Weaving Together My Life Story In A Series Of Blogs

The blog has always been a great platform for storytelling. Over time, I have shared many things about my history, my present, and goals for the future - they are:

My Life Story - Have you ever thought about the impact of big decisions that you made in your life? How about the small ones or the ones made for you? How would have your life turned out if things went the other way?

My Love Story - Michelle and met on October 15, 2010 in a serendipitous way. We were both part of a charity in Raleigh, NC and one night at a dinner struck up a conversation about many things - including our love of travel.

My Housing Story - After 13 moves and stops in three Canadian Provinces and three U.S. States, here is my journey in pictures from the Northwest to the Southeast of North America.

My Car Story - I have the dubious honor of getting speeding tickets on all 6 driveable continents - lucky that there are no cars in Antarctica! Did I ever tell you the time I passed the Polizia in Italy with my mom?

My Travel Story - The story started with a "Rollerblades and Red Bull" journey to 100 countries. It is now expanding in every direction after hitting 7 continents and the 7 wonders of the world (most with kids in tow).

My Nautical Story - I am pretty sure the love of water started in 1972 when I was six weeks old and my grandparents Bob and Dona McBain retired to Shuswap, British Columbia, Canada, and built a log cabin.

My Crazy MBA Story - In the summer of 2017, while climbing Machu Picchu, Peru as part of my wife Michelle’s International MBA from Manhattan College, I thought – why not me?

My Hockey Story - As long as I can remember, I have been playing hockey. Over four and a half decades and thousands of games later, I still lace them up a couple times a week, year-round.

My Cycling Story - When the Covid-19 pandemic first took hold in March 2020 we responded quickly as a family - including strict stay at home orders and no outside contact until we could get a handle on the risks. My attention now turned to exercise - and biking across North America (virtually).

My Retirement Story - I have no interest in disconnecting fully from the work that makes me so fulfilled. I could never see myself  in bingo-playing retired life. I want to stay curious, engaged, and adding value past the (very specific) date in 2034 that I am aiming for.

My Christmas Story - Whether traveling to see family, or going to Disney or Hawaii, or simply staying home - the season is packed with memories of family and friends.

My Music Story - My favorite music can be best defined as sad / emotional / multi-level slow music. Oddly, it is opposite of my worldview - which is normally overly-positive and optimistic.

My Movie Story - Oddly enough, I think Pretty Woman made me very interested in business. I named my cat Austin Powers - oh, and yes, "Danger" is his middle name. Our current dog is named August Rush (Auggie Doggy). Movies such as Planes, Trains & Automobiles, Forrest Gump, & National Lampoon's Vacation have become soundtracks to my life.

These are all my personal stories. My business stories wrap around channels, partnerships, alliances, and ecosystems and can be found here. 

Also business related, on this platform I named the top 100 most visible channel influencers and top 100 global women in technology groups that continue to get thousands of visitors per month.

Thanks for taking a walk with me through memory lane!

 

The "Not In My Backyard" (NIMBY) backlash against data centers has turned the physical infrastructure of artificial intelligence into a fierce national land-use battle.

For years, the tech industry marketed the cloud as an invisible metaphor, but AI’s massive appetite for resources has broken that illusion, forcing industrial-scale installations into local communities.

Currently, the United States houses over 4,500 active data centers. To fuel the AI boom, an additional 700 to 1,500 facilities are actively under construction or in development nationwide.

Check if one is in your backyard here: https://www.businessinsider.com/ai-data-center-near-me-location-tracker-2026-6

This unprecedented footprint has triggered a severe public backlash; a recent Gallup poll revealed that 71% of U.S. adults now oppose data center construction in their local areas.

Opponents cite strained local power grids, skyrocketing utility bills, immense water consumption for cooling, and disruptive noise pollution. Local rejections and high-profile lawsuits, such as the citizen-led suit against the 9-gigawatt Stratos project in Utah, are stalling major rollouts.

Moving forward, the trend will shift from urban mega-hubs like Northern Virginia to rural regions, with 67% of planned facilities targeting rural areas to avoid localized resistance.

To survive, developers must pivot to energy-aware hybrid infrastructure, secure independent power via natural gas or small nuclear reactors, and engage transparently with communities to balance national compute demands with local quality of life.

We are entering an unprecedented cycle of IPOs where we will have three companies all join the trillion (or likely multi-trillion) dollar club on day one.

SpaceX (which has xAI, X, and Grok inside), Anthropic, and OpenAI have taken the "unicorn" story to the next level.

(A unicorn is startup company valued at $1 billion or more by private investors before going public.)

The story doesn't track for all unicorns though. As of March of 2026, there are 1,356 total unicorns across all industries with 485 of them being in enterprise technology.

Fun facts:

1. The San Francisco "Bay Area" alone has 171 enterprise tech unicorns — more than 1 in 3 globally.

2. The US 🇺🇸 isn't just winning — it's lapping everyone 341 of 485 (70%) are American. The next four — China 🇨🇳 (26), UK 🇬🇧 (17), Israel 🇮🇱 (16), France 🇫🇷 (13) — combined still don't match New York City alone (42).

3. $4 trillion+ in combined value, but wildly top-heavy. The median valuation is just $1.7B — barely over the threshold. The three companies above represent 2/3 of value.

4. 2021 was a unicorn factory 148 of 485 companies — 30.5% — earned unicorn status in 2021 alone. That's more than the entire decade of 2013–2020 combined.

5. 99 companies are worth exactly $1 billion. One in five enterprise tech unicorns is sitting right at the minimum threshold, suggesting many are valued at the round number they were last marked at, not true market price discovery.

6. Sequoia Capital's portfolio is worth more than most countries' GDPs. Sequoia appears in 52 companies with a combined valuation of $2 trillion+ — mostly because of OpenAI and Anthropic.

7. The big three investors are everywhere Andreessen Horowitz (41 companies), Sequoia Capital (39), and Accel (38) appear in roughly 1 of every 12 companies on the list each.

8. The average time since joining the list is 4.1 years. The oldest — Mu Sigma Inc. (data analytics, India) — has been a unicorn for over 13 years with no exit. Lookout and Magic Leap have been waiting 12+ years.

9. Israel punches well above its weight with 16 companies, $29.4B in combined value, from a country of 10 million people. That's more unicorns per capita than any nation except the US, and ahead of Germany and Australia despite being a fraction of their size.

10. The AI wave is just getting started 88 companies joined in 2025 to March 2026 alone. Nearly 1 in 5 of the entire list in just 18 months. The newest entrants (WorkOS, AMI Labs, Nexthop AI, Axiom Math) all hit unicorn status in March 2026, and 4 of the top 8 by valuation are pure-play AI companies.

Outside of the consumer interest in big IPOs (and soon to be richest people in the world), the business interest for channel partnerships is seeing which categories of enterprise tech are getting the attention of serious money.

Early market success regularly results in huge channel plays downstream - just look at Anthropic's $100 million investment in partners a few weeks ago!

Today marks a historical moment in the rapid growth of AI.

AI agents crawling the web have, for the first time, surpassed humans in internet activity, according to Cloudflare.

The split is currently 57% machine to 43% human, at least as measured by HTTP requests. The gulf is certain to widen.

What are the bots doing, you ask?

Checking prices, comparing flights, ordering products, facilitating payments, reading pages, and, not unlike their web crawling forebears, scraping and indexing content. (But this time, for AI models not search engines)

Generative AI has spent years learning from the web, now agents are spending their time "doing" on the web. That translates to lots of page load requests, even if it’s not much time spent compared to humans.