It took a few months for the data-logging to begin, but I’m now in data-heaven. Here’s what one day of data looks like.

Figure 1: 24 readings daily

At first glance, this chart may not seem overly special. But, I contend that it represents a large step toward a very different world.

Consider the fact that before my smart meter, the power company could only measure my annual power consumption in twelve, monthly chunks. The new smart meter subdivided those chunks into 8,760 hourly readings, thus increasing the resolution of my power consumption picture by a factor of 730.

With the cost of sensors, processing power, wireless communications and cloud storage plummeting, we’re on the cusp of being able to measure things with unprecedented granularity.  Just as telescopes and microscopes opened access to worlds that were once invisible to the naked eye, devices like smart meters are too opening up new worlds. The finer we chop the data, the higher the resolution. The higher the resolution, the more visibility that we have.

For example, Figure 1 illustrates that my house burns 0.45 Kilowatt-hours (KWh) for each hour between 12:00 and 4:00 a.m.–a time when the Ploof household was sleeping. The only devices running at that time were a refrigerator, 60-watt porch light, clock radios, cable modem, wireless router, and other items that are in “sleep mode” (computers, DVR, etc…)

So, how much does it cost to run my house at its lowest electrical consumption level? At $0.17 per KWh, it costs 7.75 cents for every hour. Think that number is small? Try multiplying it by the 8,760 hours in a year. It costs me $657 per year just to run the house at its lowest level without anything else running!

Let’s play with this number a little more. According to the US Energy Information Administration, the average California household consumes 562KWh/month (6,744 KWh/yr.) Since my household consumed 8,168 KWh last year, let’s say that my usage is 21% higher than the average residence in my little town. Assuming that the average baseline power consumption of its 18,000 residents is 21% lower than mine, at a minimum, they consume:

• 6,399 KWh/hour
• 153,576 KWh per day
• 56,055,240 KWh/year

which costs the residents $9.529 million annually. Start multiplying that number by the residents of the state or the residents of the country, and we’re talking huge numbers. By increasing the resolution of our data, we get to see the big picture in a totally different way.

And we still haven’t even come close to hitting the highest resolutions as power readings can be subdivided even more to offer insight into how much power is being consumed by individual appliances or fixtures. Such granularity will allow us to actually measure phantom load, the estimated (we don’t yet have the granularity to measure it) amount of electrical energy that is consumed by an appliance while plugged in yet switched off. In other words, most phantom load is just wasted energy.

According to Wikipedia, phantom load is estimated to be 10% of our power consumption. Using the baseline electrical consumptions calculated earlier, phantom load (with everything off) for my little town is estimated at 5.6 million KWh/year at an annual cost of $950,000.

$950,000 paid for wasted energy. Think about what the city could do with this amount of money.

Today’s technology allows us to cost-effectively measure the total power consumption of our homes on an hourly basis. It’s only a matter of time for when new technologies enable us to cost-effectively do the same thing for everything that we plug in, thus increasing the granularity to actually measure phantom load. With the ability to measure it, we’ll be able to do something about it–like automatically disconnecting appliances from the grid when they are not needed.

Throughout history, resolution enhancing devices like telescopes, microscopes and now smart meters have lead to new discoveries that shake our fundamental assumptions and ultimately lead to innovation. They allow us to measure things as opposed to estimating them. Since most businesses are built on measurements, this increased resolution offers fertile ground for the development of new products, services and ultimately businesses.

Are you ready for this new granular age?

Two quick definitions:

1. Mediums store things
2. Networks distribute things

The Media Revolution ended on January 18th, 2012, when the worldwide poster child for physical media, Kodak, filed for bankruptcy. The end of the film-era demonstrated proof that our world had finally transitioned from one that stored its content in the form of atoms to one that now stores its content in the form of bits.

The Network Revolution, on the other hand, is just starting to heat up. With search engines connecting our digitized content semantically, Facebook and LinkedIn connecting people through our relationships, and interest-based networks like Twitter connecting us through our favorite subjects, we’ve just scratched the surface on understanding how to distribute our digital content through them effectively. And while we hone our skills in the use of semantic, relational, and interest-based networks, a new network form is emerging from the primordial ooze of innovation–one that connects people with the information that they need to make daily decisions in their personal and professional lives.

Recent advances in hardware, software, and cloud-based technologies have combined to seemingly make the impossible possible by offering ways to solve problems from the bottom-up, as opposed to the traditional top-down manner. Networks enable an unprecedented power of scale, totally inverting the concept of attaining efficiency through resource centralization. For example:

• Citizen-based networks such as Safecast.org and the soon-to-be-built #AirQualityEgg network, allow individuals and Non Government Organizations to pool their resources to create valuable information for their communities, one sensor at a time.
• As GPS technologies become more prevalent, people can share anonymized information that may benefit the collective. For example, by combining my GPS location with that provided by others, mobile applications such as Waze can provide a real-time picture of traffic congestion, ultimately helping all of the participants make better informed routing decisions.
• Or, have you ever tried to plan an event around a weather forecast such as, “There’s a 20 percent chance of rain today?” By combining your GPS location with a National Weather Service map, DarkSky can accurately predict the moment that it will start (or stop) raining in your exact location.
• Through wireless connectivity within my house (Wifi, Bluetooth, and soon-to-be ZigBee), I can connect my bathroom scale, blood pressure cuff, and refrigerator to my private network to track my svelte build (well, okay let’s not push it), systolic and diastolic measurements for my doctor, and check my refrigerator before I leave work for a list of things that I need to pick up on my way home.

The network infrastructure exists. The cost of connecting sensors to the network is plummeting. The combination of these two forces requires companies to start asking some serious questions.

• How can our ability to tap into sensor-based networks help create new products and services, fund their development, and ultimately deliver them to our customers?
• How can we harness the scaling power of networks to make our companies smarter, leaner, and much more efficient?
• How can we use the power of network technologies to reduce whatever form of waste exists in our business processes (money, resources, environmental contaminants) in order to increase the overall health of our company, finances, employees and local communities?

The Media Revolution is over. Bits have beaten atoms and our behaviors are forever changed. However, the Network Revolution is beginning to pick up steam. How will you use the creative destruction that it’s about to unleash upon the status quo?

Last Thursday, I joined a panel with four others to discuss social media. Simple, right? But things got a little odd when the panel was introduced similarly to those who spoke earlier of careers in engineering, government, finance, politics, public security, international business, education, etc….

The problem is that social media is NOT a career.

Social Media a set of communication tools that carry content, whether that content comes in the forms of text, audio, video, GPS location, etc… These powerful tools give us the ability to share our opinions about life, passions, products and services. Social media provides vehicles for us to demonstrate our expertise and talents. It gives us a way to seek the opinions of others, no matter where they live.

Social media is not something that stands alone as a career. Instead, it’s an integral part of one’s career, whether we choose engineering, government, finance, politics, public security, international business, or education.

You can’t have a career in social media, however, you can use social media in your career. The keyword is “use.” Use social media to separate yourself from other candidates in the job market. Use social media to help your company, nonprofit, or club to communicate their value to their constituencies. Use social media to interact with customers, vendors, investors, and employees.

Choose a career. Enhance it with social media.

This soon-to-be law is drawing criticism from both ends of the extreme. Some see it as the ultimate panacea of entrepreneurial opportunity. Others see it as a tool for hucksters and charlatans to separate us from our hard-earned money.

I’m willing to bet that the truth lies somewhere in the middle.

Those who see legalized crowdfunding as the answer to our economic prayers must understand that all business aren’t created equal. Some will succeed and some will fail. Investing is risky. If you’ve ever invested money before, you’ve probably lost some of it. It happens. Buyer beware.

On the other hand, those who see crowdfunding as the new “smoke-filled room where digital thieves plan to pick our pockets” need to understand the power of the networked crowd. Public offerings aimed at specific communities will be vetted by those communities. Crowdfunders for a particular project probably have intimate knowledge about the products, services, and sometimes even the players. Those vetted by a networked community will have a good chance of getting funded by it. On the other hand, any company or individual who has broken trust with that community will likely suffer its wrath.

Is H.R. 3606 perfect? Probably not. But it offers American entrepreneurs access to something that their European counterparts already have–crowdfunding sources such as CrowdCube.

The networked economy is upon us. We can choose to sit and wait for other countries to lead the way, or we can dive right in too.

Are you in?

But what if one of these Kickstarter backers wants more than just a game, a tee-shirt, or an Elevator Dock? What if they want a piece of the company or a piece of the project? Wouldn’t it be possible for someone like Tim Schafer to sell stock in his company through a service like Kickstarter?

Not in the United States.

Although crowdfunding for equity is allowed in some European countries, investor protection laws that resulted after the Crash of ‘29 preclude the practice here. But change is in the air. Legislation is working its way through Congress to allow small businesses to sell securities under lighter SEC restrictions.

Congressman Patrick McHenry (R) of North Carolina, introduced H.R. 2930, The Entrepreneur Access to Capital Act. After some debate, H.R. 2930 passed the House by a vote of 407 to 17, where it now sits in the the Senate’s Committee on Banking, Housing, and Urban Affairs.

The bill seeks exemptions in the Securities Acts of 1933 and 1934 to allow companies to raise funds by selling securities under certain restrictions:

• Company can raise $2 million per year by providing investors with audited financial statements. It can raise $1 million per year without providing those documents.

• Risk to investors is limited by restricting levels of participation to the lessor of $10 thousand or 10% of an investor’s annual income.

• Those who sell securities (whether they be the company or intermediaries) will still be subject to certain Securities and Exchange Commission filing requirements, but  neither will need to be registered “…as a broker under section 15(a)(1) of the Securities and Exchange Act of 1934 solely by reason of participation in such transaction.”

While H.R.2930 waits in the Senate, it has also been packaged with four other bills to form H.R.3606–a.k.a the Jumpstart Our Business Startups (JOBS) Act, (don’t you just love these names?) which was approved by the House, by a 390 to 23 vote. Those four other bills include:

• H.R. 2940 The Access To Capital For Job Creators Act
• H.R. 1070 The Small Company Capital Formation Act
• H.R. 2167 The Private Company Flexibility And Growth Act (Still in House)
• H.R. 4088, The Capital Expansion Act (The House version of S.1941)

And while all of the bills mentioned so far have “H.R.” in front of them, the Senate has its version too. Senator Scott Brown (R) of Massachusetts, introduced S. 1791, The Democratizing Access to Capital Act.

The largest hurdle these bills must overcome requires convincing lawmakers that investors are protected. With images of Enron and Bernie Madoff fresh in their minds, legislators will be taking a close look at the reporting exemptions from stringent reporting practices such as Sarbanes-Oxley that these bills offer small businesses.

The big questions will come down to risk. How much risk will investors be subject to? On Wednesday, March 21, 2012 the Senate’s Committee on Banking, Housing, and Urban Affairs will conduct an open hearing entitled “Examining Investor Risks in Crowdfunding” to discuss this very topic.

One of the questions that I had after reading these bills was: “And then what?” For example, H.R. 2930 restricts the selling of crowdfunded securities “…during the 1-year period beginning on the date of purchase, unless such securities are sold to–1) the issuer of such securities; or 2) an accredited investor.”

It makes for an interesting future. Let’s assume that a Crowdfunding Law is passed in 2012 and that some crowdfunded securities are sold to investors. At some time in 2013, will these securities be available to sell on the open market? If so, who will handle those sales? Will there be a new marketplace to buy such securities, like a Crowdfunding Stock Exchange?

Networked technologies have given us new ways to work together. Services like Kickstarter have given video game developers new options beyond finicky publishers. Crowdfunding for equity laws will give small businesses capital options beyond neighborhood bankers and traditional investors. If Congress can balance small business’s need for capital with an acceptable level of risk for investors, we may be entering a new era of entrepreneurialism.

What do you think?

Photo Credit: Library of Congress

Computers are better than humans at repetitive tasks, which makes them the right choice when problems need to be brute-forced through quickly. And although people can perform repetitive tasks, their forte is assessing complex situations. The differences in each process are profound. For example, if we asked a computer and a person to calculate pi to the one-millionth digit, a computer would do so in the blink of an eye, while a person would require a month of Sundays. Yet, if we asked that same computer to sort zoo photographs by species, a child would finish the task before the computer could determine the difference between an animal and a zookeeper. Computers may be able to calculate the live path of an asteroid traveling through a gravitational field with ease, but when it comes to discerning a monkey from a mongoose, they are not smarter than a 5th grader.

For some reason, billions of simple, highly-interconnected neurons are much better at pattern recognition than powerful individual microprocessors.

For many years, scientists have been trying to emulate the brain’s method for solving problems through the creation of Artificial Neural Networks (ANNs). The problem with neural networks is that they need to be “taught” through a trial and error process, much like humans are taught a new language, mathematics, or music. And although we’ve found some limited applications for ANNs, we still haven’t found a cost-effective use for them to solve many real-world problems.

But, perhaps we’ve been looking at the problem the wrong way. What if, instead of building application-specific computers based on the type of problem to solve, we created a hybrid system that used the best attributes of human and machine computation?

Hybrid Human-Machine Computing

Professor Luis von Ahn’s mission is to “…build systems that combine humans and computers to solve large-scale problems that neither can solve alone.” If you don’t recognize von Ahn’s name, you probably recognize his work–he helped developed CAPTCHA, the web-based challenge system that allows websites to determine the difference between machines and humans. CAPTCHA, which stands for Completely Automated Public Turing test to tell Computers and Humans Apart, is built on the fundamental principle that human brains are better at pattern recognition than computers. Since people have better abilities to identify highly distorted letters than computers, CAPTCHA provides website owners and their customers a level of security with respect to web-based transactions. According to von Ahn, the CAPTCHA verification process happens about 200 million times per day [1]–a number that got him thinking differently about another problem that he was working on–the accurate digitization of books.

Companies such as Google and Amazon have large scale projects to digitize books. The process involves scanning physical books and converting the captured images to text through optical character recognition (OCR) software. And while OCR technology is effective at translating clear and perfectly aligned images, it makes many mistakes while translating less-than-perfect ones.

But that’s when professor von Ahn got an idea. If he could find a way to tap into the collective intelligence manifested within 200 million transactions per day, would it be possible to extract additional value from each transaction, such as helping computers with difficult OCR problems? He did so by retooling CAPTCHA to offer two words instead of one. One would be used to pass the security test while the other would help a stumped computer.

“Whenever you type the distorted characters,” Professor von Ahn explains reCAPTCHA, “not only are you authenticating yourself as a human, but in addition, you’re helping us to digitize books…With this method, we are digitizing approximately 100 million words a day, which is the equivalent of two-million books per year.”[2]

Let’s put 100 million words per day into a business perspective:

• 100 million transactions at 10 seconds per translation represents about 277,778 person-hours per day.
• 277,778 person-hours at 8-hours per workday forms an equivalent “project team” of about 34,722 people, which is slightly larger than Google’s workforce.
• If project team members were paid at the federal minimum wage of $7.25 per hour, its daily payroll would cost $251,736.

But there’s more to these numbers. Even if it were economically feasible to hire 34,000 full-time employees who did nothing but translate obscure images into text, that team could never approach the efficiency of 100 million people performing the task once per day. Normal human limitations, such as fatigue or boredom, would surely slow them down.

Companies Must Think Differently

Not too long ago, the ability to access 10 seconds of 100 million people’s time to perform a menial task would have been cost-prohibitive. Today, it’s free. CAPTCHA and reCAPTCHA are examples of how hybrid networks drive down transaction costs associated with distributed labor, and companies must think about how these technologies will affect their businesses.

Many companies talk about the power of networked computers. They use fancy terms such as cloud computing, the Internet of Things, and machine-to-machine (M2M) communications. And while only a few of them are thinking past obvious uses, only a handful are pushing the boundaries of possibility, such as professor von Ahn, who is now wondering how to “…get 100 million people to help us translate the whole web into every major language, for free?”[4]

Professor von Ahn’s newest project, Duolingo, offers the following value proposition to the 1.2 billion people who want to learn another language:

If you’ll help us translate web pages, we’ll help you learn a new language for free.

Duolingo is presently in beta testing, but is already showing positive results. “The translations that we get from people are as accurate as those from professional language translators,”[5] von Ahn said, offering good news for society, yet not-so-good news for professional translators.

Hybrid computer human networks offer lessons for any CEO. They may identify untapped resources that hold the keys to unlocking the same problems that the company has been stuck on for years.

It’s time to think past the obvious. It’s time to think hybrid.

• Companies are pretty good at predicting costs
• and they’re not very good at predicting demand.

If they were, companies like Ford, Coca-Cola and Columbia Pictures never would have released the Edsel, New Coke, or Ishtar.

The problem is that until recently, the financial success of a project was determined posteriori (after the fact), by how much revenue was generated. But wouldn’t it be better if we could actually predict the project’s financial success a priori (before the fact?) Recent advances in “social” technologies have resulted in a new sort of crystal ball that can not only predict marketplace viability accurately, but can also establish the holy grail of marketing: value-based pricing.

A New Way

Imagine for a moment that you have an idea for a great new product. You know how much that product will cost to develop and manufacture, but don’t yet have a good feeling on how well the marketplace will respond to it. Sound familiar? So how do you determine whether or not to continue with the project? Product testing? Focus groups? Surveys? And even after performing all of these expensive pseudo-scientific actions, doesn’t the decision still come down to a gut-feel based on “intangibles?”

But, what if, instead of surveys or gut-feelings, we had a way to know exactly how many people would prepay for your product? And what if, those same customers would also determine an average selling price (ASP) for the product too?

Fantasy? Nope. Just another business innovation that is resulting from our experimentation with social technologies.

Musician Julia Nunes explains.

“Normally I’d record the album and incur a fun amount of debt, and then, I would try to make that money back by selling the album,” she says in her Kickstarter project video where she’s requesting $15,000 to fund her project. “But now we have this awesome platform called Kickstarter, and I can basically pre-sell the album, and offer up a bunch of stuff that I’d never sell on my regular website, with the added bonus of you guys knowing exactly where your money is going…directly into the studio.”

Had Julia decided to follow the traditional business decision cycle, she’d have to consider investing $15,000 of her own (or borrowed) money to record, manufacture, market, and distribute her album. If she assumed an ASP for each album at $9.99 on iTunes, she’d need to sell well over 1,500 of them (to also cover sales costs) just to break even. If that number passed her gut-check, she’d probably green-light the project.

However Kickstarter opened a new way for Julia to assess the financial viability of her project. Having already calculated the $15,000 that would make the project worth her while, she didn’t have to wait to determine the financial success of her project posteriori, instead the marketplace determined that for her a priori, as 1,685 people prepaid $77,888 for her to create her album.

Business Ramifications

Many people look at Kickstarter as a cute way for the little guy to make it. And they’re missing the point. Something much bigger is happening here as networked technologies are squeezing inefficiencies out of traditional business decision-making processes. The concept of network funding has applicability in any business, not just musicians, as indicated by the 5,258 people who gave $364,000 to Peter Dering to manufacture his Camera Clip System, or the 12,521 folks who gave $1.464M to Casey Hopkins to manufacture his Elevation Dock: The Best Dock for the iPhone.

The business ramifications of network-based funding run even deeper. Consider the fact that companies are never quite certain that they’ve optimized the price-to-demand ratio to generate the most revenue. Companies spend many hours trying to determine pricing, constantly “guesstimating” the consequences of setting prices high to establish a perceived value, or “diving the boat” to drive revenue through volume. Either way, the uncertainty frequently leaves companies with a nagging suspicion that they’ve left money on the table.

Yet, Julia Nunes established a value-based selling price for her album a priori to recording its first note. The ASP for her album was $46.22 [($77,888/1,685), with a median of $30 (determined by the breakdown of backers provided by Kickstarter]. Without a service like Kickstarter, had Julia gone to a record publisher and said, “I can sell exactly 1,685 albums at an ASP of $46.22,” she would have been laughed out of the building, because even the best A&R person in the world can’t predict sales with that level of accuracy. However, Julia’s prediction wasn’t based on the squishiness of a gut-feel; it was based on fact.

So, what does this mean for your business?

The more we use our social networks, the more we learn about their value. As we learn, new uses will emerge, such as helping businesses assess risk in a way that was impossible to do just a few years ago. Services like Kickstarter offer producers the ability to see exactly what consumers are willing to commit to their credit cards before getting too deep into the product development cycle.

So, I have a question. Is your company actively considering the power of networks in their business, or has it already dismissed them as minor tools to be placed into the hands of corporate communicators?

Note: If you’d like to read the full story behind Julia Nune’s successful use of social media technologies, please feel free to get your free copy of The Rule of Thumbs.

I went online to learn that the building that I saw represented their new corporate headquarters. I learned that they were growing, having acquired twelve additional semiconductor companies over the past three years–who each brought some pretty cool technologies with them. After a few more mouse-clicks, I also noticed that the company had a very small social media presence. Thinking that this might be Kismet (like how many analog/mixed signal companies with cool new technologies yet very little social media presence can I expect to move into the area?), I decided to write a report, on spec, complete with specific recommendations on how the company might use its online properties to better communicate with its customers–electrical engineers.

I wrote the report and snail-mailed a hardcopy to a Microsemi contact with whom I’d been introduced through a mutual colleague. Unfortunately, it wasn’t meant to be. No complaints. Such are the risks of spec research.

However, as I shared the report with a few friends, it occurred to me that independent of the subject-company’s name on the report, the document contained relevant information for any high-tech, B2B company who is considering the use of online publishing platforms. So, rather than having this report remain lost forever on my hard-drive, I decided to share it with my readers.

If you work for a B2B company in a high-tech industry, you should read this report: Microsemi Corporation: Online Properties Analysis and Recommendations. Perhaps it’ll help provide a new perspective by which to evaluate your own online properties.

Historically, technology leaps that force us to rethink our world leave us temporarily overwhelmed and lost. Without something familiar to hold onto, we end-up acting like artists who are standing in front of large empty canvases, trying to figure out what to do with our infinite palate of colors.

The way to beak such creative logjams is to focus on solving specific problems. Why must we rely on the government to monitor the radiation from a nuclear power plant? What exactly is the water quality in my home town? If we could put accelerometers into every high school football helmet or mouthpiece, could we reduce the number of concussion injuries? The new innovators must focus on solving specific problems that have personal meaning to them.

2012 is shaping up to be the year of the engineer. I’m not just talking just about classically trained engineers who hold engineering degrees. I’m talking about the fact that advances in open source hardware, interchangeable modules, the Internet of Things, and the DIY movement are making engineers out of all of us.

We just need to focus on solving problems that are more important to us than to a company who is looking to solve a problem for the generic marketplace. Why does our street seem to get more potholes than those around it? Does our city have a traffic problem that could be solved by aggregating and studying live congestion data? Are there things at home or work that would better served through automation?

We also need to crank the innovation handle backward by examining the possibilities of the absurd. What if we put a sensor in every blade of grass on a baseball field? What if you could put a microprocessor in your favorite sweater? What if our local high school could launch its own satellite?

The future is either ours to invent, or ours to stare at aimlessly.

What’s it going to be?

Before World War II, most innovation came from the toils of sole inventors with well-known names such as Davinci, Copernicus, Curie, Bell, Edison, Bohr, Maxwell, Newton, Einstein, Faraday and many more. However, the role of the individual innovator changed during WWII, when a need to increase the pace of innovation outstripped the individual’s production capabilities.

The United States responded to the challenge by forming the National Defense Research Committee (NDRC) “…to coordinate, supervise, and conduct scientific research on the problems underlying the development, production, and use of mechanisms and devices of warfare.” As a result of the NDRC and other organizations like it, the roots of innovation shifted from the individual inventor to the process of Organized Research and Development (OR&D).

Leading and Trailing Technologies

Organized Research and Development is expensive. It produces leading technologies that require even more resources to commercialize. But with the pace of innovation accelerating, leading technologies don’t hold that spot very long. As new technologies are invented, once-leading technologies eventually become trailing technologies–innovations that may lack their original luster, yet fill a new role. Trailing technologies meet the affordability and functionality requirements of individual inventors.

Many examples of the leading-to-trailing technology exchange show how the innovation cycle has been affected. For example, when transistors replaced vacuum tubes, individual innovators built circuits out of cheap tubes. When integrated circuits (ICs) replaced transistors, individual inventors started building things with transistors. And as Moore’s Law compounded the advances in integrated circuits, trailing IC technologies were scooped up by individual inventors such as Steve Wozniak to build things like personal computers.

For the past sixty years, the differences between leading and trailing technologies were large enough to limit the effectiveness of individual inventors. Not anymore. With trailing technology microprocessors powerful enough to perform real-time processing, standardized protocols that allow ubiquitous communications, cloud-based storage and processing services that offer scale, and access to pools of other inventors via social networks, the individual innovator is making a comeback. The day has come where millions of individual innovators now have the capacity to solve problems more efficiently than their deep-pocketed OR&D counterparts.

So, what are they going to invent? My next post will cover the things that these new innovators must do to take advantage of their new-found bounty.

Portrait of Alexander Graham Bell: Courtesy Smithsonian on Flickr