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A 2017 Frontier-Tech Founder’s Atlas

Three reasons, and five places to seek treasure in a fantastic seventeen

By Shahin Farshchi

Today’s founders are yesterday’s explorers. They build and captain crews that overcome seemingly impossible odds. They are also rewarded with great treasure for their discoveries. Today, the waters are less forgiving, crews can instantly disperse, and treasures can elude the very best. However, it is a better time than ever to build a magical team around solving a big problem with disruptive tech, or seek to join an amazing startup. Why?

The half-life of products and technology keeps getting shorter. Large companies are built and tuned to deliver products quickly — products that are getting obsolete at a faster pace than ever. New products that integrate functions obsolesce some products while creating entirely new product categories. For instance, smartphones obviated digital still cameras, but created opportunities for startups doing photo sharing and editing. The commoditized business of building cheap cameras was laid to waste, while billions in value was generated by the likes of Instagram, Pintrest, and SnapChat. Unfortunately large companies are not as effective as startups at re-tooling their capabilities and adjusting their cultures to enter entirely new product categories. Startups are well-positioned to dominate these nascent markets.

The toolsets are more powerful than ever. Amazon Web Services was just the beginning. Google, Amazon, and Microsoft’s arms race for offering the most powerful developer tools has been a boon for founders. Computer vision, data analytics, and deep learning toolsets are free and abundant. Meanwhile, Asian contract manufacturers, amid stiff competition, are making it easy to get hardware startups into production, while some go the extra mile of providing end-to-end services starting from design for manufacturing to customer support.

The funding climate more conducive to funding transformational ideas: Investors can’t ignore the massive rewards that come with funding successful startups. Tens of billions of dollars has been pouring into US Venture Capital per year, with 2016 expected to be on pace to be the largest in ten years. But beware, this upward trend of of investment into venture capital funds is contemporaneous with investors deploying capital at a lower rate. This is great news for brave founders with magical teams pursuing bold ideas, but bad news for incremental, “me-too” startups.

U.S. venture funds are on track to raise more capital in 2016 than they did in years prior to the great recession. However, the rate at which they have been deploying the capital is at its lowest levels since 2012. This trend is favorable for founders solving unique problems with unique technology, but challenging for other fledgling startups.

The trends, tools, and capital are the fuel, while the onus is on the founders to build the kernels of tomorrow’s billion-dollar economic engines. While we’ve seen an explosion of innovations in machine learning and AI, we can expect hundreds of interesting businesses that leverage those innovations. Furthermore, the abundance created by breakthroughs in automation will inevitably lead to scarcities which will form the basis of yet another generation of interesting businesses:

Driverless cars as the next “platform”

The term “platform” probably started with PCs, followed by the Internet, the cloud, and mobile. Behold the tomorrow’s platform: driverless vehicles, which accelerated from novelty to certainty. The first challenge is implementing driverless vehicles that are safer than humans; where Uber, Google, Zoox, nuTonomy and others have made tremendous progress. There could be even larger opportunities around making driverless cars accessible and interoperable with conventional human-piloted cars: big auto manufacturers, startups, and academics are exploring the benefits of connecting cars to ease traffic and increase safety. The ride-hailing giants expect to leverage their massive distribution and reach to end-customers to offer driverless transportation as a service. Zoox is reinventing the vehicle from scratch with the vision of offering an unforgettable driverless transport experience. Blackberry made a move into connected cars with its acquisition of QNX, a middleware layer that sits between the vehicle and connected car platforms such as Apple’s CarPlay and Ford’s SYNC. Others startups are aiming to secure vehicle systems from hackers inside and outside the vehicle. I encourage founders to imagine a not-too-distant future of autonomous vehicles being widely available; how can they further improve, and secure the driverless transport experience? Historic examples are productivity software on top of PCs, search on top of the internet, advertising on search, analytics on social, services on the cloud and mobile. Driverless cars will be the next “plarform.”

The progression of the automobile has led to the destruction of some companies, and creation of behemoths serving the scarcities that came about as the automotive industry matured. Distributors of horse feed gave way to service stations. Manufacturing lines marginalized coachbuilders and brought about automotive parts manufacturers and distributors. As vehicles matured and become more reliable, comfort and luxury products and services such as performance parts and car stereos became popular. Tomorrow’sautonomous cars is an opportunity for billion-dollar startups today.

Building big businesses leveraging AI

There has been an explosion of AI startups; CBInsights has crated an excellent snapshot. Many of these companies are led by AI and deep learning experts attempting to revolutionize healthcare, e-commerce, business-intelligence, and automate unskilled labor. Most have done an excellent job applying AI and deep learning to automate tasks that make humans more productive, as well as predict future trends and consumer behavior. Many predominantly-technical founders are wisely attempting to engage with customers early on to integrate the innovations into their current workflows. Some founders have gone a step further by partnering on day one with individuals who have an intimate knowledge of their target customers, as cofounders. It is inevitable that AI and deep learning will have a major role in most industrial and consumer products, just like how many products are “smart” and “connected” today. The question is whether AI will form the basis of many transformational, iconic companies, OR remain as a powerful tool for incumbent players starting with Apple, Google, Amazon, and Facebook, and eventually trickling down to all businesses. The challenge for founders is not only solving problems leveraging AI, but also building great products that can underpin interesting businesses.

Building big business by accessing space

The Cold War, Space Race, and science fiction mobilized thousands of talented young engineers to solve hard problems around gaining access to space. Our craving for gadgets pulled down the cost of incredibly sophisticated sensors, radios, and compute power. When coupled to our over-half-century experience building and launching spacecraft, space is now accessible to high school students. Planet’s founding and success has proven that incredible businesses can be built around NewSpace, and we are still in the early innings. Planet was the first to offer high-revisit-rate optical earth imaging for mapping, finance, insurance, and agriculture. Other upstarts are aiming to see through clouds and the dark by transmitting and sensing radio waves rather than relying on the sun to light up the earth, thereby offering customers more persistent data. Small launch vehicle companies are trying to make it cheaper and faster to get satellites into orbit. Some are even trying to spool up labs in the International Space Station to enable scientists to outsource microgravity research. Unfortunately, the founding teams of most space startups are dominated by scientists and Trekkies. Some are starting new companies as an extension of traditional imaging, telecommunications and launch service companies — most of which don’t fit the traditional venture model. I encourage experts across all industries: sports, media, entertainment, hospitality, healthcare, insurance, e-commerce, transportation, and beyond to look at how they can leverage cheap access to space to enable disruptive businesses.

Supercharging human intelligence with artificial intelligence

Deep learning algorithms were inspired by how we think the brain works. Behold the power to be gained by understanding how our brains actually work. Bryan Johnson has proposed an interesting approach toward augmenting human intelligence with artificial intelligence: directly coupling computers to our brains. We have already experienced tremendous achievements in computer vision, speech, and natural language processing by building systems — neural nets — that simply mimic our limited understanding of the human brain. To further our understanding of the brain, researchers have used dense, high-speed, implanted electrode arrays, which until recently weren’t even wireless. Moore’s law and advances in low-power wireless technology have allowed researchers to see and stimulate single neurons with high fidelity, leading to interesting brain-machine interfaces. Unfortunately, having to implant devices into the brain has limited its application in human patients to those with severe Epilepsy. Some creative researchers have developed non-invasive methods of observing and managing brain activity; though they cannot measure brain activity at the cellular level. The non-invasive devices can capture brain activity in a way that’s analogous to listening to people in a stadium by holding a microphone on the 50-yard line. Researchers are experimenting with infrared imaging, in-ear electrodes, and advanced algorithms to capture high-fidelity signals non-invasively, as well as trans-dermal direct-current stimulation to safely stimulate the brain. How far away are we from coupling computers directly to our brains? Can consumers one day command machines with their thoughts, or access the corpus of human knowledge through a simple mental inquiry? Can humans stay ahead of AI by augmenting themselves with it? Our smartphones and now Amazon’s Alexa act as our eyes to the world and a powerful lever — will they improve to the point where they can simply predict our needs and infer our thoughts?

Our smartphones bring the entire corpus of human knowledge to our fingertips. Unfortunately we are bandwidth-limited by having to look at tiny screens and and tap clumsily on touch screens. Can scientific methods used to understand brain function augment the consumer electronics we love to create a broadband connection with our brains? Can this connection eventually augment our intelligence with the most recent advances in artificial intelligence, resulting in all humans being super humans?

Disrupting education

The fundamentals of our educational system has not changed for almost a century. Primary education prepares us to function in society through high school. Young people then immediately take on significant debt for a college education. We commit to repaying this debt for many years post-graduation in anticipation of stable, high-paying jobs. As alluded earlier, today’s businesses are being disrupted faster by new entrants, automation is becoming more prevalent, and tools used by workers are constantly changing. As a result, every worker needs constant training, therefore; why do 4-year Universities saddle students with so much debt and leave it up to them to stay current on what’s needed to stay competitive on the job? We are seeing innovative ideas where investors pay for students’ educations in exchange for a portion of their future earnings — but there is still plenty of room for innovation.

I expect Universities to depart from episodic training that isn’t useful for tomorrow’s jobs. Universities must engage in partnerships with their students; a partnership where a they get paid when their students get paid. I encourage the best and largest Universities, especially those with large, perpetual endowments, to experiment with the notion of being lifetime partnerships with their students. Students should enter the workforce after receiving the most basic training, and choose to continue pursuing specialist degrees in after experiencing working in those fields, or choose a different field altogether. University partners must keep students current with all the requisite tools needed to accel in their respective careers. Training programs need to be tailored to individual needs, as opposed to batch processing students based on assumptions around what skills will needed on the job. Udacity and EdX are just two examples of new institutions aiming to disrupt education. I expect many more startups to gradually shift today’s anarchronism of an educational system toward a community of lifelong partners constantly bringing security and skills to our workforce.

Batch-processing students may have been effective in the middle of the twentieth century. However, today’s constantly-evolving jobs make a basic college education less useful. Universities need to train students more efficiently and get them out into the field faster, with the expectation that they will re-engage for further specialization, or re-training for a different field altogether. Universities need to become long-term life partners, not just episodic trainers. Startups can have a key role in this transition.

At Lux, we are sailing full steam ahead, aiming to partner with world-class founders tackling world-scale problems with world-changing technology — seeking the billion-dollar treasure coupling frontier tech to billion-dollar problems.

Shahin is a partner at Lux Capital. Based in Silicon Valley, he invests in space, robotic, AI, transportation, VR and brain-tech companies; follow him on Twitter.



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