By Igor Sill, Geneva Venture Partners
Billionaire investor Mark Cuban is not bashful about discussing his thoughts on artificial intelligence (AI), predicting that the next richest founders will be AI entrepreneurs.
Cuban says if you want to stay ahead of the curve as future entrepreneur: “I am telling you…the world’s first Trillionaires (that’s with a “T”) are going to come from somebody who masters AI and all its derivatives, and applies it in ways we never thought of.” “We are going through the process where software will automate software, automation will automate automation.”
This movement exploded following Google’s acquisition of UK-based Deepmind. This AI startup’s mission was to “solve intelligence” and was backed by visionary investors Elon Musk and Peter Thiel. Since its integration into Google, Deepmind has transformed Google in oh so many ways. All Google searches are now piped through Deepmind’s artificial neural network given its efficiency over human intervention in finding relevant and accurate search results.
For the past two decades, growth rates and unicorn valuations have defined venture investment funding success for most technology companies. Every venture capital firm likes to insist that they are strategically unique and “different” even though they usually all operate from this very same playbook.
I contend that angel (seed) investors contribute far more value to a start-up than a committee-oriented venture firm partnership. An angel investor with prior high growth IPO experience with sufficient “success pattern matching” intuition combined with an extensive industry network offers a higher probability of startup success, while committee-driven VC firm decisions are just that.
Common VC firm mistakes are: misevaluating the founding team’s abilities; playing the Shark Tank valuation trap; misunderstanding the target market; Committeethinkology; assuming that a market is too small; presumes that a market already has an entrenched leader; and most importantly, lack of interest or time in mentoring, coaching, contributing and opening critical partnership doors. After all, they’re investing someone else’s money, not their own.
When coupled with seed entrepreneurs pounding VC doors, the overwhelming selection challenge becomes all too consuming and is frequently relegated to the firm’s low level Associates. Thus, the majority of mega million venture firms have moved to the Series A and later stages where quantifiable metrics exist. Both Siebel Systems and Salesforce avoided traditional VC firms until much later financing rounds, instead relying on supportive angels for their seed and Series A financing. To address this widening gap in startup funding, founders are seeking experienced angel investors as their clear first choice.
In backing start-ups, I became acutely in tune to the founders’ mindset and would rally behind those that focused on building with an attitude of unselfish responsibility and social conscientiousness. My relationships and my network became theirs.
Harvard’s Clayton Christiansen proclaimed that disruptive innovation is a process in which a new offering initially takes root in simple applications at the bottom of a market, typically by being less expensive, better and more accessible — and then relentlessly moves upmarket, eventually displacing established market leaders. Salesforce’s upstart dominance over Siebel Systems is a well recognized Silicon Valley disruption example. Zoom video over Webex and Skype is yet another, etc., etc.
New Age Disruptive Market Opportunities — AI, IoT, ML, Cybersecurity
The IoT (Internet of Things) is a system of interrelated computing devices, sensors, mechanical and digital machines with the ability to transfer information over a network without requiring human interaction, so this would includesecurity systems, thermostats, cars, electronic appliances, lights in household and commercial environments, alarm clocks, speaker systems, vending machines and most things imaginable, plus some. And, that is just the tip of the iceberg.
The acceleration in the scope, scale and economic impact of IoT when coupled with Artificial Intelligence (AI), Machine Language (ML) and cybersecurity technology have the potential to be an incredibly positive force in the world. New implementations in artificial intelligence (AI) and machine learning (ML) are incorporating algorithms to prevent cybersecurity attacks while securing software vulnerabilities, allowing security experts to conduct more higher-level examinations of threats.
Essentially, every appliance and device we use today, and even those we have yet to imagine will be affected. In fact, IoT and more importantly, The Industrial Internet of Thing revolution (IIoT), is already well on its way. According to a new market research report Digital Transformation Market (IoT, Cloud, Big Data, AI, Cybersecurity, IT, Telecom) published by Meticulous Research®, the digital transformation market is expected to grow at a CAGR of 22.7% to reach $3,294 Billion by 2025. The cybersecurity market size is projected to reach $258.99 Billion by 2025, growing at a CAGR of 11.9%.
The digitization of machines, vehicles, systems, sensors and other elements of the physical world is an innovative idea providing powerful solutions. We are already experiencing a real impact by changing how goods are produced and distributed, how products are serviced and refined, and how doctors and patients manage health and wellness. Business-to-business enterprise applications will probably capture more value — nearly 70% over consumer uses.
Another significant disruptive force is the degree to which the world is much more connected through global trade and movements in capital, people, and information (data and communication), what politicians call “flows.”
If businesses execute digital transformation properly, integrating the physical and digital worlds could generate up to $11.1 trillion a year in economic value by 2025. That’s a huge disruptable market opportunity. An angel investor’s financial heaven.
1. Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data
2. Data Science Simplified Part 1: Principles and Process
3. Getting Started with Building Realtime API Infrastructure
4. How I used machine learning as inspiration for physical paintings
Real time AI application development infrastructure is a deep, complicated space that’s going through a massive transformation. Palantir, has successfully exploited this segment with great execution skills, building a culture of working for the common good and building a future where data can be leveraged to serve people, create value and improve the quality of life. Palantir was founded back in 2003 and they, along with many others (Microsoft, Lucid, IBM, Amazon, Facebook, Apple, Nvidia, etc), developed legacy tools, and legacy enterprise software applications and outdated platforms. There are tremendous numbers of old generation, outdated and vulnerable software applications operating out there. As an early stage seed investor, I seek out disruptive technology application solutions suitable for large, addressable global markets, and driven by brilliant, passionate, tried-and-proven entrepreneurs. Once the right technology is beta-tested, then proven, it’s all about customer traction and team execution. Closing customers early in a startup’s life is essential to avoid building “yet another” similar solution. So, I suggest, entrepreneurs build applications that businesses love. Ask, what is it this industry really crying out for, what does it really need? What stands in the way of achieving this need? One major reason for a technology company’s breakthrough success is its dynamic, constantly evolving business plan, tuning into the market’s needs, seizing new opportunities and always striving for much bigger customer successes. Of course an entrepreneur’s survival instincts are an important and powerful characteristic. Somehow, the survival instinct is closely related to luck. I’ve found that the harder one works, the luckier they become. And, of course being at the right place at the right time helps, so, one needs to survive long enough in order for that to happen.
Seek out Investors Who Understand and Appreciate your Business
Most VCs focus solely on early traction analytics, assessing evidence of strong traction as sufficient to validate product acceptance. Ask other founders who have worked with the VCs you’re considering to tell you about their biggest contributions, their biggest value, their corporate connections. I contend that connecting with good investors, qualifying them and asking them about their enterprise, AI, ML, Cybersecurity, SaaS experience may be a very important element that a “partner” provides. A value-added investor should be part financier, business development advocate, strategic alliances door opener, executive search consultant, deal-maker connector, fundraiser and sound business advisor.
It takes a very special skillset to bridge that gap, and to fund, support and build a community around a next generation transformative go-forward vision.
One such start-up which I believe has all the elements for success: an experienced leadership team, next-generation AI disruptive technology in a huge and growing market and the ability and skill to execute, while demonstrating social benefits of its technology capabilities when it comes to corporate values, is Walnut Creek-based VantIQ.
A successful startup is often driven by the vision of its founders and its core leadership team and that is what the founding team of VantIQ has achieved. VantIQ has created and developed a technology stack for the rapid design, development, deployment and operation of next-generation, real-time AI & IoT applications that transforms business processes.
With AI, privacy, and behavior-manipulation concerns, modern tech companies today face significant and complex problems. Thus, it is important to demonstrate clearly the social as well as economic benefits when it comes to corporate values. I found that VantIQ shares a deep commitment and intense sense of purpose in the role they play in society and how they create value for their customers. I believe the best technology businesses are intrinsically aligned with the long-term interests of society.
Leadership team
I have tremendous confidence in VantIQ’s co-founder & CEO, Marty Sprinzen, the former founder of Forte Software and former COO of Ingres Corporation. Sprinzen along with co-founder & CTO, Paul Butterworth and his team built one of the most successful scalable enterprise-class distributed applications software companies in history. Sun Microsystems acquired public-traded Forte Software for $540 Million in mid 1999 causing ORACLE’s Larry Ellison to acquire the combined Forte/Sun Microsystems so as to offer ORACLE’s customers and prospects a sustained technology growth path.
Market & Competition
Founded in late 2015, and now with over four years in development, revisions and successful deployments, I believe that VantIQ is several years ahead of its competitors. The company has made incredible market inroads here in the US, as well as UK, Europe, Japan, China, LATAM and more than quadrupled its growth last year with even greater growth prospects this year, despite the pandemic. VantIQ is seeing dramatic growth globally across all industry sectors driven by digital transformation mandates that encompass big data, AI, machine learning security and IoT.
Summary
My pattern-matching intuitive approach has been formed by a set of experiences about how businesses function during a time of fast-paced innovation and competition. Winning the customer confidence of Fortune 500 companies is not easy, but VantIQ has demonstrated it can do so even though it’s still a growing startup with no traditional VC firm funding. I believe VantIQ can and will be the category leader in AI, IIoT platform solutions and applications globally. That is why I made a substantial investment and commitment in VantIQ’s leadership team: Marty, Paul and Miguel.
Credit: BecomingHuman By: Igor Sill