‘Field Of Dreams’

Ivanpah Solar Plant

Ivanpah Solar Electric Generation Plant  photo/Brightsource

What has 300,000 garage door-size mirrors, 40 story towers, costs 2.2 billion dollars, powers 140,000 homes, uproots tortoises from their homes, and ignites one bird every two minutes (labelled “streamers” by wildlife experts)…?

Ivanpah Solar is jointly-owned by Brightsource, NRG, and Google. Their belief in clean energy is proving to be as quixotic as the belief in clean data and secure browsers. Where Wind Power has been found to ravage ecosystems and kill endangered species on the ground and in the air, Solar uproots desert wildlife and ignites birds inflight. And while Solar advances toward the levelized cost of natural gas the natural gas pipeline industry has a generational lead managing ecosystem effects.

Every field of dreams generates its own set of nightmares but where dreams meet money, well…you just never know.

Ivanpah Solar Farms


Body Heat

Today there are 7 billion distributed energy generators roaming the planet…

David Carroll - Wake Forest

David Carroll …photo/Wake Forest

You can generate enough power from your body heat to power your cell phone. It turns out your campfire, car dashboard, even your body generates enough heat to recharge electronic devices. All you need is a way to capture the heat and convert it to watts. Power Felt, invented by David Carroll at Wake Forest does exactly that.

For those of us who’ve long been involved in distributed energy architectures, converting body heat into watts is the archetype. You may not be able to heat your home or power your car with your own body heat but for 7 billion people to power their mobile devices for the one-time cost of a piece of clothing is transformational and disruptive on a planetary scale. Carroll sees sensors embedded in Power Felt providing advance warnings of heart-failure. Let your imagination run.

With the IT world gearing-up for Big Data, Big Computing, and high-powered datacenters, the most disruptive technologies may turn out to be Small Data and low-powered sensors distributed across a sea of humanity.

power felt

Power Felt …photo/Wake Forest

Listen To Your Heart

listen to your heart

Photoplethysmography  photo/MIT TR

While Big Data gets all the attention, startups like Valencell fit optical emitters, photodetectors, and accelerometers into earbuds and get big value from small data in small places. It turns out that listening to your vital signs is the best way to monitor signals from your body. Before wrist-tech even gets established it’s being disrupted by ear-tech.

As the pace of information technology advances at an increasing rate, planning for and responding to disruption may turn out to be THE art of business management.

cf: MIT Technology Review

Call Me In The Morning

Pick one, will he or she have cardiac surgery…?

Cardiac Arrest

“Cardiac Arrest” photo/nick

Ask a hundred cardiologists, they’ll split right down the middle. Wait two years, 40 will change their minds. This bizarre drama repeats itself in varying degrees over a host of diseases: prostate cancer, dengue fever, even the common cold. Big Data will bring more accurate diagnostics to healthcare but first, it’s showing the most sage advice a human doctor can give today is still,  “Call me in the morning.”

Click HERE to see what IBM is doing about it using lessons it learned on Jeopardy.

There’s A 34% Chance I’m Not Human


“Tolerance” on Allen Parkway – Houston …photo/nick

What if your social IQ as measured by followers, re-posts, and retweets is bogus? “Social Bots” are non-human poseurs that follow, tweet, retweet, and siphon social bitstreams to game the ad-revenue system. In a stroke of Promethean irony celebrities and politicians now find a large percentage of their followers to be fake people.

Young researchers at Texas A&M and Indiana University have been working for years to detect fingerprints of social bots. Partially supported by DARPA, they recently posted a Web service called Bot, or Not (HERE) where you can enter any Twitter id to determine the likelihood it’s a Social Bot. Full disclosure…there’s a 34% chance that I’m not human.

For an interesting exposé see “How to Spot a Social Bot on Twitter.”