with a bespoke combination of capital, skills, experience, and network, a place were the world’s best founders WANT to come build and iterate their startups to scalable product market fit and success.
If this sounds exciting, get in touch, and come make a dent in the Universe with us.
The First Person to Hack the iPhone Built a Self-Driving Car. In His Garage. Using Artificial Intelligence software and consumer-grade cameras – that have become good enough to allow a clever tinkerer to create a low-cost self-driving system for just about any car.
That tinkerer and hacker is George Hotz.
The technology he is building represents an end run on much more expensive systems being designed by Google, Uber, the major automakers, and, if persistent rumors and numerous news reports are true, Apple.
One of the most important things when building a startup is the sequence of how you execute. It is even more important than “doing the right things”.
You need to be laser focused and meticulous on the execution at hand, while driving towards your big vision of your company, and evaluating the plan regularly.
By NOT planning every detail of what needs to happens in the next 12 months, you are increasing your attention span on what is needed right now, while making sure you make the best decisions with as much data as you can at any given point in time.
When you are planning in detail what to do in 6 to 12 months, you are making decisions with a large number of assumptions and little data.
I am saying this so often to our portfolio company founders and the team at BootstrapLabs that it is starting to sound like a mantra:
Have faith in your assumptions, but trust your data.
And sorry – you are not getting away from planning, which is just as important to create a shared vision and understanding of the road ahead within the team. The assumptions are not less important. You just need to understand that they are just assumptions, and when and how they turn into data.
It is actually quite simple. When you launch a new startup, you are always underskilled and underfunded as you start to build, and you need to create a model of how you execute effectively where you are (shameless plug: we are trying to fix that with BootstrapWorks, still stealth – but sign-up for the waitlist!), while keeping your big vision in mind, and constantly reevaluating and changing the focus to adapt to the current situation.
For example: You know you are addressing a large market, and your product and DevOps really need to scale. You know that if you hit Milestone C you are going to have a million users of your product. You are now at Milestone A, and the reality is that unless you focus 100% on nailing the core Product Market Fit with your early customers to get to Milestone B, you will neither know what is needed from the platform to scale to a million users, or raise the funding to do so.
Ben Horowitz talk about wartime and peacetime CEOs in his book, “The Hard Thing About Hard Things”. Using those terms, when you start a new company you need to be in the wartime CEO mode, otherwise you will not survive long enough to fight your first real battle.
All of this applies before finding an initial Product Market Fit and before raising A/B rounds to scale. At that point the same mechanics apply, but both at a larger scale and longer timeframe. And you need to plan for resources much further ahead. But that goes back to the core message of this blog post. You always need to execute and optimize for where you are at any given point in time.
Techblogs tend to paint a glamorous picture of how easy it is to raise a billion dollars in funding and build a startup. Reality is very different – it is hard work, a long journey and compared to a job, you are never really off the job.
As a startup founder for 20+ years and counting, 10 years as an angel investor, and lately a Venture Capital investor through BootstrapLabs, I have seen a number of interesting patterns in startup founder’s/CEO’s behavior.
One thing I think a fair bit about is the ‘obsessive’ behavior of successful founders that I advised and invested in for the past 10 years (and I see this trait in myself as well…).
Startup CEOs are working super hard, and not always at the office. They always seem to be preoccupied, which drives spouses and family members crazy sometimes.
It’s not that they are literally working 90+ hours a week in an office, doing work tasks such as coding, recruiting, selling, etc. Once they start to grow their team and begin getting traction, to be successful they need to shift into how to really drive the business. And they always need to be thinking about the next big thing, and how to get the company to the next level or stage of growth.
The reason for this is that startups are not really executing a business model, they are in search of a hyper scalable business model. And that search continues until they get escape velocity, die, or divest for other reasons.
So on the journey of a startup CEO you don’t have a quiet moment in your head most days, you are constantly thinking about your ‘baby’, and trying to figure out how to solve problems 24/7 around the clock 365 days a week (or sorry, I mean per year).
As I tell many founders that pitch us at BootstrapLabs, you need to surround yourself early on with a team that shares this ‘obsessive’ behavior to drive your startup forward. And your most important job is to find those people and make them excited about the being part of the journey.
So even when having dinner with friends, or taking care of the kids, or in the morning shower, the founder/CEO is thinking that to hit that $5 million annual run rate to raise the “A” round, you need to ramp up hiring of the sales force and marketing teams. And you need somebody that has experience in X and skills in Y. Or that a particular piece of the product is inhibiting the growth, or is not good enough to drive Product Market Fit, etc.
When launching a new startup: You usually start in a search & discovery mode – that seems to be all over the place for many of the people around you. But once you start to get data points and validation of what you do, you need to quickly shift into a very different approach that is laser focused. At the same time you need to stop every 2 weeks or so and question just about everything and make sure that your assumptions are still valid.
From early assumptions to Laser Focus: Once you have found what to zoom in on, your most scarce resource is actually neither money or time, but personal attention span – which is why most startup CEO’s go into a reductionist mode to create a clear focus on the most important things that need to happen to bring the company to the next level. If you focus on the right things at the wrong time, your company dies.
This is why there are a few key things you need to learn early on as a founder/CEO of a startup:
- You need to recruit co-founders and team members that give you leverage (execute things independently better than you) – this will increase your attention to other things you do better.
- Early on and for the core team, you need to find people that share your obsession & passion.
- You need deep domain skills for the core things you are trying to do within the team, for everything else you need great advisors that can give you sharp insights a few times a month.
Because of the shift from discovery to reductionist mode, the early team is extra hard to build, as very few people are capable of shifting successfully between these two operating modes. In part, this is why it is so hard to find co-founders, since this prerequisite skill is so scarce.
After you have found a focus it becomes a tad easier, but you still need to build a core team with an almost obsessive drive to take things to the next level, and then work really really hard to become a Unicorn.
“No sleep for the wicked”
Anybody building a startup or marketing or selling something should listen to this piece when Steve Jobs talks about marketing.
The piece about focus is kind of important too, well worth 16 minutes of your time!
2015 has been a banner year for BootstrapLabs. During the past 12 months, we led our first Series A round in an exciting FinTech company, all our portfolio companies raised follow-on funding at higher valuation and we continued to expand our Expert in Residence team to support our portfolio companies.
We believe that technology is a driving force for positive change in the global economy, in society in general, and our daily lives in particular. We continue to be impressed by the talent and passion our founders demonstrate every day and look forward to continuing investing in disruptive technology companies that can transform the way we live, the way we work, and the way we connect with the world around us.
Many believe private companies are overvalued, while others think the next tech bubble is coming. At the same time we see that seed stage investments, where BootstrapLabs focuses, are more vibrant and exciting than ever (e.g., a $25K seed stage investment in Uber would be worth ~ $125M at the $40B valuation mark; even if you assume that Uber is worth $1B, it would still be an investment worth ~ $3M, or 125x the invested amount).
BootstrapLabs is “deep in the stack” alongside its founders day after day, driving the venture market momentum forward. Our global innovation discovery network, combined with our Silicon Valley investment and execution model, provides us with a unique vantage point on what is happening in every corner of the world. Here is what we are observing:
The HOT tech industry is attracting new, mostly late stage, institutional investors that need to invest tens of millions per deal to move the needle.
In 2015, over 566 deals were financed by investment banks, mutual funds, hedge funds, asset managers, and others, while 78% of the deals over $1 Billion have been lead (read priced) by non-VC investors.
Late stage deals are becoming more competitive and less price sensitive due to a combination of i) pent-up demand driven by lower public market returns and the relative rarity of such high growth private technology companies and ii) more financial engineering and deal structuring that aims at lowering the risk for investors, independent of valuation paid (e.g. preferences, ratchets, dividends, etc.) Arguably, these higher valuations are behaving more like “out-of-the-money strike prices” of call options rather than rational valuations driven by operational and technological performance. The chart below outline the dramatic increase in valuation in the later stage as well as the larger amount of money invested by these non-VC investors.
There are also NEW sources of capital targeting the Tech Industry via Equity Crowdfunding and platforms that are driving retail investors into the venture market.
As these platform emerge and private companies can do “public offering of private equity”, secondary market for private equity trading/exchange will gain momentum and importance. One big signal of such trend was the recent acquisition of SecondMarket, the leader in the space by Nasdaq.
Why are non-VCs investing in the tech space?
Startups are staying private longer prior to IPOs today, which means that private investors are making the most of the value from their investment during the pre-IPO period. Traditional public investors, like hedge funds and mutual funds, are starting to realize that in order to capture more value they have to move earlier in the game and start investing in pre-IPO rounds (Private IPOs). See this prior post from Ben Levy, Co-Founder of BootstrapLabs on How to Milk a Unicorn…
Also, traditional VCs have realized that they have to invest earlier in the cycle in order to maximize their investments and not become irrelevant themselves in a world that is changing fast.
Value is Captured Earlier
Because it takes a lot less capital and people to build a proven and scalable product/model, early stage investment has become the most important and possibly the most lucrative part of the value creation chain in our opinion.
Later, Access is King
Late stage investors will only succeed if i) they can identify outliers early and ii) they can win a seat at the table during the next fundraising round (hint: money is not enough)
These structural changes, combined with deregulation, have created a once in a lifetime opportunity to form and scale new ventures, as well as new VC firms to finance them. As shown by this recent research report published by Cambridge Associate, more than ever before in the history of the Venture Capital industry, newly formed VC firms have been able to invest and capture some of the top performing startups.
Yet, the opportunities for individual investors remains limited as the industry is shifting to a new model/structure. Similar to the situation with established VCs and hot startups, an individual investor better gain access to future hot new VC funds/managers now, because the best performing funds will have limited access for existing LPs and possibly no access for non-existing LPs in their future funds.
Quality vs Quantity
The number of startups created each year has exploded and will continue to grow quickly as the cost of building technology companies has decreased by at least 10x in the last 20 years, and success stories continue to be blasted across the media as a source of inspiration and validation. The problem will be to identify the good startups as the noise level continues to rise.
Early stage growth no longer signals long term success and the ability to iterate, build and improve your product has become one of the most valuable success skills in the tech space. At BootstrapLabs we excel at finding top talent, bringing them to the best ecosystem (Silicon Valley) and supporting them in their full-cycle “build-measure-learn” iterations.
Innovation is a constant requirement for corporations to remain relevant and it is a pillar of subsistence for our society. Tech innovation will continue to grow and generate outlier returns for the best VCs (and their investors) in the industry. As someone recently mentioned to us “VC is at a dawn of a new era”. Just look at these numbers:
- 3.6 Billion unique mobile subscribers in 2014
- 2+ Billion people connected on major social media networks (1.4B FB, 250M TW, 300M LNKD, 300M Instagram)
- 120x faster online speed (6.7 Mbps US average today)
- 243 million machine-to-machine connections
- 50 Billion connected devices by 2020
- $1.7 Trillion e-commerce spend
The total of all the Unicorn valuations today is worth about half the value of Apple. Some of them will go public, some will be acquired. Apple could actually acquire most of the Unicorns and still have billions in its bank account to spare.
The slow growth in the number of IPOs is a consequence of a historical switch and the growing importance of innovation. Companies need to invest most of their cash flow in innovation, while public market investors expect short term revenue first. Many startups are building for long term success, and if they go public too early they will be unable to maximize their innovation or opportunity. As Marc Andreessen said during a recent interview: “It’s not a tech bubble, it`s a tech bust”… many of the innovation and technology companies are still undervalued and we are strongly optimistic about the great future in front of us”. So is BootstrapLabs!
Please note this is a short version of the Venture Capital Disrupts Itself: Breaking the Concentration Curse report published by the Cambridge Associates. At the end of this blog post you can find the link to access to the original file.
Venture Capital Disrupts Itself: Breaking the Concentration Curse
The Old Wives Tale … Conventional investor wisdom holds that a concentrated number of certain venture firms invest in a concentrated number of companies that then account for a majority of venture capital value creation in any given year. Therefore, LPs seeking compelling venture capital returns should only commit to a handful of franchise managers. And those are precisely the managers that do not offer access. Thus, LPs are “cursed” and will never experience the differentiated return pattern offered by venture capital exposure.
… Is Flawed. As the venture capital industry and technology markets have evolved and matured, however, more managers are creating significant investment value for LPs, with value increasingly created through companies located outside the United States and across a range of subsectors. Specifically, our analysis of the top 100 venture investments as measured by value creation (i.e., total gains) per year from 1995 through 2012, an 18-year period, demonstrated:
- an average of 83 companies each year account for value creation in the top 100 investments in the asset class for each year;
- in the post-1999 (i.e., post-bubble) period, the majority of the value creation in the top 100 each year has, on average, been generated by deals outside the top 10 deals;
- an average of 61 firms account for value creation in the top 100 investments in venture capital per year; and
- the composition of the firms participating in this level of value creation has changed, with new and emerging firms consistently accounting for 40%–70% of the value creation in the top 100 over the past 10 years.
In short, the widely held belief that 90% of venture industry performance is generated by just the top 10 firms (which our analysis shows was somewhat relevant pre-2000) is a catchy but unsupported claim that may lead investors to miss attractive opportunities with managers that can provide exposure to substantial value creation.
You can access the full Cambridge Associates report here.