Artificial Intelligence and Investing in the Future of Technology

Our job as early-stage investors and technologists is to filter through hype, fads, and short-term trends in the world of technology. We work to cut to the core of technological innovations that have staying power, develop new markets, change behaviors, and solve wide-scale problems.

Over the last several years at ffVC, we’ve been busy researching and engaging with the community on the significance of artificial intelligence (AI), its role in technology, and its potential to improve, enhance, and evolve society.

Although it has been on the cusp of the mainstream for the past half century and has arguably become one of the biggest buzzwords in tech, we believe some of most promising developments in the future of technology — and the ways in which technology will continue to bring about massive improvements in efficiency and productivity — will be rooted in AI.

As we stated last year, we think of AI as a layer across multiple sectors, rather than a sector in and of itself. We like to draw comparisons to the ways in which mobile upended technology: reshaping the ways we live, work, interact with one another, and share information. This illustrates how we believe AI can have the same transformative effects in the decades to come.

Like all pervasive technologies, timing is just as important as potential. Several factors have coalesced over the last few decades to bring us to this inflection point.

(1) Building Blocks: computing power, data, and the cloud

Computing power has doubled every 18 months for the past half century. This trend was first observed in Gordon Moore’s now famous 1965 paper. Today, this processing power is exponentially cheaper than ever before. More accessible computing power led to an explosion in computing devices (the average American household owns three computers alone). The proliferation of computers has produced near endless quantities of data. Nearly every day, it’s estimated we produce 2.5 quintillion bytes of data — that’s a 2.5 followed by a staggering 18 zeros. Suddenly, there became a need for a single repository to store and connect these massive troves of data, giving way to the cloud.

(2) Key breakthrough: unparalleled data sets coupled with cheap processing power

Although many pertinent advancements of deep learning and neural nets took shape throughout the ’80s and ’90s, it was only until we could feed these models with enough data — supported by massive amounts of cheap computing power — that we became able to harness AI’s potential, thus realizing a major breakthrough in the last decade.

(3) Investment brings major advancements in talent, core AI technologies, and developer tools

This breakthrough brought widespread transformational potential, catalyzing a flood of capital and resources. As a result of this inflow, more academics entered the private sector than ever before: 58% of computer science P.h.D. graduates are now choosing career paths in AI, up from 38% just a decade ago. With more and more experts, the last few years alone have seen significant developments in core AI technologies like Natural Language Processing (NLP), Computer Vision, Speech Recognition, and TPUs and FPGAs on the hardware side. These advancements are becoming more accessible to developers through tools such as Alphabet’s Tensor Flow, IBM’s Watson, and Microsoft’s Cognitive Services.

(4) Foundation creates boundless opportunity/widespread consumer acceptance

With these building blocks in place, entrepreneurs and technologists are leveraging computing power, data sets, the cloud, newly available developer tools, and talent to create efficiencies and productivity never before possible. And this is only just the beginning. Coupled with further investments by major consumer technology companies, we as consumers have come to accept, and to expect, continued advances in AI technology that we use every day — look no further than Amazon’s Alexa.

A continued focus on researching and understanding the broader technological and ethical components of AI by rich and diverse groups of multidisciplinary experts means that we’ll continue to see intelligent systems being built that will collaborate with humans and complement our irreplaceable qualities.

And as AI continues to advance, we’ve made a specific commitment to invest capital and resources to help a select group of the best and the brightest entrepreneurs build the next generation of companies harnessing its potential. In July of last year, we announced that commitment with the launch of the NYU/ffVC AI NexusLab, a partnership between our firm and NYU that will provide a select group of AI-focused startups the guidance and tools to build and enhance their ideas and products over an intensive four-month period.

The program also underscores our commitment to support New York City as a growing center of excellence, talent, and innovation for artificial intelligence. Our city is home to world-class educational institutions and headquarters many of the nation’s core industries. Talented entrepreneurs will increasingly be able to work alongside incumbent players, using AI to solve problems, gain valuable feedback, and spur advances across many technical categories.

We received over two hundred AI NexusLab applications from founders across the world, and were amazed by the passion, ingenuity, and brilliance of the companies that have expressed interest in the program. But we ultimately had to select just five.

Today, we’re happy to launch the inaugural cohort of the AI NexusLab. Five game-changing companies that have been working intensively since entering the program in December 2016, and are using AI to solve diverse and identifiable problems in healthcare, robotics, customer service, marketing, and financial services:

AlphaVertex combines data science and machine learning technologies to deliver cognitive systems that provide advanced analytical capabilities to the investment community. The company monitors, links, classifies, measures, and analyzes large volumes of information across global financial markets to identify emerging trends before they become obvious, and models the impact of events on financial instruments. is an artificially intelligent medical billing and coding platform that helps healthcare providers parse and process billings and claims.

Cambrian Intelligence is a robotics operating system used to train industrial-grade robots to conduct difficult physical tasks. The company works with customers in industries like manufacturing — where robot automation is typically conducted by hand, coding every single movement of a robot — to teach robots fundamental modules that can be leveraged to build higher-order competencies.

HelloVERA is developing a more efficient and intelligent alternative to customer service by developing a natural language processing engine that is used to power AI customer service agents across various channels such as email, chat, and social.

Klustera is digitalizing and unifying the real-world connection between customers and brands with a marketing augmentation platform that helps automate customer intelligence and retention. Klustera uses anonymous smartphone WiFi signals and image recognition to transform human consumer behavior within brick and mortar spaces (i.e. airports, malls, restaurants) into data and insights.

Today, the AI NexusLab companies will appear to show off their capabilities and discuss the future of AI at our Future Labs AI Summit, where they’ll join the likes of experts from Facebook, IBM, CB Insights, FirstMark Capital, and Fast Forward Labs, to name a few.

We hope you’ll follow along with us, and the AI NexusLab, as we continue to support and encourage developments in artificial intelligence across the tech and startup ecosystem.

Interested in joining us? Applications for the second cohort of the AI NexusLab are now open through May 3. The 2017 program will officially kick off in summer 2017.

You can read more about the AI NexusLab in TechCrunch.