Mark Montgomery is the Founder and CEO of the KYield, Inc. His interest in AI goes back to 1984. Mark recounts the days when he and his wife owned an inn that hosted a variety of individuals and groups, including UW, PNNL, HP, and Microsoft. Two decades later the head of research at Microsoft has referred to Mark's inn as the 'learning' inn. He remembers his late friend Russell Borland who was a frequent guest and was an early employee of Microsoft and the key person for Word among other products. Mark says Russell joined his lab as a board member and advisor just before retiring from Microsoft in 1997.

Experimenting with Technologies and Firms

In 1995 Mark founded the knowledge systems lab as a small business network, and in 1997 he launched GWIN, which was a cutting-edge social/learning network. "I ran the lab solo from our property in rural Arizona. The idea for KYield came to me while operating GWIN almost 25 years ago now", says Mark.

But soon he realized that it would take at least a decade before the technology would be viable and during that time, Mark incubated KYield while running an early-stage VC firm. In 2006 he filed a patent application covering a portion of KOS which is what we today call the distributed AI OS. He states that the AI systems patent wasn't approved until 2011. Meanwhile, in 2010, he announced his healthcare platform, and in 2012 Mark tested the basic data structure with a mutual vendor on one of the largest financial networks.

"From 2009-2016 I was also a frequent guest at the Santa Fe Institute. I've engaged with senior management in many of the world's leading organizations over the last decade", adds Mark.

AI Systems that Taught Hard Lessons

Mark mentions the hard lessons he learned during his journey from the idea to the commercialization of large-scale AI systems. He says that those experiences were the reasons which profoundly shaped him. As running the early lab and networks is critically important, he notes that Russell Borland, Les Vadasz, Vint Cerf, and other board members, and many others have played a great role in developing the lab. Mark believes that several years as a frequent visitor at SFI had certainly influenced his journey too. Mark remarks another big impact that has shaped him that was when his brother was diagnosed with ALS and it was the same year when he was motivated to accelerate R&D.

The Two Attributes for Success

Firstly, Mark says that he didn't set out to become a leader or an influencer in AI. The most important part he believes is to invest time is to understand the science, engineering, operational, and business environments, without which he affirms to have no credibility. To become competent in AI systems, he presumes that it requires consuming tens of thousands of papers across several disciplines, including computer science, mathematics, and physics, though he also recommends economics, neuroscience, and psychology.

Secondly, he stresses upon getting some good hands-on experience in an applied lab. He firmly trusts that when an individual can demonstrate rightly, they are capable of understanding science and engineering better to forge new ground, that's when he says one can become an influencer.

Fostering Innovation to Stay Ahead

"We've had a great many direct discussions along the way of course, but when we first approached senior management teams in the world's leading organizations, not a single one had ever considered the concept of enterprise-wide AI systems", says Mark. He feels that his experience has been a bit like that expressed by Steve Jobs – "Our task is to read things that are not yet on the page". Now, Mark takes pride in saying that the KYield is attempting to remain many years ahead of the herd.

Knowledge on Disruption Tech which Leads the Way

Mark strongly affirms that disruptive aspects of the technologies are just beginning to have an impact on healthcare, education, and government, which are resistant to change yet also the sectors society needs to change the most due to economics and need.

He says that we are already at the stage where CEOs of most organizations should be well along in the process of becoming experts in AI systems. Otherwise, he believes that they won't be able to even recognize whether ana device is good or bad and it may turn out to be one of the greatest problems that business nations would face.

Embracing the Challenges Optimistically

The first decade of KYield was devoted primarily to theoretical research and technical viability and Mark on the other hand didn't formalize the underlying mathematical theorem until a few years ago. After which he met with a CEO of a leading tech company in 2007 and had some partnership talks and his scientific fellows reported that KYield was impossible. Though it wasn't impossible, Mark thought the CEO understood it.

Mark's commercialization journey began after the initial patent was approved and data structure got tested. KYield was initially limited to organizations that had a supercomputer, but in 2010, he estimated the cost of a primitive pilot to be about US$100 million. Even though he didn't sell any, most showed a high-level interest in buying it.

When the AI revolution really began to take off in 2014 followed by tens of billions of dollars of investment, there was an increase in performance which led to the reduced cost for his KOS by more than a factor of 10.

Mark says that KYield has come a long way in the 25 years since the idea stage. And he also wrote an article on the top ten obstacles to successful enterprise AI recently for those seeking more detail.

A Future Representing SGM

In this context, Mark talks about his most recent invention called the synthetic genius machine (SGM), by reflecting much of the last decade in R&D at KYield. He thinks the SGM represents the future quite well as it will provide the narrow superintelligence as a service at the confluence of data physics, AI, and quantum computing. Through this, his primary value to society will be accelerated discovery, research, and development.

Words of Wisdom to the Buds

Advising the budding leaders' Mark stresses, "Be prepared. Many people have jumped on the AI bandwagon in recent years claiming to be an expert who hasn't done the work. They need not have a Ph.D., but frankly, they should have the equivalent of multiple advanced degrees combined with at least a decade of applied experience".. He finally adds that KYield has disclosed their 15 EAI management principles recently, which is a good place to start.