My Three Immutable Laws of AI (from the 1990's)

I started in AI R&D in 1991 at Allen-Bradley followed by three years in the AI Development Group at Eaton-Cutler/Hammer. I learned three lessons that have proven to be immutable truths over the past 30 years:

1. AI is Biased - thankfully this is no longer an issue hidden on the underbelly of the beast, and the truth is that likely all algorithms are biased. There are many biases built into training data, including the decision of what training data to include and where to source it. Be aware that finding uniqueness, that diamond in the rough, is highly unlikely if the data set includes no prior examples.

2. AI Cannot Predict the Future - There's a specific bias many overlook: time. AI is biased entirely in favor of the past; it cannot predict the future. Instead, what we call "predictions" are really just the recognition of patterns from the past, extrapolated into a guess about the future. Keep in mind the hot hand fallacy because AI often doesn't. Probability itself is based on a biased assumption that we can predict the likelihood of future events, and being close, even often, is not the same as being right.

3. AI Always Gives an Answer - today we call it "hallucinations", but the problem with AI giving non-sensical answers is not new. AI can be trusted, until it can't, and there's no way to know in which realm the answer you're provided sits. Given my background in plant floor automation and embedded systems, you can understand how this was, and continues to be, a showstopper in many ways. 

AI matters. It’s helping us solve problems and gain efficiencies never realizable before. It's a great tool, but it's not a replacement for independent, critical thinking. And always be skeptical of any AI deployment where safety and security are paramount. Back in 1994, some of my AI research in fuzzy logic and neural networks was focused on self-driving vehicles. And we're still waiting.

Gold Mining or Equipment Rentals?

If you owned a gold mine, would your focus be on extracting the gold, or helping others extract the gold by renting them the mining equipment? Telcos would jump at the chance to provide equipment rentals.

After a decade and a half in the Telco world, in May of 2025 I escaped. I had joined the telco world with the belief that they would own the cloud. Who could possibly be better positioned in the burgeoning world of cloud computing than a company entrusted to transport data? I knew in my heart as a strategist that leadership was ready and understood the fatal flaw in the cloud strategies of Amazon, Microsoft and Google: large, regional data centers. In contrast, telcos had available infrastructure all the way down to the highly coveted last mile. Given the adage that compared to the cost of moving data, everything else is free; the opportunity was obvious. Able to put the compute and storage at the last mile, as I blogged about a decade ago, and telco's would rule the cloud.

Was I right about the opportunity? Yes. Edge computing as it's now called, proved it. Was I right about telco leadership seizing the opportunity? Not even close.

After stints at AT&T and Verizon I have learned one immutable truth: there is no innovation in telecommunications. That era ended with the forced divestiture of AT&T Labs during the famous 1980's DOJ breakup of Ma Bell. Executives at telcos have one idea they live and die by: maximize return on assets. It makes sense to a degree given the massive investment they've made in copper, fiber and spectrum. In the telecommunications world, innovation is outsourced. Ericson, Nokia, Cisco, Juniper, etc. What is sold as innovation is acutally integration. Telco's own the assets, everyone else owns the innovation. 

If you were involved in cloud between 2010 and 2015 you know that enterprise customers didn't trust public cloud and often railed against it. Customers wanted cloud, just not public cloud. They needed something more secure that hung off their backbone and enabled easier and faster integration with their partners (innovation that was outsourced again, this time to Equinix). And the truly visionary CIO's wanted a step further, to push process down into the network.  

While at AT&T, I navigated my way to the cloud computing product team and worked to influence their thinking by bringing an outsider point of view and the voice of our customers. I had financial services customers who envisioned pushing settlement down into the network, healthcare customers interested in performing image analysis at the edge, and one bank that wanted to buy up to 600,000 compute nodes. AT&T's NetBond product served an important tactical need, connecting customers to the public cloud providers they were starting to use. But the big opportunity was providing the secure, reliable, trusted compute and storage that Fortune 500 CIO's felt wasn't available in the cloud market. Whomever satisfied that need was poised to talk about the SDN and Edge Computing, capabilities that would threaten the hyperscalers. 

NetBond was the begining, and the end, of cloud at AT&T.

Despite providing a strong business case and making introductiosn to the founders of starups able to bring the needed capabilities into the network, there was no interest. On the surface, it's hard to find money for anything other than spectrum at a telco. But hidden under that argument there was an even better reason. While speaking at InterOp in Vegas I received a phone call from an AT&T SVP explaining my deal to sell hundreds of thousands of compute nodes was dead. I pushed for an explanation and was told the internal cost of compute was an order of magnitude greater than the hyperscalers. Gobsmacked, I asked how we made money on the customers we already had. We weren't, but luckily we'd sold less than 2k nodes. AT&T shut down it's cloud operations shortely thereafter. 

After a short stint at Tangoe, I arrived at Verizon, knowing their cloud story a bit better from previous experience. In a former life I'd been asked to partner on a plan to help Terremark avoid a second bankruptcy. I asked to be read into their strategy. Cloud computing. Yes, but what's the strategy? VMWare. No, that's a product, what's the strategy? No, that's the strategy. Well, I said in my not so humble opinion, they're destined to fail because VMWare is crazy expensive and will lock them into innovations a generation and build cycle behind the public cloud providers. Nobody listened. Verizon bought Terremark, then wrote it all off soon after I joined months before Verizon divested the Terremark assets and sold the business to IBM. What remained was Verizon's NetBond competitor, Secure Cloud Interconnect, with the same value prop: lock in the innovations of everyone else in exchange for locking in a portion of the transport; transport that will be devalued every year as customers demand lower and lower prices.

How could I have been so wrong? After significant soul searching, I realized what I saw was invisible to the generations of telco executives focused exclusively on transport. They talked in assets, whereas I talked in architectures. What I inherently understood escapated their notice: the company who owns the architecture owns the future. Telcos by nature don't believe in owning architecture, and asset owners don't innovate, they manage. 

I learned a valuable lesson painfully. Now I see the fingerprints of architecture vs assets everywhere. Why are car companies developing their own infotainment systems? Architecture. Why are streaming companies steaming to the precipice of their own demise? Assets. Why are the naysayers warning of an AI bubble? Assets.

If only I'd re-read my own articles on the evil of assets in 2012, or that economics always wins in 2013 about leveraging the assets of others. 

Now the telcos are in a race to the bottom of the cost curve, the eventual reality of every company who cannot differentiate the value of their product. Firings are the norm. AT&T fired 9.5k people in 2024, Verizon fired 13k people just before the holidays this year. Why? Their executives were sitting on a gold mine but were focused on the mining euipment.

Ugh

Newton’s Three Laws and the Public/Private Cloud Debate

For the past five years I’ve noticed a change in the conversation with CFO’s on the use of cloud computing.  I’ve always known CFOs are the driving force behind the adoption of public cloud.  Who could say no to better, cheaper, faster with lower capex and the ability to reduce the hard assets of IT which all too often anchor technology in the past?  However, today I increasingly hear CFOs push back on public cloud driven by one singular concern: predictability.

From a financial point of view, there is a critical assumption built into the pay-as-you-go model: that consumption and therefore cost is predicable.  In the early days public cloud was always cheaper, however, great strides in private cloud technology, maturation of the space, and the challenges in moving to a cloud centric IT platform have muddied the waters.  As someone who has never been a proponent of private cloud, I feel the water is as clear as ever.  IT infrastructure has never been built on predictability.  For decades, networks, servers, and storage have been designed to a “just in case” standard.  The result is tremendous bloat which is being engineered out through virtualization, but the workloads are no more or less predictable.  What’s missing is the understanding that public cloud isn’t just about capex vs opex, it’s also about momentum and friction.

Infrastructure assets are evil; they anchor us in the technology of the day and act as a damper on innovation.  I’ve lived the nightmare of being forced to architect a solution around existing infrastructure assets, sometimes merely to justify their existence regardless of their impact on the solution.  Assets grow like a planet, swirling gasses of expectation coming together forming a gravitational field which attract more mass in the form of processes and protections.  Soon the planet becomes so massive it starts attracting its own moons of ancillary assets into orbit.  Where there’s mass we have to respect Newton’s three laws.  Objects at rest tend to stay at rest and thus have no momentum, not the message the CEO wants to hear in relation to innovation.  Objects require a force to accelerate dampened by friction; the greater the mass, the more friction will work against the building momentum.  And since for every action there is an equal and opposite reaction, to generate the momentum required for change, ever increasing investments in time and energy are required.

Like the car travelling toward the horizon will get closer to the mountains but not the moon, private cloud gets a company into virtualization but not cloud computing.  I know some will argue I’m too optimistic, however I point to the success of companies such as Netflix, whose competitive advantage is the result of investing early in learning the lessons of public cloud.  I also point to respected executives like Chris Drumgoole, COO of IT at GE, making bold public statements about their migration not just to cloud, but to public cloud.  What he has said publicly many others have told me privately, but first they must get their CFO’s to look past the head fake of relating predictability to public cloud risk.