Many of these early electronic entrepreneurs started their companies as independent laboratories. Most would get a small location for tinkering part-time. Such was the case of Hewlett-Packard in 1938. Others would pitch their ‘labs’ to bigger corporations like Shockley Semiconductor Laboratory (1956), or Fairchild Semiconductors (1957), both divisions of larger companies. The de-facto term for these primigenial companies was ‘laboratory’ and not ‘startup.’
As the electronic industry evolved into semiconductors, more and more individuals started leaving their research positions at larger corporations. These people would then raise funds to begin a “startup” company in the “high-tech” field. This was a decade (1950s) of accelerated innovation fueled by post-war efforts. In 1957 the Soviet Union launched the Sputnik-1, the first man-made object to orbit Earth. The increasing paranoia with the Soviet Union’s technological advancements acted as an accelerant for intense investment from universities like Stanford and the Defense Department alike.
In 1958 the US government created NASA and DARPA, which would effectively fuel most innovations in high-tech during the 1960s. The rapid pace needed to fuel defense projects like the guidance system for the Apollo program or the Minuteman missile project forced many of these semiconductor companies to ramp up production. Scaling high-tech at the time wasn’t easy. Every step was a struggle, and constant innovations were needed.
This high-stakes, free-money, and quick-scaling environment produced a crop of business leaders, engineers, and investors that would define our notion of “startup.”
From chips to bits
In 1968, Gordon and Moore left Fairchild Semiconductors to start their own company, INTegrated ELectronics, aka Intel Corporation. Armed with their first microprocessor, the Intel 4004, they went on to fuel the rise of the personal computer during the 1970s.
As computers became mainstream, so did the need to build software programs. The same ethos that drove the first Silicon Valley “labs” began permeating the new software startups. By then, investors had started poring into the valley, looking for new opportunities in the latest high-tech field. This migration was the genesis of a new type of investor, the “Ad-Venture Capital” investor, and heralded the modern Venture Capital industry.
The decade of the 1960s became the origin of some of the most prominent Venture Capital firms of our age. Firms like Davis & Rock (1961), Sutter Hill Ventures (1968), Venrock (1969), Kleiner Perkins Caufield & Byers (1972), or Sequoia Capital (1972) all got started within those years. They became the driving force that developed and fine-tuned the startup modus operandi that still operates today.
Venture Capital took over most of the investments from the Department of Defense, becoming the “easy money” but retained the gusto for high stakes, fast returns.
The rise of the Internet Startup
As the industry developed new computers, new tools were required, and in 1986 the DARPA-funded computer network Arpanet opened its doors to several universities. By 1989 the first commercial internet service providers appeared, and the world changed again.
Computers could now speak to one another and access information miles away. In 1990 Berners-Lee developed the first suite of web tools and the first web server, propelling us into the Internet era.
Startups in “high-tech” began moving into this new space developing the two things they knew how to do best: semiconductors (Cisco Systems, 1986) and software (Netscape Communications, 1994).
As technology moved from physical (semiconductors) to digital (software), the barriers to entry began to decrease. With widespread computers and universities interconnected through Arpanet, a new wave of students learned how to code software faster than ever before. Innovation started to spread and the challenge of being in the right “lab” at the right moment began to fade. The pace of innovation accelerated dramatically, and the number of high-tech web-based companies reached a new record.
This dramatic shift got captured in a redefinition of what we understood by “startup.” Suddenly, the usual “high-stakes, easy-money, fast-scaling” took on a new meaning. With an ever-expanding pool of startups, cutting-edge innovation began to dilute and decrease. This change began shifting the notion that startups were always high-stakes. The other side of the coin was that investment in these types of startups became mainstream. The consequence was a sharp increase of less sophisticated investors playing the game, turning the “easy-money” into “super-easy-money.”
And so, a new startup breed had appeared, the Internet “startup”; An incremental innovation, super easy money, an infinite scale company.
The limits of the web
And the Dotcom Bubble (2000) came and went, and innovations established during the 90s paved the way for more bandwidth, more connectivity, more devices (smartphone revolution), and obviously, more scale (social media). Enter Web2.0.
The credo of “more, bigger, faster” became the war cry of a new wave of investors. Web2.0 brought substantial changes, but startup-wise it produced even faster democratization. Now anyone, from anywhere, could create an Internet “startup.” Hardware was abstracted through cloud services, software was abstracted through libraries, frameworks, and no-code platforms, and connectivity became ubiquitous and cheaper than most utilities.
This erosion of the barriers of entry and the digitalization of our societies has suddenly turned all new companies into de-facto startups. All new businesses followed a similar pattern of fundraising (VC, Corporate VC, foundations, crowdfunding, fund of funds, etc.), product building (Design thinking, agile, lean, etc.), digital marketing (social media, digital ads, analytics, etc.), and even exit strategies.
The one thing that didn’t change much was the definition. As our industries have become increasingly digital, we’ve changed the moniker of Internet “startup” for Fintech, Healthtech, Martech, or Proptech startups. Now what defines a startup isn’t the Internet anymore but the vertical it operates in. Even that is becoming hazier and hazier as we deploy technology that fuses different verticals (i.e., Fin-Insur-Prop tech startups).
As every venture turns into a startup, we’ve had to introduce new terms to differentiate between them. For example, we now categorize startups not just based on their verticals but by their business scale. And that’s how we now split startups between early stage (aka new and small) and growth/scale-ups (aka expanding and with a specific headcount). Needless to say, what company gets labeled depends entirely on the perception of the local ecosystem.For example, what in Europe we consider a “growth” company, Silicon Valley would classify as “early stage.”
In the same way, we now differentiate startups based on their sequential funding rounds (early stage, Series A, B, C, etc.) or even by their perceived value (unicorns, companies valued at over $1 billion; decacorns, companies valued in over $10 billion; and even hectocorns, over $100 billion).
Despite all these terms, the fundamental startup definition has remained the same. But this has been changing in the past few years.
The new frontiers
As the saying goes, history doesn’t repeat itself but rhymes. As the friction of doing a startup has decreased, many voices have been pushing for a return to cutting-edge innovation. Let’s go back to “high-stakes, easy-money” again.
This shift has been happening for a while, and it’s been associated with several different technologies. During the 50s, it was electronics; then it became semiconductors in the 60-70s, computers in the 70-80s, the Internet in the 90-00s, and smartphones in the 2010s.
Nowadays, we could say that Artificial Intelligence, and in particular, Deep Learning, is one of the technologies driving a new era of high stakes. And for clarity’s sake, when I say Artificial Intelligence, I mean the building, training, and deploying of massive models, not the use of third-party AI services. But it’s not the only one. Advances in quantum computing and communications, fusion reactors, batteries, aerospace technology (frontier tech, space tech), Blockchain, or biotechnology (nanomaterials, synthetic biology, etc.) have also been driving much of this.
All these technologies are increasingly being grouped under what we now call Deep Tech, startup companies that possess proprietary technology derived from their scientific research. Some people call these Hard Tech startups, and they aren’t wrong.
There has been an increasing movement to support and return to developing startups in the hard sciences. Back to the “labs,” back to the garage, and onto tackling challenging problems for society. In the same way that World War II and the Cold War spurred a dramatic wave of hard tech, the current geopolitical environment is catalyzing a similar stimulus.
The search for sustainable energy, food, water, transportation, or urbanization is attracting not just increasing research but funding too. New pandemics and the need to produce an ever-growing amount of new compounds (food, drugs, fertilizers, advanced materials, etc.) are fueling the growth of biotechnology and unleashing the era of synthetic biology.
These Deep Tech startups are different. They don’t get built in a month; their need for innovation at all steps is exponential; the return on the investment is longer and riskier; their need for specialists is more acute and harder to meet; their market scale is small and limited. That is, they’re “high-stakes, hard-money, big risk .”As it happened before, what’s now “hard money” is becoming government-funded semi-free money.
The shift towards Deep Tech will entail significant changes in the system. Deep tech requires savvy investors, highly specialized teams, and broad collaboration between experts. To achieve the coveted scale, each Deep Tech vertical will need to deploy a novel infrastructure and wait. There won’t be one-click solutions or millions of clients awaiting the products. It’s time to return to hard work, disruptive creativity, and patience. Those that get in now will become the future Fairchilds, Intels, or Apples of the world.