For any entrepreneur who has ever started a business, you know that it is not an easy task. From filing the correct paperwork to finding the most reliable employees to getting that first set of consistent customers, every single investment matters. No one understands this better than Scott Amyx, the Chair & Managing Partner at Amyx Ventures. Scott and his team take startup companies through a stringent process with specific criteria to ensure that they bring only the highest quality ICOs into the market. Seen as someone who has expansive insights on how technology is constantly changing, Scott is creating something truly amazing for the market.

Tamara: Can you share a story that inspired you to get involved in AI?

Scott: I have always been interested in AI as far I can imagine, but in terms of taking that curiosity and knowledge into the public domain was when I started writing on WIRED as a SME contributor. I was able to write two articles for them that looked at various aspects of Artificial Intelligence (AI). The first questioned our ability to reach immortality with the help of wearables, primarily the belief that mind loading or whole brain emulation might move us toward an imperishable state. My other article focused on how quickly AI is advancing right in front of our eyes. Before we know it, AI will go beyond human capabilities and essentially outsmart us. The possibilities are outstanding.

Tamara: Describe your company and the AI/predictive analytics/data analytics products/services you offer.

Scott: We are a venture capital firm that specializes in IP-intensive exponential technologies and startups. As it relates to AI/ML and data analytics, the industry applications that we prefer are in renewable energy, industrial batteries, smart cities, autonomous vehicles, Industrial Internet of Things, robotics, advanced material science, quantum computing and decentralized/ distributed computing/ wild fog/ edge analytics. Typically, we work at the epicenter of deep tech convergence — AI, IoT, data analytics, blockchain, cryptography and privacy.

Tamara: How do you see the AI/data analytics/predictive analysis industry evolving in the future?

Scott: It depends on how you define the future in terms of time horizon. In the near future, it’s broadening as well as deepening domain specific use cases to provide actionable business insights. There are, of course, technical and business challenges still to overcome — reliable and trustworthy data sources, data biasness, heterogeneous data integration, GDPR privacy regulatory mandate, AI neural network opaque results, data poisoning, fraud and abuse.

In the intermediate term, the pockets of AI use cases will begin to fill niches along the entire value chain of a business. When these AI systems are then connected to RPAs and workflow engines, we will start to see more of the value chain becoming automated, real-time and predictive. This in turn also means that the value chain can be optimized continuously to adjust statistically significant business variables/ factors to derive specific expected business results. This will then open the prescriptive data analytics wide open.

Tamara: What is the biggest challenge facing the industry today in your opinion?

Scott: There are many challenges! However, those challenges are also counterbalanced by the real optimism and practicality of businesses (and governments) seeking to reap the benefits of AI.

Setting aside the lack of talent composition of AI COE for a moment, perhaps the biggest challenge is not technical, but qualitative — the mindset. From resistance to change, irrational fear of AI, concerns of job displacement and so on, people at all levels of the organization are struggling to embrace AI. In many cases, the CXO realizes the necessity of AI, robotics and automation to squeeze out cost centers but when it comes to implementing the digital transformation, they face resistance at every turn.

Tamara: How do you see your products/services evolving going forward?

Scott: AI is still very much at infancy, contrary to popular belief. We have yet to fully harness the power of niche AI. We foresee that as new deep tech becomes commercialized such as universal quantum computers, the power of AI will take an almost vertical slope in terms of innovation and the pace of innovation. AI systems will beget more AI systems and more of the business and consumer processes will become hyper-automated. I do want to clarify that this is not Singularity, but still within the firm boundary of weak AI. We anticipate investing in these leap-bound opportunities.

Tamara: What is your favorite AI movie and why?

Scott: The now infamous Minority Report with Tom Cruise is up there. Contrary to mainstream, it was far from being futuristic. It lacked imagination as most of the technology featured in the 2002 movie was already in R&D at universities and research institutions. SixthSense gesture-based wearable computer system developed at MIT Media Lab was created by Steve Mann in 1994. Then a headworn gestural interface version in 1997 and a neckworn model in 1998. By the time Pranav Mistry showcased the SixSense in 2009 it was already in development for 15 years. This and other similar movies in the AI dystopian genre have created an over-exaggerated perception of the capability of AI. I point this out because sensationalized movies have hurt the overall AI domain by planting irrational fear in the mind of moviegoers. Those people, in turn, also happen to be employed in corporations and organizations now faced with investment decisions around AI.

On a slightly different topic, the use of human Precogs is somewhat crude as it relies on psychic power rather than AI predictive data analytics to predict future crimes. Interestingly, in the future, we may not be able to “see” to the extent of Precogs but AI systems will be able to predict crimes down to the neighborhood and most likely suspects based on deep learning from past and continuous crime data.

Tamara: What type of advice would you give my readers about AI?

Scott: Rewire your synaptic connections when it comes to AI. The common beliefs about AI sits on a dangerous precipitous of slippery slope. Most AI scientists and researchers will tell you that AI is still at an infancy. It works within a very well-defined environment. If you change the domain or worse, let it operate in the real-world with infinite variables and complexities, these AI systems would fail miserably. In addition, to suggest that certain startups or researchers are working on general AI (or AGI), the research community would find that laughable. Though Ray Kurzweil may suggest Singularity in 2029, most AI researchers puts this AI milestone past 100 years. Others in the tech community often correlate the Moore’s Law to AI. Infinite computing power does not translate into a linear regression line to Singularity.

Tamara: How does AI, particularly your product/service, bring goodness to the world? Can you explain how you help people?

Scott: Ultimately the yield comes from productivity. Our investment in AI means leaner, highly efficient and scalable operations with less CapEx and OpEx in the long run. That productivity translates into higher GDP growth.

Tamara: What would be the funniest or most interesting story that occurred to you during your company’s evolution?

Scott: We actively experiment with deep tech. Couple of years ago, we built a fun app powered by AI API services to automatically gauge the primary and secondary emotions of the user and turn his/her emotional reaction into emojis and funny memes. When we demonstrated it on stage with live audience participants, people loved the immediacy and humor.

Tamara: What are the 3-5 things that most excite you about AI? Why? (industry specific)

Scott: AI is a broad term. For this article, it’s focused on data analytics, but AI has many tentacles. Near-term, it’s NLP and computer vision related AI that we see the most use cases, but where we see the value is in the orchestration of systems as a virtual intermediary. Smart city presents a reasonably good illustration. In an urban city, there are smart transportation, smart buildings, smart surveillance, smart utilities and so on. Each of those are already a collection of systems of systems; soon to be AI systems of systems. The next evolution is managing across systems to coordinate a massively complex set of tasks. For instance, in the case of a tsunami, earthquake or terrorist attack or bombing, imagine the potentially hundreds if not thousands of tasks that would need to be coordinated. From first responders, traffic control, utility and telecommunication repair, mass transportation, crowd control, hospitals to store closures, ecosystems of AI can help orchestrate, coordinate and negotiate with other AI systems to respond in almost real-time to maximize lives saved, minimize asset damage and quickly regain normal city operations.

Tamara: What are the 3-5 things worry you about AI? Why? (industry specific)

Scott: The areas that I worry about are 1) data privacy, 2) eventual job displacement, and 3) labor segments unable to retrain or adapt to rapidly changing business environments and skill requirements.

GDPR is a sledgehammer approach to data protection that will result in costly audit, financial and general computer controls and regulatory compliance requirements. The irony is that GDPR still does not guarantee privacy especially as data will be generated, stored and shared in decentralized wireless sensor networks/ mesh networks, thanks to the increasing ubiquity of the Internet of Things. Privacy, blockchain and other novel cryptographic approaches will help but “bad” agents are actively looking to profit off IoT, increased data, and even leverage AI to help create efficiencies in their work to spread economic loss, data theft and politically motivated propaganda.

Exponential technologies will bring new jobs and business models that we can’t begin to fathom. However, not all will benefit. Think about your uncle, aunt, a friend or a neighbor. Do you see them easily adapting to data science, AI or anything remotely technically progressive? We need to account for this segment of the population that will be left behind. Unfortunately, universal basic income or taxing the robots are sustainable or realistic solutions. This is why I have recently kicked off a project called the Human Currency to explore innovative solutions, not only for those left behind, but for humanity in the context of automation.

Tamara: Over the next three years, name at least one thing that we can expect in the future related to AI?

Scott: Most of us will have own personal, ambient AI virtual assistant. Not like Fin, X.ai or Alexa but more like Jarvis from Iron Man that will help interface with everything around you, solve problems, perform complex tasks and help manage every facet of your personal and professional life. It will become indispensable and worth an army of dedicated staff.