The History of Computing

Carlota Perez is a researcher who has studied hype cycles for much of her career. She’s affiliated with the University College London, the University of Sussex, The Tallinn University of Technology in Astonia and has worked with some influential organizations around technology and innovation. As a neo-Schumpeterian, she sees technology as a cornerstone of innovation. Her book Technological Revolutions and Financial Capital is a must-read for anyone who works in an industry that includes any of those four words, including revolutionaries. 

Connecticut-based Gartner Research was founded by GideonGartner in 1979. He emigrated to the United States from Tel Aviv at three years old in 1938 and graduated in the 1956 class from MIT, where he got his Master’s at the Sloan School of Management. He went on to work at the software company System Development Corporation (SDC), the US military defense industry, and IBM over the next 13 years before starting his first company. After that failed, he moved into analysis work and quickly became known as a top mind in the technology industry analysts. He often bucked the trends to pick winners and made banks, funds, and investors lots of money. He was able to parlay that into founding the Gartner Group in 1979. 

Gartner hired senior people in different industry segments to aid in competitive intelligence, industry research, and of course, to help Wall Street. They wrote reports on industries, dove deeply into new technologies, and got to understand what we now call hype cycles in the ensuing decades. They now boast a few billion dollars in revenue per year and serve well over 10,000 customers in more than 100 countries. 

Gartner has developed a number of tools to make it easier to take in the types of analysis they create. One is a Magic Quadrant, reports that identify leaders in categories of companies by a vision (or a completeness of vision to be more specific) and the ability to execute, which includes things like go-to-market activities, support, etc. They lump companies into a standard four-box as Leaders, Challengers, Visionaries, and Niche Players. There’s certainly an observer effect and those they put in the top right of their four box often enjoy added growth as companies want to be with the most visionary and best when picking a tool.

Another of Gartner’s graphical design patterns to display technology advances is what they call the “hype cycle”. The hype cycle simplifies research from career academics like Perez into five phases. 

* The first is the technology trigger, which is when a breakthrough is found and PoCs, or proof-of-concepts begin to emerge in the world that get press interested in the new technology. Sometimes the new technology isn’t even usable, but shows promise.  * The second is the Peak of Inflated Expectations, when the press picks up the story and companies are born, capital invested, and a large number of projects around the new techology fail. * The third is the Trough of Disillusionment, where interest falls off after those failures. Some companies suceeded and can show real productivity, and they continue to get investment. * The fourth is the Slope of Enlightenment, where the go-to-market activities of the surviving companies (or even a new generation) begin to have real productivity gains. Every company or IT department now runs a pilot and expectations are lower, but now achievable. * The fifth is the Plateau of Productivity, when those pilots become deployments and purchase orders. The mainstream industries embrace the new technology and case studies prove the promised productivity increases. Provided there’s enough market, companies now find success.

There are issues with the hype cycle. Not all technologies will follow the cycle. The Gartner approach focuses on financials and productivity rather than true adoption. It involves a lot of guesswork around subjective, synthetical, and often unsystematic research. There’s also the ever-resent observer effect. However, more often than not, the hype is seperated from the tech that can give organizations (and sometimes all of humanity) real productivity gains. Further, the term cycle denotes a series of events when it should in fact be cyclical as out of the end of the fifth phase a new cycle is born, or even a set of cycles if industries grow enough to diverge.

ChatGPT is all over the news feeds these days, igniting yet another cycle in the cycles of AI hype that have been prevalent since the 1950s. The concept of computer intelligence dates back to the 1942 with Alan Turing and Isaac Asimov with “Runaround” where the three laws of robotics initially emerged from. By 1952 computers could play themselves in checkers and by 1955, Arthur Samuel had written a heuristic learning algorthm he called “temporal-difference learning” to play Chess. Academics around the world worked on similar projects and by 1956 John McCarthy introduced the term “artificial intelligence” when he gathered some of the top minds in the field together for the McCarthy workshop. They tinkered and a generation of researchers began to join them. By 1964, Joseph Weizenbaum’s "ELIZA" debuted. ELIZA was a computer program that used early forms of natural language processing to run what they called a “DOCTOR” script that acted as a psychotherapist. 

ELIZA was one of a few technologies that triggered the media to pick up AI in the second stage of the hype cycle. Others came into the industry and expectations soared, now predictably followed by dilsillusionment. Weizenbaum wrote a book called Computer Power and Human Reason: From Judgment to Calculation in 1976, in response to the critiques and some of the early successes were able to then go to wider markets as the fourth phase of the hype cycle began. ELIZA was seen by people who worked on similar software, including some games, for Apple, Atari, and Commodore. 

Still, in the aftermath of ELIZA, the machine translation movement in AI had failed in the eyes of those who funded the attempts because going further required more than some fancy case statements. Another similar movement called connectionism, or mostly node-based artificial neural networks is widely seen as the impetus to deep learning. David Hunter Hubel and Torsten Nils Wiesel focused on the idea of convultional neural networks in human vision, which culminated in a 1968 paper called  "Receptive fields and functional architecture of monkey striate cortex.” That built on the original deep learning paper from Frank Rosenblatt of Cornell University called "Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms" in 1962 and work done behind the iron curtain by Alexey Ivakhnenko on learning algorithms in 1967. After early successes, though, connectionism - which when paired with machine learning would be called deep learning when Rina Dechter coined the term in 1986, went through a similar trough of disillusionment that kicked off in 1970.

Funding for these projects shot up after the early successes and petered out ofter there wasn’t much to show for them. Some had so much promise that former presidents can be seen in old photographs going through the models with the statiticians who were moving into computing. But organizations like DARPA would pull back funding, as seen with their speech recognition projects with Cargegie Mellon University in the early 1970s. 

These hype cycles weren’t just seen in the United States. The British applied mathemetician James Lighthill wrote a report for the British Science Research Council, which was published in 1973. The paper was called “Artificial Intelligence: A General Survey” and analyzed the progress made based on the amount of money spent on artificial intelligence programs. He found none of the research had resulted in any “major impact” in fields that the academics had undertaken. Much of the work had been done at the University of Edinbourgh and funding was drastically cut, based on his findings, for AI research around the UK. Turing, Von Neumann, McCarthy, and others had either intentially or not, set an expectation that became a check the academic research community just couldn’t cash. For example, the New York Times claimed Rosenblatt’s perceptron would let the US Navy build computers that could “walk, talk, see, write, reproduce itself, and be conscious of its existence” in the 1950s - a goal not likely to be achieved in the near future even seventy years later.

Funding was cut in the US, the UK, and even in the USSR, or Union of the Soviet Socialist Republic. Yet many persisted. Languages like Lisp had become common in the late 1970s, after engineers like Richard Greenblatt helped to make McCarthy’s ideas for computer languages a reality. The MIT AI Lab developed a Lisp Machine Project and as AI work was picked up at other schools like Stanford began to look for ways to buy commercially built computers ideal to be Lisp Machines. After the post-war spending, the idea that AI could become a more commercial endeavor was attractive to many. But after plenty of hype, the Lisp machine market never materialized. The next hype cycle had begun in 1983 when the US Department of Defense pumped a billion dollars into AI, but that spending was cancelled in 1987, just after the collapse of the Lisp machine market. Another AI winter was about to begin.

Another trend that began in the 1950s but picked up steam in the 1980s was expert systems. These attempt to emulate the ways that humans make decisions. Some of this work came out of the Stanford Heuristic Programming Project, pioneered by Edward Feigenbaum. Some commercial companies took the mantle and after running into barriers with CPUs, by the 1980s those got fast enough. There were inflated expectations after great papers like Richard Karp’s “Reducibility among Combinatorial Problems” out of UC Berkeley in 1972. Countries like Japan dumped hundreds of millions of dollars (or yen) into projects like “Fifth Generation Computer Systems” in 1982, a 10 year project to build up massively parallel computing systems. IBM spent around the same amount on their own projects. However, while these types of projects helped to improve computing, they didn’t live up to the expectations and by the early 1990s funding was cut following commercial failures.

By the mid-2000s, some of the researchers in AI began to use new terms, after generations of artificial intelligence projects led to subsequent AI winters. Yet research continued on, with varying degrees of funding. Organizations like DARPA began to use challenges rather than funding large projects in some cases. Over time, successes were found yet again. Google Translate, Google Image Search, IBM’s Watson, AWS options for AI/ML, home voice assistants, and various machine learning projects in the open source world led to the start of yet another AI spring in the early 2010s. New chips have built-in machine learning cores and programming languages have frameworks and new technologies like Jupyter notebooks to help organize and train data sets.

By 2006, academic works and open source projects had hit a turning point, this time quietly. The Association of Computer Linguistics was founded in 1962, initially as the Association for Machine Translation and Computational Linguistics (AMTCL). As with the ACM, they have a number of special interest groups that include natural language learning, machine translation, typology, natural language generation, and the list goes on. The 2006 proceedings on the Workshop of Statistical Machine Translation began a series of dozens of workshops attended by hundreds of papers and presenters. The academic work was then able to be consumed by all, inlcuding contributions to achieve English-to-German and Frnech tasks from 2014. Deep learning models spread and become more accessible - democratic if you will. RNNs, CNNs, DNNs, GANs. 

Training data sets was still one of the most human intensive and slow aspects of machine learning. GANs, or Generative Adversarial Networks were one of those machine learning frameworks, initially designed by Ian Goodfellow and others in 2014. GANs use zero-sum game techniques from game theory to generate new data sets - a genrative model. This allowed for more unsupervised training of data. Now it was possible to get further, faster with AI. 

This brings us into the current hype cycle. ChatGPT was launched in November of 2022 by OpenAI. OpenAI was founded as a non-profit in 2015 by Sam Altman (former cofounder of location-based social network app Loopt and former president of Y Combinator) and a cast of veritable all-stars in the startup world that included: 

* Reid Hoffman, former Paypal COO, LinkedIn founder and venture capitalist. * Peter Thiel, former cofounder of Paypal and Palantir, as well as one of the top investors in Silicon Valley. * Jessica Livingston, founding partner at Y Combinator. * Greg Brockman, an AI researcher who had worked on projects at MIT and Harvard

OpenAI spent the next few years as a non-profit and worked on GPT, or Generative Pre-trained Transformer autoregression models. GPT uses deep learning models to process human text and produce text that’s more human than previous models. Not only is it capable of natural language processing but the generative pre-training of models has allowed it to take a lot of unlabeled text so people don’t have to hand label weights, thus automated fine tuning of results. OpenAI dumped millions into public betas by 2016 and were ready to build products to take to market by 2019. That’s when they switched from a non-profit to a for-profit. Microsoft pumped $1 billion into the company and they released DALL-E to produce generative images, which helped lead to a new generation of applications that could produce artwork on the fly. Then they released ChatGPT towards the end of 2022, which led to more media coverage and prognostication of world-changing technological breakthrough than most other hype cycles for any industry in recent memory. This, with GPT-4 to be released later in 2023.

ChatGPT is most interesting through the lens of the hype cycle. There have been plenty of peaks and plateaus and valleys in artificial intelligence over the last 7+ decades. Most have been hyped up in the hallowed halls of academia and defense research. ChatGPT has hit mainstream media. The AI winter following each seems to be based on the reach of audience and depth of expectations. Science fiction continues to conflate expectations. Early prototypes that make it seem as though science fiction will be in our hands in a matter of weeks lead media to conjecture. The reckoning could be substantial. Meanwhile, projects like TinyML - with smaller potential impacts for each use but wider use cases, could become the real benefit to humanity beyond research, when it comes to everyday productivity gains.

The moral of this story is as old as time. Control expectations. Undersell and overdeliver. That doesn’t lead to massive valuations pumped up by hype cycles. Many CEOs and CFOs know that a jump in profits doesn’t always mean the increase will continue. Some intentially slow expectations in their quarterly reports and calls with analysts. Those are the smart ones.

Research into the history of computers sometimes leads down some interesting alleys - or wormholes even. My family would always go out to eat Chinese food, or pick it up, on New Year’s day. None of the one Chinese restaurants in the area actually closed, so it just made sense. The Christmas leftovers were gone by then and no one really wanted to cook. My dad mentioned there were no Chinese restaurants in our area in the 1970s - so it was a relatively new entrant to the cuisine of my North Georgia town.

Whether it’s the Tech Model Railroad or hobbyists from Cambridge, stories abound of young engineers debating the merits of this programming technique or chipset or that. So much so that while reading Steven Levy’s Hackers or Tom Lean’s Electronic Dreams, I couldn’t help but hop on Door Dash and order up some yummy fried rice. Then I started to wonder, why this obsession? 

For one, many of these hackers didn’t have a ton of money. Chinese food was quick and cheap. The restaurants were often family-owned and small. There were higher end restaurants but concepts like P.F. Chang’s hadn’t sprung up yet. That wouldn’t come until 1993. Another reason it was cheap is that many of the proprietors of the restaurants were recent immigrants. Some were from Hunan, others from Taipei or Sichuan, Shanghai, or Peking (the Romanized name for Beijing). Chinese immigrants began to flow into the United States during the Gold Rush of California in the late 1840s and early 1850s. 

The Qing Empire had been at its height at the end of the 1700s and China ruled over a third of humans in the world. Not only that - it was one of the top economies in the world. But rapid growth in population meant less farmland for everyone - less jobs to go around. Poverty spread, just as colonial powers began to pick away at parts of the empire. Britain had banned the slave trade in 1807 and Chinese laborers had been used to replace the slaves. The use of opium spread throughout the colonies and with the laborers, back into China. The Chinese tried to ban the opium trade and seized opium in Canton. The British had better ships, better guns, and when the First Opium War broke out, China was forced to give up Hong Kong to the British in 1842, which began what some historians refer to as a century of humiliation while China gave up land until they were able to modernize. Hong Kong became a British colony under Queen Victoria and the Victorian obsession with China grew. Art, silks (as with the Romans), vases, and anything the British could get their hands on flowed through Hong Kong.

Then came the Taiping Rebellion, which lasted from 1851 to 1864. A Christian was named theocrat and China was forced to wage a war internally with around 20 million people dying and scores more being displaced. The scent of an empire in decay was in the air. Set against a backdrop of more rebellions, the Chinese army was weakened to the point that during the First Sino-Japanese War in 1894, and more intervention from colonial powers. By 1900, the anti-colonial and anti-Christian Boxer Uprising saw missionaries slaughtered and foreigners expelled. Great powers of the day sent ships and troops to retrieve their peoples and soon declared war on the empire and seized Beijing. This was all expensive, led to reparations, a prohibition on importing arms, razing of forts, and more foreign powers occupying areas of China. The United States put over $10 million of its take from the Boxer Indemnity as they called it, to help support Chinese students who came to the United States.

The Qing court had lost control and by 1911 the Wuchang Uprising began and by 1912 2,000 years of Chinese dynasties was over with the Republic of China founded in 1912, and internal conflicts for power continuing until Mao Zedong and his followers finally seized power, established the People’s Republic of China as a communist nation, and cleansed the country of detractors during what they called the Great Leap Forward, resulting in 45 million dead. China itself was diplomatically disconnected with the United States at the time, who had backed the government now in exile in the capital city of Taiwan, Taipei - or the Republic of China as they were called during the Civil War. 

The food, though. Chinese food began to come into the United States during the Gold Rush. Cantonese merchants flowed into the sparkling bay of San Francisco, and emigrants could find jobs mining, laying railroad tracks, and in agriculture. Hard work means you get real hungry, and they cooked food like they had at home. China had a better restaurant and open market cooking industry than the US at the time (and arguably still does). Some of he Chinese who settled in San Francisco started restaurants - many better than those run by Americans. The first known restaurant owned by a Chinese proprietor was Canton Restaurant in 1849. As San Francisco grew, so grew the Chinese food industry. 

Every group of immigrants faces xenophobia or racism. The use of the Chinese laborers had led to laws in England that attempted to limit their use. In some cases they were subjugated into labor. The Chinese immigrants came into the California Gold Rush and many stayed. More restaurants were opened and some catered to white people more than the Chinese. The Transcontinental Railroad was completed in 1869 and tourists began to visit San Francisco from the east. China Towns began to spring up in other major cities across the United States. Restaurants, laundries, and other even eastern pharmacies. New people bring new ways and economies go up and down. Prejudice reared its ugly head. There was an economic recession in the 1870s. There were fears that the Chinese were taking jobs, causing wages to go down, and crime. Anti-Chinese sentiment became law in the Chinese Exclusion Act in 1882, which halted immigration into the US. That would be repealed in 1943.

Conservative approaches to immigration did nothing to limit the growing appeal of Chinese food in the United States. Merchants, like those who owned Chinese restaurants, could get special visas. They could bring relatives and workers. Early Chinese restaurants had been called “chow chow houses” and by the early 1900s there were new Chop Suey restaurants in big cities, that were affordable. Chop Suey basically means “odds and ends” and most of the dishes were heavily westernized but still interesting and delicious. The food was fried in ways it hadn’t been in China, and sweeter. Ideas from other asian nations also began to come in, like fortune cookies, initially from Japan.

Americans began to return home from World War II in the late 1940s. Many had experienced new culinary traditions in lands they visited. Initially Cantonese-inspired, more people flowed in from other parts of China like Taiwan and they brought food inspired from their native lands. Areas like New York and San Francisco got higher end restaurants. Once the Chinese Exclusion Act was repealed, plenty of immigrants fled wars and cleansing in China. Meanwhile, Americans embraced access to different types of foods - like Italian, Chinese, and fast food. Food became a part of the national identity. Further, new ways to preserve food became possible as people got freezers and canneries helped spread foods - like pasta sauce. 

This was the era of the spread of Spam and other types of early processed foods. The military helped spread the practice - as did Jen Paulucci, who bought Chun King Corporation in 1947. The Great Depression proved there needed to be new ways to distribute foods. Some capitalized on that. 4,000+ Chinese restaurants in the US in the 1940s meant there were plenty of companies to buy those goods rather than make them fresh. Chop Suey, possibly created by the early Chinese migrants. A new influx of immigrants would have new opportunities to diversify the American pallate. 

The 1960s saw an increase in legislation to protect human rights. Amidst the civil rights movement, the Hart-Celler Act of 1965 stopped the long-standing practice of controlling immigration effectively by color. The post-war years saw shifting borders and wars throughout the world - especially in Eastern Europe and Asia. The Marshal Plan helped rebuild the parts of Asia that weren’t communist, and opened the ability for more diverse people to move to the US. Many that we’ve covered went into computing and helped develop a number of aspects of computing. They didn’t just come from China - they came from Russia, Poland, India, Japan, Korea, Vietnam, Thailand, and throughout. Their food came with them. This is the world the Hackers that Steven Levy described lived in. The first Chinese restaurant opened in London in 1907 and as well when people who lived in Hong Kong moved to the UK, especially after World War II.

That number of Chinese restaurants in the US grew to tens of thousands in the decades since Richard Nixon visited Beijing in 1972 to open relations back up with China. But the impact at the time was substantial, even on technologists. It wasn’t just those hackers from MIT that loved their Chinese food, but those in Cambridge as well in the 1980s, who partook in a more Americanized Chinese cuisine, like “Chow mein” - which loosely translates from “fried noodles” and emerged in the US in the early 1900s. 

Not all dishes have such simple origins to track down. Egg rolls emerged in the 1930s, a twist on the more traditional Chinese sprint roll. Ding Baozhen, a governor of the Sichuan province in the Qing Dynasty, discovered a spicy marinated chicken dish in the mid-1800s that spread quickly. He was the Palace Guardian, or Kung Pao, as the dish is still known. Zuo Zongtang, better known as General Tso, was a Qing Dynasty statesman and military commander who helped put down the Taiping Rebellion in the later half of the 1800s. Chef Peng Chang-kuei escaped communist China to Taiwan, where he developed General Tso’s chicken and named it after the war hero. It came to New York in the 1970s. Sweet and Sour pork also got its start in the Qing era, in 18th century Cantonese cuisine and spread to the US with the Gold Rush.

Some dishes are far older. Steamed dumplings were popular from Afghanistan to Japan and go back to the Han Dynasty - possibly invented by the Chinese doctor Zhang Zhongjing in the centuries before or after the turn of the millennia. Peking duck is far older, getting its start in 1300s Ming Dynasty, or Yuan - but close to Shanghai. Otto Reichardt brought the ducks to San Francisco to be served in restaurants in 1901. Chinese diplomats helped popularize the dish in the 1940s as some of their staffs stayed in the US and the dish exploded in popularity in the 1970s - especially after Nixon’s trip to China, which included a televised meal on Tiananmen Square where he and Henry Kissinger ate the dish.  

There are countless stories of Chinese-born immigrants bringing their food to the world. Some are emblematic of larger population shifts globally. Cecilia Chiang grew up in Shanghai until Japan invaded, when she and her sister fled to Chengdu, only to flee the Chinese Communists and emigrate to the US in 1959. She opened The Mandarin in 1960 in San Francisco and a second location in 1967. It was an upscale restaurant and introduced a number of new dishes to the US from China. She went on to serve everyone from John Lennon to Julia Child - and her son Philip replaced her in 1989 before starting a more mainstream chain of restaurants he called P.F. Chang’s in 1993. The American dream, as it had come to be known. Plenty of other immigrants from countries around the world were met with open arms. Chemists, biologists, inventors, spies, mathematicians, doctors, physicists, and yes, computer scientists. And of course, chefs. Diversity of thought, diversity of ideas, and diversity-driven innovation can only come from diverse peoples. The hackers innovated over their Americanized versions of Chinese food - many making use of technology developed by immigrants from China, their children, or those who came from other nations. Just as those from nearly every industry did.

The Silk Road, or roads more appropriately, has been in use for thousands of years. Horses, jade, gold, and of course silk flowed across the trade routes. As did spices - and knowledge. The term Silk Road was coined by a German geographer named Ferdinand van Richthofen in 1870 to describe a network of routes that was somewhat formalized in the second century that some theorize date back 3000 years, given that silk has been found on Egyptian mummies from that time - or further. The use of silk itself in China in fact dates back perhaps 8,500 years.

Chinese silk has been found in Scythian graves, ancient Germanic graves, and along mountain ranges and waterways around modern India gold and silk flowed between east and west. These gave way to empires along the Carpathian Mountains or Kansu Corridor. There were Assyrian outposts in modern Iran and the Sogdia built cities around modern Samarkand in Uzbekistan, an area that has been inhabited since the 4th millennium BCE. The Sogdians developed trading networks that spanned over 1,500 miles - into ancient China. The road expanded with he Persian Royal Road from the 5th century BCE across Turkey and with the conquests of Alexander the Great in the 300s BCE, the Macedonian Empire pushed into Central Asia into modern Uzbekistan. The satrap Diodotus I claimed independence of one of those areas between the Hindu Kush, Pamirs, and Tengri Tagh mountains, which became known as the Hellenized name Bactria and called the Greco-Bactrian and then Into-Greek Kingdoms by history. Their culture also dates back thousands of years further. 

The Bactrians became powerful enough to push into the Indus Valley, west along the Caspian Sea, and north to the Syr Darya river, known as the Jaxartes at the time and to the Aral Sea. They also pushed south into modern Pakistan and Afghanistan, and east to modern Kyrgyzstan. To cross the Silk Road was to cross through Bactria, and they were considered a Greek empire in the east. The Han Chinese called them Daxia in the third century BCE. They grew so wealthy from the trade that they became the target of conquest by neighboring peoples once the thirst for silk could not be unquenched in the Roman Empire. The Romans consumed so much silk that silver reserves were worn thin and they regulated how silk could be used - something some of the Muslim’s would do over the next generations. 

Meanwhile, the Chinese hadn’t known where their silk was destined, but had been astute enough to limit who knew how silk was produced. The Chinese general Pan Chao in the first century AD and attempted to make contact with the Roman’s only to be thwarted by Parthians, who acted as the middlemen on many a trade route. It wasn’t until the Romans pushed East enough to control the Persian Gulf that an envoy was sent by Marcus Aurelius that made direct contact with China in 166 AD and from there, spread throughout the kingdom. Justinian even sent monks to bring home silkworm eggs but they were never able to reproduce silk, in part because they didn’t have mulberry trees. Yet, the west had perpetrated industrial espionage on the east, a practice that would be repeated in 1712 when a Jesuit priest found how the Chinese created porcelain. 

The Silk Road was a place where great fortunes could be found or lost. The Dread Pirate Roberts was a character from a movie called the Princess Bride, who had left home to make his fortune, so he could spend his life with his love, Buttercup. The Silk Road had made many a fortune, so Ross Ulbricht used that name on a site he created called the Silk Road, along with Frosty and Attoid. He’d gotten his Bachelors at the University of Texas and Masters at Penn State University before he got the idea to start a website he called the Silk Road in 2011. Most people connected to the site via ToR and paid for items in bitcoins. After he graduated from Penn State, he’d started a couple of companies that didn’t do that well. Given the success of Amazon, he and a friend started a site to sell used books, but Ulbricht realized it was more profitable to be the middle man, as the Parthians had thousands of years earlier. The new site would be Underground Brokers and later changed to The Silk Road. Cryptocurrencies allowed for anonymous transactions. He got some help from others, including two that went by the pseudonyms Smedley (later suspected to be Mike Wattier) and Variety Jones (later suspected to be Thomas Clark).

They started to facilitate transactions in 2011. Business was good almost from the beginning. Then Gawker published an article about the site and more and more attention was paid to what was sold through this new darknet portal. The United States Department of Justice and other law enforcement agencies got involved. When bitcoins traded at less than $80 each, the United States Drug Enforcement Agency (DEA) seized 11 bitcoins, but couldn’t take the site down for good. It was actually an IRS investigator named Gary Alford who broke the case when he found the link between the Dread Pirate Roberts and Attoid and then a post that included Ulbricht’s name and phone number. Ulbricht was picked up in San Francisco and 26,000 bitcoins were seized, along with another 144,000 from Ulbricht’s personal wallets. Two federal agents were arrested when it was found they traded information about the investigation to Ulbricht. Ulbricht was also accused of murder for hire, but those charges never led to much. Ulbricht now servers a life sentence.

The Silk Road of the darknet didn’t sell silk. 70% of the 10,000 things sold were drugs. There were also fake identities, child pornography, and through a second site, firearms. There were scammers. Tens of millions of dollars flowed over this new Silk Road. But the secrets weren’t guarded well enough and a Silk Road 2 was created in 2013, which only lasted a year. Others come and go. It’s kinda’ like playing whack-a-mole. The world is a big place and the reach of law enforcement agencies limited, thus the harsh sentence for Ulbricht.

Dassler shoes was started by Adolf Dassler in 1924 in Germany, after he came home from World War I. His brother Rudolph joined him. They made athletic shoes and developed spikes to go on the bottom of the shoes. By 1936, they convinced Jesse Owens to wear their shoes on the way to his gold medals. Some of the American troops who liked the shoes during World War II helped spread the word.

The brothers had a falling out soon after the war was over. Adolph founded Adidas while Rudolph created a rival shoe company called Puma. This was just in time for the advertising industry to convince people that if they bought athletic shoes that they would instantly be, er, athletic. The two companies became a part of an ad-driven identity that persists to this day. One most who buy the products advertised hardly understand themselves.

A national identity involves concentric circles of understanding. The larger a nation, the more concentric circles and the harder it is to nail down exactly who has what identity. Part of this is that people spend less time thinking about who they are and more time being told who they should want to be like. Woven into the message of who a person should be is a bunch of products that a person has to buy to become the ideal. That’s called advertising. 

James White founded the first modern advertising agency called ‘R. F. White & Son' in Warwick Square, London in 1800. The industry evolved over the next hundred or so years as more plentiful supplies led to competition and so more of a need to advertise goods. Increasingly popular newspapers from better printing presses turned out a great place to advertise. The growth of industrialism meant there were plenty of goods and so competition between those who manufactured or trafficked those goods. The more efficient the machines of industry became, the more the advertising industry helped sell what the world might not yet know it needed. Many of those agencies settled into Madison Avenue in New York as balances of global power shifted and so by the end of World War II, Madison Avenue became a synonym for advertising. Many now-iconic brands were born in this era.

Manufacturers and distributors weren’t the only ones to use advertising. People put out ads to find loves in personals and by the 1950s advertising even began to find its way into politics. Iconic politicians could be created. 

Dwight D Eisenhower served as the United States president from 1953 to 1961. He oversaw the liberation of Northern Africa in World War II, before he took command to plan the invasion of Normandy on D Day. He was almost universally held as a war hero in the United States. He had not held public office but the ad men of Madison Avenue were able to craft messages that put him into the White House. Messages like “I like Ike.”

These were the early days of television and the early days of computers. A UNIVAC was able to predict that Eisenhower would defeat Adlai Stevenson in a landslide election in 1952. The country was not “Madly for Adlai” as his slogan went. 

ENIAC had first been used in 1945. MIT Whirlwind was created in 1951, and the age of interactive computing was upon us. Not only could a computer predict who might win an election but new options in data processing allowed for more granular ways to analyze data. A young Senator named John F. Kennedy was heralded as a “new candidate for the 1960s.” Just a few years later Stephenson had lambasted Ike for using advertising, but this new generation was willing to let computers help build a platform - just as the advertisers were starting to use computers to help them figure out the best way to market a product. It turns out that words mattered.

At the beginning of that 1960 election, many observed they couldn’t tell much difference between the two candidates: Richard Nixon and John Kennedy. Kennedy’s democrats were still largely factored between those who believed in philosophies dating back to the New Deal and segregationists. Ike presided over the early days of the post-World War II new world order. This new generation, like new generations before and since, was different. They seemed to embrace the new digital era. Someone like JFK wasn’t punching cards and feeding them into a computer, writing algorithms, or out surveying people to collect that data. That was done by a company that was founded in 1959 called Simulmatics. Jill Lepore called them the What If men in her book called If/Then - a great read that goes further into the politics of the day. It’s a fascinating read. The founder of the company was a Madison Avenue ad man named Ed Greenfield. He surrounded himself with a cast of characters that included people from John Hopkins University, MIT, Yale, and IBM. 

Ithiel de Sola Pool had studied Nazi and Soviet propaganda during World War II. He picked up on work from Hungarian Frigyes Karinthy and with students ran Monte Carlo simulations on people’s acquaintances to formulate what would later become The Small World Problem or the Six Degrees of Separation, a later inspiration for the social network of the same name and even later, for Facebook. The social sciences had become digital. Political science could then be used to get at the very issues that could separate Kennedy from Nixon.

The People Machine as one called it was a computer simulation, thus the name of the company. It would analyze voting behaviors. The previous Democratic candidate Stevenson had long-winded, complex speeches. They analyzed the electorate and found that “I Like Ike” resonated with more people. It had, after all, been developed by the same ad man who came up with “Melts in your mouth, not in your hands” for M&Ms. They called the project Project Microscope. They recruited some of the best liberal minds in political science and computer science. They split the electorate into 480 groups. A big focus was how to win the African-American vote. Turns out Gallup polls didn’t study that vote because Southern newspapers had blocked doing so.

Civil rights, and race relations in general wasn’t unlike a few other issues. There was anti-Catholic, anti-Jew, and anti-a lot. The Republicans were the party of Lincoln and had gotten a lot of votes over the last hundred years for that. But factions within the party had shifted. Loyalties were shifting. Kennedy was a Catholic but many had cautioned he should down-play that issue. The computer predicted civil rights and anti-Catholic bigotry would help him, which became Kennedy’s platform. He stood for what was right but were they his positions or just what the nerds thought? He gained votes at the last minute. Turns out the other disenfranchised groups saw the bigotry against one group as akin to bigotry against their own; just like the computers thought they would. Kennedy became an anti-segregationist, as that would help win the Black vote in some large population centers. It was the most aggressive, or liberal, civil-rights plank the Democrats had ever taken up. 

Civil rights are human rights. Catholic rights are as well. Kennedy offered the role of Vice President to Lyndon B Johnson, the Senate Majority Leader and was nominated to the Democratic candidate. Project Microscope from Simulmatics was hired in part to shore up Jewish and African-American votes. They said Kennedy should turn the fact that he was a Catholic into a strength. Use the fact he was Catholic to give up a few votes here and there in the South but pick up other votes. He also took the Simulmatics information as it came out of the IBM 704 mainframe to shore up his stance on other issues. That confidence helped him out-perform Nixon in televised debates. They used teletypes and even had the kids rooms converted into temporary data rooms. CBS predicted Nixon would win. Less than an hour later they predicted Kennedy would win. Kennedy won the popular vote by .1 percent of the country even after two recounts. The Black vote hat turned out big for Kennedy.

News leaked about the work Simulmatics had done for Kennedy. Some knew that IBM had helped Hitler track Jews as has been written about in the book IBM and the Holocaust by Edwin Black. Others still had issues with advertising in campaigns and couldn’t fathom computers. Despite Stalin’s disgust for computers some compared the use of computers to Stalinistic propaganda. Yet it worked - even if in retrospect the findings were all things we could all take for granted. They weren’t yet. The Kennedy campaign at first denied the “use of an electronic brain and yet their reports live on in the Kennedy Library. A movement against the use of the computer seemed to die after Kennedy was assassinated. 

Books of fiction persisted, like The 480 from Eugene Burdick, which got its title from the number of groups Simulmatics used. The company went on to experiment with every potential market their computer simulation could be used in. The most obvious was the advertising industry. But many of those companies went on to buy their own computers. They already had what many now know is the most important aspect of any data analytics project: the data. Sometimes they had decades of buying data - and could start over on more modern computers. They worked with the Times to analyze election results in 1962, to try and catch newspapers up with television. The project was a failure and newspapers leaned into more commentary and longer-term analysis to remain a relevant supplier of news in a world of real-time television. They applied their brand of statistics to help simulate the economy of Venezuela in a project called Project Camelot, which LBJ later shot down. 

Their most profitable venture became working with the defense department to do research in Vietnam. They collected data, analyzed data, punched data into cards, and fed it into computers. Pool was unabashedly pro-US and it’s arguable that they saw what they wanted to see. So did the war planners in the pentagon, who followed Robert McNamara. McNamara had been one of the Quiz Kids who turned around the Ford Motor Company with a new brand of data-driven management to analyze trends in the car industry, shore up supply chains, and out-innovate the competition. He became the first president of the company who wasn’t a Ford. His family had moved to the US from Ireland to flee the Great Irish Famine. Not many generations later he got an MBA from Harvard before he became a captain in the United States Army Air Forces during World War II primarily as an analyst. Henry Ford the second hired his whole group to help with the company. 

As many in politics and the military learn, companies and nations are very different. They did well at first, reducing the emphasis on big nuclear first strike capabilities and developing other military capabilities. One of those was how to deal with guerrilla warfare and counterinsurgencies. That became critical in Vietnam, a war between the communist North Vietnamese and the South Vietnamese. The North was backed by North Korea, China, and the Soviet Union, the South backed by the United States, South Korea, Australia. Others got involved but those were the main parties. We can think of McNamara’s use of computers to provide just in time provisioning of armed forces and move spending to where it could be most impactful, which slashed over $10 billion in military spending. As the Vietnam war intensified, statistically the number of troops killed by Americans vs American casualties made it look computationally like the was was being won. In hindsight we know it was not. 

Under McNamara, ARPA hired Simulmatics to study the situation on the ground. They would merge computers, information warfare, psychological warfare, and social sciences. The Vietnamese that they interviewed didn’t always tell them the truth. After all, maybe they were CIA agents. Many of the studies lacked true scholars as the war was unpopular back home. People who collected data weren’t always skilled at the job. They spoke primarily with those they didn’t get shot at as much while going to see. In general, the algorithms might have worked or might not have worked - but they had bad data. Yet Simulmatics sent reports that the operations were going well to McNamara. Many in the military would remember this as real capabilities at cyber warfare and information warfare were developed in the following decades.

Back home, Simulmatics also became increasingly tied up in things Kennedy might have arguably fought against. There were riots, civil rights protests, and Simulatics took contracts to simulate racial riots. Some felt they could riot or go die in in the jungles of Vietnam. The era of predictive policing had begun as the hope of the early 1960s turned into the apathy of the late 1960s. Martin Luther King Jr spoke out again riot prediction, yet Simulmatics pushed on. Whether their insights were effective in many of the situations, just like in Vietnam - was dubious. They helped usher in the era of Surveillance capitalism, in a way. But the arrival of computers in ad agencies meant that if they hadn’t of, someone else would have. 

People didn’t take kindly to being poked, prodded, and analyzed intellectually. Automation took jobs, which Kennedy had addressed in rhetoric if not in action. The war was deeply unpopular as American soldiers came home from a far off land in caskets. The link between Simulmatics and academia was known. Students protested against them and claimed they were war criminals. The psychological warfare abroad, being on the wrong side of history at home with the race riots, and the disintegrating military-industrial-university complex didn’t help.

There were technical issues. The technology had changed away from languages like FORTRAN. Further, the number of data points required and how they were processed required what we now call “Big Data” and “machine learning.” Those technologies showed promise early but more mathematics needed to be developed to fully weaponize the surveillance everything. More code and libraries needed to be developed to crunch the large amounts of statistics. More work needed to be done to get better data and process it. The computerization of the social sciences was just beginning and while people like Pool predicted the societal impacts we could expect, people at ARPA doubted the results and the company they created could not be saved as all these factors converged to put them into bankruptcy in 1970. 

Their ideas and research lived on. Pool and others published some of their findings. Books opened the minds to the good and bad of what technology could do. The Southern politicians, or Dixiecrats, fell apart. Nixon embraced a new brand of conservatism as he lost the race to be the Governor of California to Pat Brown in 1962. There were charges of voter fraud from the 1960 election. The Mansfeld Amendment restricted military funding of basic research in 1969 and went into effect in 1970. Ike had warned of the growing links between universities as the creators of weapons of war like what Simulmatics signified and the amendment helped pull back funding for such exploits. As Lepore points out in her book, mid-century liberalism was dead.

Nixon tapped into the silent majority who countered the counterculture of the 1960s. Crime rose and the conservatives became the party of law and order. He opened up relations with China, spun down the Vietnam war, negotiated with the Soviet leader Brezhnev to warm relations, and rolled back Johnson’s attempts at what had been called The Great Society to get inflation back in check. Under him the incarceration rate in the United States exploded. His presidency ended with Watergate and under Ford, Carter, Reagan, and Bush, the personal computer became prolific and the internet, once an ARPA project began to take shape. They all used computers to find and weigh issues, thaw the Cold War, and build a new digitally-driven world order. The Clinton years saw an acceleration of the Internet and by the early 2000s companies like PayPal were on the rise. One of their founders was Peter Thiel.

Peter Thiel founded Palantir in 2003 then invested in companies like Facebook with his PayPal money. Palantir received backing from In-Q-Tel “World-class, cutting-edge technologies for National Security”. In-Q-Tel was founded in 1999 as the global technological evolution began to explode. While the governments of the world had helped build the internet, it wasn’t long before they realized it gave an asymmetrical advantage to newcomers. The more widely available the internet, the more far reaching attacks could go, the more subversive economic warfare could be. Governmental agencies like the United States Central Intelligence Agency (CIA) needed more data and the long promised artificial intelligence technologies to comb through that data. Agencies then got together and launched their own venture capital fund, similar to those in the private sector - one called In-Q-Tel. Palantir has worked to develop software for the US Immigration and Customers Enforcement, or ICE, to investigate criminal activities and allegedly used data obtained from Cambridge Analytica along with Facebook data. The initial aim of the company was to take technology developed for PayPal’s fraud detection and apply it to other areas like terrorism, with help from intelligence agencies. They help fight fraud for nations and have worked with the CIA, NSA, FBI, CDC, and various branches of the United States military on various software projects. Their Gotham project is the culmination of decades of predictive policing work. 

There are dozens of other companies like Palantir. Just as Pool’s work on Six Degrees of Separation, social networks made the amount of data that could be harvested all the greater. Companies use that data to sell products. Nations use that data for propaganda. Those who get elected to run nations use that data to find out what they need to say to be allowed to do so. The data is more accurate with every passing year. Few of the ideas are all that new, just better executed. The original sin mostly forgotten, we still have to struggle with the impact and ethical ramifications. Politics has always had a bit of a ruse in a rise to power. Now it’s less about personal observation and more about the observations and analyses that can be gleaned from large troves of data. The issues brought up in books like The 480 are as poignant today as they were in the 1950s.

Taiwan is a country about half the size of Maine with about 17 times the population of that state. Taiwan sits just over a hundred miles off the coast of mainland China. It’s home to some 23 and a half million humans, roughly half way between Texas and Florida or a few more than live in Romania for the Europeans. Taiwan was connected to mainland China by a land bridge in the Late Pleistocene and human remains have been found dating back to 20,000 to 30,000 years ago. About half a million people on the island nation are aboriginal, or their ancestors are from there. But the population became more and more Chinese in recent centuries.

Taiwan had not been part of China during the earlier dynastic ages but had been used by dynasties in exile to attack one another and so became a part of the Chinese empire in the 1600s. Taiwan was won by Japan in the late 1800s and held by the Japanese until World War II. During that time, a civil war had raged on the mainland of China with the Republic of China eventually formed as the replacement government for the Qing dynasty following a bloody period of turf battles by warlords and then civil war.

Taiwan was in martial law from the time the pre-communist government of China retreated there during the exit of the Nationalists from mainland China in the 1940s to the late 1980. During that time, just like the exiled Han dynasty, they orchestrated war from afar. They stopped fighting, much like the Koreans, but have still never signed a peace treaty. And so large parts of the world remained in stalemate. 

As the years became decades, Taiwan, or the Republic of China as they still call themselves, has always had an unsteady relationship with the People’s Republic of China, or China as most in the US calls them. The Western world recognized the Republic of China and the Soviet and Chines countries recognized the mainland government. US President Richard Nixon visited mainland China in 1972 to re-open relations with the communist government there and relations slowly improved.

The early 1970s was a time when much of the world still recognized the ruling government of Taiwan as the official Chinese government and there were proxy wars the two continued to fight. The Taiwanese and Chinese still aren’t besties. There are deep scars and propaganda that keep relations from being repaired. 

Before World War II, the Japanese also invaded Hong Kong. During the occupation there, Morris Chang’s family became displaced and moved to a few cities during his teens before he moved Boston to go to Harvard and then MIT where he did everything to get his PhD except defend his thesis. He then went to work for Sylvania Semiconductor and then Texas Instruments, finally getting his PhD from Stanford in 1964. He became a Vice President at TI and helped build an early semiconductor designer and foundry relationship when TI designed a chip and IBM manufactured it.

The Premier of Taiwan at the time, Sun Yun-suan, who played a central role in Taiwan’s transformation from an agrarian economy to a large exporter. His biggest win was when to recruit Chang to move to Taiwan and found TSCM, or Taiwan Semiconductor Manufacturing Company. Some of this might sound familiar as it mirrors stories from companies like Samsung in South Korea. In short, Japanese imperialism, democracies versus communists, then rapid economic development as a massive manufacturing powerhouse in large part due to the fact that semiconductor designers were split from semiconductor foundry’s or where chips are actually created. 

In this case, a former Chinese national was recruited to return as founder and led TSMC for 31 years before he retired in 2018. Chang could see from his time with TI that more and more companies would design chips for their needs and outsource manufacturing. They worked with Texas Instruments, Intel, AMD, NXP, Marvell, MediaTek, ARM, and then the big success when they started to make the Apple chips. The company started down that path in 2011 with the A5 and A6 SoCs for iPhone and iPad on trial runs but picked up steam with the A8 and A9 through A14 and the Intel replacement for the Mac, the M1. They now sit on a half trillion US dollar market cap and are the largest in Taiwan. For perspective, their market cap only trails the GDP of the whole country by a few billion dollars. 

Nvidia TSMC is also a foundry Nvidia uses. As of the time of this writing, Nvidia is the 8th largest semiconductor company in the world. We’ve already covered Broadcom, Qualcomm, Micron, Samsung, and Intel. Nvidia is a fabless semiconductor company and so design chips that vendors like TSMC manufacture. 

Nvidia was founded by Jensen Huang, Chris Malachowsky, and Curtis Priem in 1993 in Santa Clara, California (although now incorporated in Delaware). Not all who leave the country they were born in due to war or during times of war return. Huang was born in Taiwan and his family moved to the US right around the time Nixon re-established relations with mainland China. Huang then went to grad school at Stanford before he became a CPU designer at AMD and a director at LSI Logic, so had experience as a do-er, a manager, and a manager’s manager. 

He was joined by Chris Malachowsky and Curtis Priem, who had designed the IBM Professional Graphics Adapter and then the GX graphics chip at Sun.   because they saw this Mac and Windows and Amiga OS graphical interface, they saw the games one could play on machines, and they thought the graphics cards would be the next wave of computing. And so for a long time, Nvidia managed to avoid competition with other chip makers with a focus on graphics. That initially meant gaming and higher end video production but has expanded into much more like parallel programming and even cryptocurrency mining.  

They were more concerned about the next version of the idea or chip or company and used NV in the naming convention for their files. When it came time to name the company, they looked up words that started with those letters, which of course don’t exist - so instead chose invidia or Nvidia for short, as it’s latin for envy - what everyone who saw those sweet graphics the cards rendered would feel. 

They raised $20 million in funding and got to work. First with SGS-Thomson Microelectronics in 1994 to manufacture what they were calling a graphical-user interface accelerator that they packaged on a single chip. They worked with Diamond Multimedia Systems to install the chips onto the boards. In 1995 they released NV1. The PCI card was sold as Diamond Edge 3D and came with a 2d/3d graphics core with quadratic texture mapping. Screaming fast and Virtual Fighter from Sega ported to the platform. 

DirectX had come in 1995. So Nviia released DirectX drivers that supported Direct3D, the api that Microsoft developed to render 3d graphics. This was a time when 3d was on the rise for consoles and desktops. Nvidia timed it perfectly and reaped the rewards when they hit a million sold in the first four months for the RIVA, a 128-bit 3d processor that got used as an OEM in 1997. Then the 1998 RIVAZX with RIVATNT for multi-texture 3D processing. They also needed more manufacturing support at this point and entered into a strategic partnership with TSMC to manufacture their boards.

A lot of vendors had a good amount of success in their niches. By the late 1990s there were companies who made memory, or the survivors of the DRAM industry after ongoing price dumping issues. There were companies that made central processors like Intel. Nvidia led the charge for a new type of chip, the GPU. They invented the GPU in 1999 when they released the GeForce 256. This was the first single-chip GPU processor. This means integrated lightings, triangle setups, rendering, like the old math coprocessor but for video. Millions of polygons could be drawn on screens every second. They also released the Quadro Pro GPU for professional graphics and went public in 1999 at an IPO of $12 per share. 

Nvidia used some of the funds from the IPO to scale operations, organically and inorganically. In 2000 they released the GeForce2 Go for laptops and acquired 3dfx, closing deals to get their 3d chips in devices from OEM manufacturers who made PCs and in the new Microsoft Xbox. By 2001 they hit $1 billion in revenues and released the GeForce 3 with a programmable GPU, using APIs to make their GPU a platform. They also released the nForce integrated graphics and so by 2002 hit 100 million processors out on the market.

They acquired MediaQ in 2003 and partnered with game designer Blizzard to make Warcraft. They continued their success in the console market when the GeForce platform was used in the PS 3 in 2005 and by 2006 had sold half a billion processors. They also added the  CUDA architecture that year to put a general purpose GPU on the market and acquired Hybrid Graphics who develops 2D and 3D embedded software for mobile devices.

In 2008 they went beyond the consoles and PCs when Tesla used their GPUs in cars. They also acquired PortalPlayer, who supplies semiconductors and software for personal media players and launched the Tegra mobile processor to get into the exploding mobile market. More acquisitions in 2008 but a huge win when the GeForce 9400M was put into Apple MacBooks. Then more smaller chips in 2009 when the Tegra processors were used in Android devices.

They also continued to expand how GPUs were used. They showed up in Ultrasounds and in 2010 the Audi. By then they had the Tianhe-1A ready to go, which showed up in supercomputers and the Optimus. All these types of devices that could use a GPU meant they hit a billion processors sold in 2011, which is when they went dual core with the Tegra 2 mobile processor and entered into cross licensing deals with Intel. 

At this point TSMC was able to pack more and more transistors into smaller and smaller places. This was a big year for larger jobs on the platform. By 2012, Nvidia got the Kepler-based GPUs out by then and their chips were used in the Titan supercomputer. They also released a virtualized GPU GRID for cloud processing. 

It wasn’t all about large-scale computing efforts. The Tegra-3 and GTX 600 came out in 2012 as well. Then in 2013 the Tegra 4, a quad-core mobile processor, a 4G LTE mobile processor, Nvidia Shield for portable gaming, the GTX Titan, a grid appliance. In 2014 the Tegra K1 192, a shield tablet, and Maxwell. In 2015 came the TegraX1 with deep learning with 256 cores and Titan X and Jetson TX1 for smart machines, and the Nvidia Drive for autonomous vehicles. They continued that deep learning work with an appliance in 2016 with the DGX-1. The Drive got an update in the form of PX 2 for in-vehicle AI. By then, they were a 20 year old company and working on the 11th generation of the GPU and most CPU architectures had dedicated cores for machine learning options of various types. 

2017 brought the Volta, Jetson TX2, and SHIELD was ported over to the Google Assistant. 2018 brought the Turing GPU architecture, the DGX-2, AGX Xavier, Clara, 2019 brought AGX Orin for robots and autonomous or semi-autonomous piloting of various types of vehicles. They also made the Jetson Nano and Xavier, and EGX for Edge Computing. At this point there were plenty of people who used the GPUs to mine hashes for various blockchains like with cryptocurrencies and the ARM had finally given Intel a run for their money with designs from the ARM alliance showing up in everything but a Windows device (so Apple and Android). So they tried to buy ARM from SoftBank in 2020. That deal fell through eventually but would have been an $8 billion windfall for Softbank since they paid $32 billion for ARM in 2016. 

We probably don’t need more consolidation in the CPU sector. Standardization, yes. Some of top NVIDIA competitors include Samsung, AMD, Intel Corporation Qualcomm and even companies like Apple who make their own CPUs (but not their own GPUs as of the time of this writing). In their niche they can still make well over $15 billion a year. 

The invention of the MOSFET came from immigrants Mohamed Atalla, originally from Egypt, and Dawon Kahng, originally from from Seoul, South Korea. Kahng was born in Korea in 1931 but immigrated to the US in 1955 to get his PhD at THE Ohio State University and then went to work for Bell Labs, where he and Atalla invented the MOSFET, and where Kahng retired. The MOSFET was an important step on the way to a microchip. 

That microchip market with companies like Fairchild Semiconductors, Intel, IBM, Control Data, and Digital Equipment saw a lot of chip designers who maybe had their chips knocked off, either legally in a clean room or illegally outside of a clean room. Some of those ended in legal action, some didn’t. But the fact that factories overseas could reproduce chips were a huge part of the movement that came next, which was that companies started to think about whether they could just design chips and let someone else make them. That was in an era of increasing labor outsourcing, so factories could build cars offshore, and the foundry movement was born - or companies that just make chips for those who design them. 

As we have covered in this section and many others, many of the people who work on these kinds of projects moved to the United States from foreign lands in search of a better life. That might have been to flee Europe or Asian theaters of Cold War jackassery or might have been a civil war like in Korea or Taiwan. They had contacts and were able to work with places to outsource too and given that these happened at the same time that Hong Kong, Singapore, South Korea, and Taiwan became safe and with no violence. And so the Four Asian Tigers economies exploded, fueled by exports and a rapid period of industrialization that began in the 1960s and continues through to today with companies like TSMC, a pure play foundry, or Samsung, a mixed foundry - aided by companies like Nvidia who continue to effectively outsource their manufacturing operations to companies in the areas. At least, while it’s safe to do so. 

We certainly hope the entire world becomes safe. But it currently is not. There are currently nearly a million Rohingya refugees fleeing war in Myanmar. Over 3.5 million have fled the violence in Ukraine. 6.7 million have fled Syria. 2.7 million have left Afghanistan. Over 3 million are displaced between Sudan and South Sudan. Over 900,000 have fled Somalia. Before Ukranian refugees fled to mostly Eastern European countries, they had mainly settled in Turkey, Jordan, Lebanon, Pakistan, Uganda, Germany, Iran, and Ethiopia. Very few comparably settled in the 2 largest countries in the world: China, India, or the United States. 

It took decades for the children of those who moved or sent their children abroad to a better life to be able to find a better life. But we hope that history teaches us to get there faster, for the benefit of all.

Mark Pincus was at the forefront of mobile technology when it was just being born. He is a recovering venture capitalist who co-founded his first company with Sunil Paul in 1995. FreeLoader was at the forefront of giving people the news through push technology, just as the IETF was in the process of ratifying HTTP2. He sold that for $38 million only to watch it get destroyed. But he did invest in a startup that one of the interns founded when he gave Sean Parker $100,000 to help found Napster. 

Pincus then started Support.com, which went public in 2000. Then Tribe.net, which Cisco acquired. As a former user, it was fun while it lasted. Along the way, Pincus teamed up with Reid Hoffman, former PayPal executive and founder of LinkedIn and bought the Six Degrees patent that basically covered all social networking. Along the way, he invested in Friendster, Buddy Media, Brightmail, JD.com, Facebook, Snapchat, and Twitter. 

Investing in all those social media properties gave him a pretty good insight into what trends were on the way. Web 2.0 was on the rise and social networks were spreading fast. As they spread, each attempted to become a platform by opening APIs for third-party developers. This led to an opening to create a new company that could build software that sat on top of these social media companies. Meanwhile, the gaming industry was in a transition from desktop and console games to hyper-casual games that are played on mobile devices. So Pincus recruited conspirators to start yet another company and with Michael Luxton, Andrew Trader, Eric Schiermeyer, Steve Schoettler, and Justin Waldron, Zinga was born in 2007. Actually Zinga is the dog. The company Zynga was born in 2007.

Facebook was only three years old at the time, but was already at 14 million users to start 2007. That’s when they opened up APIs for integration with third party products through FBML, or Facebook Markup Language. They would have 100 million within a year. Given his track record selling companies and picking winners, Zynga easily raised $29 million to start what amounts to a social game studio. They make games that people access through social networks. Luxton, Schiermeyer, and Waldron created the first game, Zynga Poker in 2007. It was a simple enough Texas hold ’em poker game but rose to include tens of millions of players at its height, raking in millions in revenue. 

They’d proven the thesis. Social networks, especially Facebook, were growing.. The iPhone came out in 2007. That only hardened their resolve. They sold poker chips in 2008. Then came FarmVille.

FarmVille was launched in 2009 and an instant hit. The game went viral and had a million daily users in a week. It was originally written in flash and later ported to iPhones and other mobile platforms. It’s now been installed over 700 million times and ran until 2020, when Flash support was dropped by Facebook. FarmVille was free-to-play and simple. It had elements of a 4x game like Civilization, but was co-op, meaning players didn’t exterminate one another but instead earned points and thus rankings. In fact, players could help speed up tasks for one another.

Players began with a farm - an empty plot of land. They earned experience points by doing routine tasks. Things like growing crops, upgrading items, plowing more and more land. Players took their crops to the market and sold them for coins. Coins could also be bought. If a player didn’t harvest their crops when they were mature, the crops would die. Thus, they had players coming back again and again. Push notifications helped remind people about the state of their farm. Or the news in FreeLoader-speak.  

Some players became what we called dolphins, or players that spent about what they would on a usual game. Maybe $10 to $30. Others spent thousands, which we referred to as whales. They became the top game on Facebook and the top earner. They launched sequels as well, with FarmVille 2 and FarmVille 3. 

They bought Challenge Games in 2010, which was founded by Andrew Busy to develop casual games a well. They bought 14 more companies. They grew to 750 employees. They opened offices in Bangalore, India and Ireland. They experimented with other platforms, like Microsoft’s MSN gaming environment and Google TV. They released CastleVille. And they went public towards the end of 2011. It was a whirlwind ride, and just really getting started. They released cute FarmVille toys. 

They also released Project Z, Mafia Wars, Hanging with Friends, Adventure World, and Hidden Chronicles. And along the way they became a considerable advertising customer for Facebook, with ads showing up for Mafia Wars and Project Z constantly. Not only that, but their ads flooded other mobile ad networks, as The Sims Social and other games caught on and stole eyeballs. And players were rewarded for spamming the walls of other players, which helped to increase the viral nature of the early Facebook games.

Pincus and the team built a successful, vibrant company. They brought in Jeff Karp and launched Pioneer Trail. Then another smash hit, Words with Friends. They bought Newtoy for $53.3 million to get it, after Paul and David Bettner who wrote a game called Chess with Friends a few years earlier. But revenues dropped as the Facebook ride they’d been on began to transition from people gaming in a web browser to mobile devices.

All this growth and the company was ready for the next phase. In 2013, Zynga hired Donald Mattrick to be the CEO and Pincus moved to the role of Chief Product Officer. The brought in Alex Garden, the General Manager for Xbox Music , Video, and Reading, who had founded the Homeward creator Relic Entertainment back in the 1990s. The new management didn’t fix the decline. The old games continued to lose market share and Pincus came back to run the company as CEO and cut the staff by 18 percent. In 2015 they brought in Frank Gibeau to the board and by 2016 moved him to  CEO of the company.

One challenge with the move to mobile was who got the processing payments. Microtransactions had gone through Facebook for years. They moved to Stripe in 2020. They acquired Gram Games, to get Merge Dragons! They bought Small Giant Games to get Empires & Puzzles. They bought Peak Games to get Toon Blast and Toy Blast. They picked up Rollic to get a boatload of actions and puzzle games. They bought Golf Rival by acquiring StarLark. And as of the time of this writing they have nearly 200 million players actively logging into their games.

There are a few things to take from the story of Zynga. One is that a free game doesn’t put $2.8 billion in revenues on the board, which is what they made in 2021. Advertising amounts for just north of a half billion, but the rest comes from in app purchases. The next is that the transition from owner-operators is hard. Pincus and the founding team had a great vision. They executed and were rewarded by taking the company to a gangbuster IPO. The market changed and it took a couple of pivots to get there. That led to a couple of management shakeups and a transition to more of a portfolio mindset with the fleet of games they own. Another lesson is that larger development organizations don’t necessarily get more done. That’s why Zynga has had to acquire companies to get hits since around the time that they bought Words with Friends. 

Finally, when a company goes public the team gets distracted. Not only is going through an IPO expensive and the ensuing financial reporting requirements a hassle to deal with, but it’s distracting. Employees look at stock prices during the day. Higher ranking employees have to hire a team of accountants to shuffle their money around in order to take advantage of tax loopholes. Growth leads to political infighting and power grabbing. There are also regulatory requirements with how we manage our code and technology that slow down innovation. But it all makes us better run and a safer partner eventually.

All companies go through this. Those who navigate towards a steady state fastest have the best chance of surviving one more lesson: when the first movers prove a monetization thesis the ocean will get red fast. Zynga became the top mobile development company again after weathering the storm and making a few solid acquisitions. But as Bill Gates pointed out in the 1980s, gaming is a fickle business. So Zynga agreed to be acquired for $12.7 billion in 2022 by Take-Two Interactive, who now owns the Civilization, Grand Theft Auto, Borderlands, WWE, Red Dead, Max Payne, NBA 2K, PGA 2K, Bioshock, Duke Nukem, Rainbow Six: Rogue Spear, Battleship, Centipede, and the list goes on and on. They’ve been running a portfolio for a long time. Pincus took away nearly $200 million in the deal and about $350 million in Take-Two equity. Ads and loot boxes can be big business.

Meanwhile, Pincus and Hoffman from LinkedIn work well together, apparently. They built Reinvent Capital, an investment firm that shows that venture capital has quite a high recidivism rate. They had a number of successful investments and SPACs. 

Zynga was much more. They exploited Facebook to shoot up to hundreds of millions in revenue. That was revenue Facebook then decided they should have a piece of in 2011, which cut those Zynga revenues in half over time. This is an important lesson any time a huge percentage of revenue is dependent on another party who can change the game (no pun intended) at any time. Diversify. 

In the beginning was the command line. Actually, before that were punch cards and paper tape. But at Multics and RSTS and DTSS came out, programmers and users needed a way to interface with the computer through the teletypes and other terminals that appeared in the early age of interactive computing. Those were often just a program that sat on a filesystem eventually as a daemon, listening for input on keyboards. This was one of the first things the team that built Unix needed, once they had a kernel that could compile. And from the very beginning it was independent of the operating system.

Due to the shell's independence from the underlying operating system, numerous shells have been developed during Unix’s history, albeit only a few have attained widespread use. Shells are also referred to as Command-Line Interpreters (or CLIs), processes commands a user sends from a teletype, then a terminal. This provided a simpler interface for common tasks, rather than interfacing with the underlying C programming. Over the years, a number of shells have come and gone. Some of the most basic and original commands came from Multics, but the shell as we know it today was introduced as the Thompson shell in the first versions of Unix.

Ken Thompson introduced the first Unix shell in 1971 with the Thompson Shell, the ancestor of the shell we still find in /bin/sh. The shell ran in the background and allowed for a concise syntax for redirecting the output of commands to one another. For example, pass the output to a file with > or read input from a file with

Lee Felsenstein went to the University of California, Berkeley in the 1960s. He worked at the tape manufacturer Ampex, where Oracle was born out of before going back to Berkeley to finish his degree. He was one of the original members of the Homebrew Computer Club, and as with so many inspired by the Altair S-100 bus, designed the Sol-20, arguably the first microcomputer that came with a built-in keyboard that could be hooked up to a television in 1976. The Apple II was introduced the following year.

Adam Osborne was another of the Homebrew Computer Club regulars who wrote An Introduction to Microcomputers and sold his publishing company to McGraw-Hill in 1979. Flush with cash, he enlisted Felsenstein to help create another computer, which became the Osborne 1. The first commercial portable computer, although given that it weighed almost 25 pounds, is more appropriate to call a luggable computer. Before Felsensten built computers, though, he worked with a few others on a community computing project they called Community Memory. 

Judith Milhon was an activist in the 1960s Civil Rights movement who helped organize marches and rallies and went to jail for civil disobedience. She moved to Ohio, where she met Efrem Lipkin, and as with many in what we might think of as the counterculture now, they moved to San Francisco in 1968. St Jude, as she became called learned to program in 1967 and ended up at the Berkeley Computer Company after the work on the Berkeley timesharing projects was commercialized. There, she met Pam Hardt at Project One. 

Project One was a technological community built around an alternative high school founded by Ralph Scott. They brought together a number of non-profits to train people in various skills and as one might expect in the San Francisco area counterculture they had a mix of artists, craftspeople, filmmakers, and people with deep roots in technology. So much so that it became a bit of a technological commune. They had a warehouse and did day care, engineering, film processing, documentaries, and many participated in anti-Vietnam war protests.

They had all this space and Hardt called around to find the computer. She got an SDS-940 mainframe donated by TransAmerica in 1971. Xerox had gotten out of the computing business and TransAmerica’s needs were better suited for other computers at the time. They had this idea to create a bulletin board system for the community and created a project at Project One they called Resource One. Plenty thought computers were evil at the time, given their rapid advancements during the Cold War era, and yet many also thought there was incredible promise to democratize everything. 

Peter Deutsch then donated time and an operating system he’d written a few years before. She then published a request for help in the People’s Computer Computer magazine and got a lot of people who just made their own things. An early precursor to maybe micro-services, where various people tinkered with data and programs. They were able to do so because of the people who could turn that SDS into a timesharing system. 

St Jude’s partner Lipkin took on the software part of the project. Chris Macie wrote a program that digitized information on social services offered in the area that was maintained by Mary Janowitz, Sherry Reson, and Mya Shone. That was eventually taken over by the United Way until the 1990s. 

Felsenstein helped with the hardware. They used teletype terminals to connect a video terminal and keyboard built into a wooden cabinet so real humans could access the system. The project then evolved into what was referred to as Community Memory.

Community Memory Community Memory became the first public computerized bulletin board system established in 1973 in Berkeley, California. The first Community Memory terminal was located at Leopard’s Record in Berkeley. This was the first opportunity for people who were not studying the scientific subject to be able to use computers. It became very popular but soon was shut down by the founders because they face hurdles to replicate the equipment and languages being used. They were unable to expand the project. 

This allowed them to expand the timesharing system into the community and became a free online community-based resource used to share knowledge, organize, and grow. The initial stage of Community Memory from 1973 to 1975, was an experiment to see how people would react to using computers to share information. 

Operating from 1973 to 1992, it went from minicomputers to microcomputers as those became more prevelant. Before Resource One and Community Memory, computers weren’t necessarily used for people. They were used for business, scientific research, and military purposes. After Community Memory,  Felsenstein and others in the area and around the world helped make computers personal. Commun tty Memory was one aspect of that process but there were others that unfolded in the UK, France, Germany and even the Soviet Union - although those were typically impacted by embargoes and a lack of the central government’s buy-in for computing in general. 

After the initial work was done, many of the core instigators went in their own directions. For example, Felsenstein went on to create the SOL and pursue his other projects in personal computing. Many had families or moved out of the area after the Vietnam War ended in 1975. The economy still wasn’t great, but the technical skills made them more employable. 

Some of the developers and a new era of contributors regrouped and created a new non-profit in 1977. They started from scratch and developed their own software, database, and communication packages. It was very noisy so they encased it in a card box. It had a transparent plastic top so they could see what was being printed out. This program ran from 1984 to 1989.  After more research, a new terminal was released in 1989 in Berkeley. By then it had evolved into a pre-web social network. 

The modified keyboard had brief instructions mounted on it, which showed the steps to send a message, how to attach keywords to messages, and how to search those keywords to find messages from others. 

Ultimately, the design underwent three generations, ending in a network of text-based browsers running on basic IBM PCs accessing a Unix server. It was never connected to the Internet, and closed in 1992. By then, it was large, unpowered, and uneconomical to run in an era where servers and graphical interfaces were available. A booming economy also ironically meant a shortage of funding. The job market exploded for programmers in the decade that led up to the dot com bubble and with inconsistent marketing and outreach, Community Memory shut down in 1992.

Many of the people involved with Resource One and Community memory went on to have careers in computing. St Jude helped found the cypherpunks and created Mondo 2000 magazine, a magazine dedicated to that space where computers meet culture. She also worked with Efrem Lipkin on CoDesign, and he was a CTO for many of the dot coms in the late 1990s. Chris Neustrup became a programmer for Agilent. The whole operation had been funded by various grants and donations and while there haven’t been any studies on the economic impact due to how hard it is to attribute inspiration rather than direct influence, the payoff was nonetheless considerable.

Lars Magnus Ericsson was working for the Swedish government that made telegraph equipment in the 1870s when he started a little telegraph repair shop in 1976. That was the same year the telephone was invented. After fixing other people’s telegraphs and then telephones he started a company making his own telephone equipment. He started making his own equipment and by the 1890s was shipping gear to the UK. As the roaring 20s came, they sold stock to buy other companies and expanded quickly.

Early mobile devices used radios to connect mobile phones to wired phone networks and following projects like ALOHANET in the 1970s they expanded to digitize communications, allowing for sending early forms of text messages, the way people might have sent those telegraphs when old Lars was still alive and kicking. At the time, the Swedish state-owned Televerket Radio was dabbling in this space and partnered with Ericsson to take first those messages then as email became a thing, email, to people wirelessly using the 400 to 450 MHz range in Europe and 900 MHz in the US. That standard went to the OSI and became a 1G wireless packet switching network we call Mobitex.

Mike Lazaridis was born in Istanbul and moved to Canada in 1966 when he was five, attending the University of Waterloo in 1979. He dropped out of school to take a contract with General Motors to build a networked computer display in 1984. He took out a loan from his parents, got a grant from the Canadian government, and recruited another electrical engineering student, Doug Fregin from the University of Windsor, who designed the first circuit boards. to join him starting a company they called Research in Motion. Mike Barnstijn joined them and they were off to do research. 

After a few years doing research projects, they managed to build up a dozen employees and a million in revenues. They became the first Mobitex provider in America and by 1991 shipped the first Mobitex device. They brought in James Balsillie as co-CEO, to handle corporate finance and business development in 1992, a partnership between co-CEOs that would prove fruitful for 20 years. 

Some of those work-for-hire projects they’d done involved reading bar codes so they started with point-of-sale, enabling mobile payments and by 1993 shipped RIMGate, a gateway for Mobitex. Then a Mobitex point-of-sale terminal and finally with the establishment of the PCMCIA standard, a  PCMCIP Mobitex modem they called Freedom.

Two-way paging had already become a thing and they were ready to venture out of PoS systems. So  in 1995, they took a $5 million investment to develop the RIM 900 OEM radio modem. They also developed a pager they called the Inter@ctive Pager 900 that was capable of  two-way messaging the next year. Then they went public on the Toronto Stock Exchange in 1997.

The next year, they sold a licensing deal to IBM for the 900 for $10M dollars. That IBM mark of approval is always a sign that a company is ready to play in an enterprise market. And enterprises increasingly wanted to keep executives just a quick two-way page away. But everyone knew there was a technology convergence on the way. They worked with Ericsson to further the technology and over the next few years competed with SkyTel in the interactive pager market.

Enter The Blackberry They knew there was something new coming. Just as the founders know something is coming in Quantum Computing and run a fund for that now. They hired a marketing firm called Lexicon Branding to come up with a name and after they saw the keys on the now-iconic keyboard, the marketing firm suggested BlackBerry. They’d done the research and development and they thought they had a product that was special. So they released the first BlackBerry 850 in Munich in 1999. But those were still using radio networks and more specifically the DataTAC network.

The age of mobility was imminent, although we didn’t call it that yet. Handspring and Palm each went public in 2000. 

In 2000, Research In Motion brought its first cellular phone product in the BlackBerry 957, with push email and internet capability. But then came the dot com bubble. Some thought the Internet might have been a fad and in fact might disappear. But instead the world was actually ready for that mobile convergence. Part of that was developing a great operating system for the time when they released the BlackBerry OS the year before. And in 2000 the BlackBerry was named Product of the Year by InfoWorld. 

The new devices took the market by storm and shattered the previous personal information manager market, with shares of that Palm company dropping by over 90% and Palm OS being setup as it’s own corporation within a couple of years. People were increasingly glued to their email. While the BlackBerry could do web browsing and faxing over the internet, it was really the integrated email access, phone, and text messaging platform that companies like General Magic had been working on as far back as the early 1990s.

The Rise of the BlackBerry The BlackBerry was finally the breakthrough mobile product everyone had been expecting and waiting for. Enterprise-level security, integration with business email like Microsoft’s Exchange Server, a QWERTY keyboard that most had grown accustomed to, the option to use a stylus, and a simple menu made the product an instant smash success. And by instant we mean after five years of research and development and a massive financial investment.

The Palm owned the PDA market. But the VII cost $599 and the BlackBerry cost $399 at the time (which was far less than the $675 Inter@ctive Pager had cost in the 1990s). The Palm also let us know when we had new messages using the emerging concept of push notifications. 2000 had seen the second version of the BlackBerry OS and their AOL Mobile Communicator had helped them spread the message that the wealthy could have access to their data any time. But by 2001 other carriers were signing on to support devices and BlackBerry was selling bigger and bigger contracts. 5,000 devices, 50,000 devices, 100,000 devices. And a company called Kasten Chase stepped in to develop a secure wireless interface to the Defense Messaging System in the US, which opened up another potential two million people in the defense industry

They expanded the service to cover more and more geographies in 2001 and revenues doubled, jumping to 164,000 subscribers by the end of the year. That’s when they added wireless downloads so could access all those MIME attachments in email and display them. Finally, reading PDFs on a phone with the help of GoAmerica Communications! And somehow they won a patent for the idea that a single email address could be used on both a mobile device and a desktop. I guess the patent office didn’t understand why IMAP  was invented by Mark Crispin at Stanford in the 80s, or why Exchange allowed multiple devices access to the same mailbox.

They kept inking contracts with other companies. AT&T added the BlackBerry in 2002 in the era of GSM. The 5810 was the first truly convergent BlackBerry that offered email and a phone in one device with seamless SMS communications. It shipped in the US and the 5820 in Europe and Cingular Wireless jumped on board in the US and Deutsche Telekom in Germany, as well as Vivendi in France, Telecom Italia in Italy, etc. The devices had inched back up to around $500 with service fees ranging from $40 to $100 plus pretty limited data plans. The Tree came out that year but while it was cool and provided a familiar interface to the legions of Palm users, it was clunky and had less options for securing communications. The NSA signed on and by the end of the year they were a truly global operation, raking in revenues of nearly $300 million. 

The Buying Torndado They added web-based application in 2003, as well as network printing. They moved to a Java-based interface and added the 6500 series, adding a walkie-talkie function. But that 6200 series at around $200 turned out to be huge. This is when they went into that thing a lot of companies do - they started suing companies like Good and Handspring for infringing on patents they probably never should have been awarded. They eventually lost the cases and paid out tens of millions of dollars in damages. More importantly they took their eyes off innovating, a common mistake in the history of computing companies.

Yet there were innovations. They released Blackberry Enterprise Server in 2004 then bolted on connectors to Exchange, Lotus Domino, and allowed for interfacing with XML-based APIs in popular enterprise toolchains of the day. They also later added support for GroupWise. That was one of the last solutions that worked with symmetric key cryptography I can remember using and initially required the devices be cradled to get the necessary keys to secure communications, which then worked over Triple-DES, common at the time. One thing we never liked was that messages did end up living at Research in Motion, even if encrypted at the time. This is one aspect that future types of push communications would resolve. And Microsoft Exchange’s ActiveSync. 

By 2005 there were CVEs filed for BlackBerry Enterprise Server, racking up 17 in the six years that product shipped up to 5.0 in 2010 before becoming BES 10 and much later Blackberry Enterprise Mobility Management, a cross-platform mobile device management solution. Those BES 4 and 5 support contracts, or T-Support, could cost hundreds of dollars per incident. Microsoft had Windows Mobile clients out that integrated pretty seamlessly with Exchange. But people loved their Blackberries.

Other device manufacturers experimented with different modes of interactivity. Microsoft made APIs for pens and keyboards that flipped open. BlackBerry added a trackball in 2006, that was always kind of clunky. Nokia, Ericsson, Motorola, and others were experimenting with new ways to navigate devices, but people were used to menus and even styluses. And they seemed to prefer a look and feel that seemed like what they used for the menuing control systems on HVAC controls, video games, and even the iPod. 

The Eye Of The Storm A new paradigm was on the way. Apple's iPhone was released in 2007 and Google's Android OS in 2008. By then the BlackBerry Pearl was shipping and it was clear which devices were better.

No one saw the two biggest threats coming. Apple was a consumer company. They were slow to add ActiveSync policies, which many thought would be the corporate answer to mobile management as group policies in Active Directory had become for desktops. Apple  and Google were slow to take the market, as BlackBerry continued to dominate the smartphone industry well into 2010, especially once then-president Barack Obama strong-armed the NSA into allowing him to use a special version of the BlackBerry 8830 World Edition for official communiques. Other world leaders followed suit, as did the leaders of global companies that had previously been luddites when it came to constantly being online. Even Eric Schmidt, then chairman of google loved his Crackberry in 2013, 5 years after the arrival of Android.

Looking back, we can see a steady rise in iPhone sales up to the iPhone 4, released in 2010. Many still said they loved the keyboard on their BlackBerries. Organizations had built BES into their networks and had policies dating back to NIST STIGs. Research in Motion owned the enterprise and held over half the US market and a fifth of the global market. That peaked in 2011.

BlackBerry put mobility on the map. But companies like AirWatch, founded in 2003 and  MobileIron, founded in 2007, had risen to take a cross-platform approach to the device management aspect of mobile devices. We call them Unified Endpoint Protection products today and companies could suddenly support BlackBerry, Windows Mobile, and iPhones from a single console. Over 50 million Blackberries were being sold a year and the stock was soaring at over $230 a share. 

Today, they hold no market share and their stock performance shows it. Even though they’ve pivoted to more of a device management company, given their decades of experience working with some of the biggest and most secure companies and governments in the world.

The Fall Of The BlackBerry The iPhone was beautiful. It had amazing graphics and a full touch screen. It was the very symbol of innovation. The rising tide of the App Store also made it a developers playground (no pun intended). It was more expensive than the Blackberry, but while they didn’t cater to the enterprise, they wedged their way in there with first executives and then anyone. Initially because of ActiveSync, which had come along in 1996 mostly to support Windows Mobile, but by Exchange Server 2003 SP 2 could do almost anything Outlook could do - provided software developers like Apple could make the clients work.

So by 2011, Exchange clients could automatically locate a server based on an email address (or more to the point based on DNS records for the domain) and work just as webmail, which was open in almost every IIS implementation that worked with Exchange. And Office365 was released in 2011, paving the way to move from on-prem Exchange to what we now call “the cloud.” And Google Mail had been around for 7 years by then and people were putting it on the BlackBerry as well, blending home and office accounts on the same devices at times. In fact, Google licensed Exchange ActiveSync, or EAS in 2009 so support for Gmail was showing up on a variety of devices.

BlackBerry had everything companies wanted. But people slowly moved to that new iPhone. Or Androids when decent models of phones started shipping with the OS on them. BlackBerry stuck by that keyboard, even though it was clear that people wanted full touchscreens. The BlackBerry Bold came out in 2009. BlackBerry had not just doubled down with the keyboard instead of full touchscreen, but they tripled down on it.

They had released the Storm in 2008 and then the Storm in 2009 but they just had a different kind of customer. Albeit one that was slowly starting to retire. This is the hard thing about being in the buying tornado. We’re so busy transacting that we can’t think ahead to staying in the eye that we don’t see how the world is changing outside of it. 

As we saw with companies like Amdahl and Control Data, when we only focus on big customers and ignore the mass market we leave room for entrants in our industries who have more mass appeal. Since the rise of the independent software market following the IBM anti-trust cases, app developers have been a bellwether of successful platforms. And the iPhone revenue split was appealing to say the least. 

Sales fell off fast. By 2012, the BlackBerry represented less than 6 percent of smartphones sold and by the start of 2013 that number dropped in half, falling to less than 1 percent in 2014. That’s when the White House tested replacements for the Blackberry. There was a small bump in sales when they finally released a product that had competitive specs to the iPhone, but it was shortly lived. The Crackberry craze was officially over. 

BlackBerry shot into the mainstream and brought the smartphone with them. They made the devices secure and work seamlessly in corporate environments and for those who could pay money to run BES or BIS. They proved the market and then got stuck in the Innovator’s Dilemna. They became all about features that big customers wanted and needed. And so they missed the personal part of personal computing.

Apple, as they did with the PC and then graphical user interfaces saw a successful technology and made people salivate over it. They saw how Windows had built a better sandbox for developers and built the best app delivery mechanism the world has seen to date. Google followed suit and managed to take a much larger piece of the market with more competitive pricing. 

There is so much we didn’t discuss, like the short-lived Playbook tablet from BlackBerry. Or the Priv. Because for the most part, they a device management solution today. The founders are long gone, investing in the next wave of technology: Quantum Computing. The new face of BlackBerry is chasing device management, following adjacencies into security and dabbling in IoT for healthcare and finance. Big ticket types of buys that include red teaming to automotive management to XDR. Maybe their future is in the convergence of post-quantum security, or maybe we’ll see their $5.5B market cap get tasty enough for one of those billionaires who really, really, really wants their chicklet keyboard back. Who knows but part of the fun of this is it’s a living history.

Imagine a game that begins with a printout that reads:

You are standing at the end of a road before a small brick building. Around you is a forest. A small stream flows out of the building and down a gully. In the distance there is a tall gleaming white tower.

Now imagine typing some information into a teletype and then reading the next printout. And then another. A trail of paper lists your every move. This is interactive gaming in the 1970s. Later versions had a monitor so a screen could just show a cursor and the player needed to know what to type. Type N and hit enter and the player travels north. “Search” doesn’t work but “look” does. “Take water” works as does “Drink water” but it takes hours to find dwarves and dragons and figure out how to battle or escape. This is one of the earliest games we played and it was marvelous. The game was called Colossal Cave Adventure and it was one of the first conversational adventure games. Many came after it in the 70s and 80s, in an era before good graphics were feasible. But the imagination was strong. 

The Oregon Trail was written before it, in 1971 and Trek73 came in 1973, both written for HP minicomputers. Dungeon was written in 1975 for a PDP-10. The author, Don Daglow, went on the work on games like Utopia and Neverwinter Nights Another game called Dungeon showed up in 1975 as well, on the PLATO network at the University of Illinois Champagne-Urbana. As the computer monitor spread, so spread games.

William Crowther got his degree in physics at MIT and then went to work at Bolt Baranek and Newman during the early days of the ARPANET. He was on the IMP team, or the people who developed the Interface Message Processor, the first nodes of the packet switching ARPANET, the ancestor of the Internet. They were long hours, but when he wasn’t working, he and his wife Pat explored caves. She was a programmer as well. Or he played the new Dungeons & Dragons game that was popular with other programmers.

The two got divorced in 1975 and like many suddenly single fathers he searched for something for his daughters to do when they were at the house. Crowther combined exploring caves, Dungeons & Dragons, and FORTRAN to get Colossal Cave Adventure, often just called Adventure. And since he worked on the ARPANET, the game found its way out onto the growing computer network. Crowther moved to Palo Alto and went to work for Xerox PARC in 1976 before going back to BBN and eventually retiring from Cisco.

Crowther loosely based the game mechanics on the ELIZA natural language processing work done by Joseph Weizenbaum at the MIT Artificial Intelligence Laboratory in the 1960s. That had been a project to show how computers could be shown to understand text provided to computers. It was most notably used in tests to have a computer provide therapy sessions. And writing software for the kids or gaming can be therapeutic as well. As can replaying happier times. 

Crowther explored Mammoth Cave National Park in Kentucky in the early 1970s. The characters in the game follow along his notes about the caves, exploring the area around it using natural language while the computer looked for commands in what was entered. It took about 700 lines to do the original Fortran code for the PDP-10 he had at his disposal at BBN. When he was done he went off on vacation, and the game spread.

Programmers in that era just shared code. Source needed to be recompiled for different computers, so they had to. Another programmer was Don Woods, who also used a PDP-10. He went to Princeton in the 1970s and was working at the Stanford AI Lab, or SAIL, at the time. He came across the game and asked Crowther if it would be OK to add a few features and did. His version got distributed through DECUS, or the Digital Equipment Computer Users Society. A lot of people went there for software at the time. The game was up to 3,000 lines of code when it left Woods.

The adventurer could now enter the mysterious cave in search of the hidden treasures. The concept of the computer as a narrator began with Collosal Cave Adventure and is now widely used. Although we now have vast scenery rendered and can point and click where we want to go so don’t need to type commands as often. The interpreter looked for commands like “move”, “interact” with other characters, “get” items for the inventory, etc. Woods went further and added more words and the ability to interpret punctuation as well. He also added over a thousand lines of text used to identify and describe the 40 locations. Woods continued to update that game until the mid-1990s.

James Gillogly of RAND ported the code to C so it would run on the newer Unix architecture in 1977  and it’s still part of many a BSD distribution. Microsoft published a version of Adventure in 1979 that was distributed for the Apple II and TRS-80 and followed that up in 1981 with a version for Microsoft DOS or MS-DOS. Adventure was now a commercial product. Kevin Black wrote a version for IBM PCs. Peter Gerrard ported it to Amiga

Bob Supnik rose to a Vice President at Digital Equipment, not because he ported the game, but it didn’t hurt. And throughout the 1980s, the game spread to other devices as well. Peter Gerrard implemented the version for the Tandy 1000. The Original Adventure was a version that came out of Aventuras AD in Spain. They gave it one of the biggest updates of all. Colossal Cave Adventure was never forgotten, even though it was Zork was replaced. Zork came along in 1977 and Adventureland in 1979.

Ken and Roberta Williams played the game in 1979. Ken had bounced around the computer industry for awhile and had a teletype terminal at home when he came across Colossal Cave Adventure in 1979. The two became transfixed and opened their own company to make the game they released the next year called Mystery House. And the text adventure genre moved to a new level when they sold 15,000 copies and it became the first hit. Rogue, and others followed, increasingly interactive, until fully immersive graphical games replaced the adventure genre in general. That process began when Warren Robinett of Atari created the 1980 game, Adventure. 

Robinett saw Colossal Cave Adventure when he visited the Stanford Artificial Intelligence Laboratory in 1977. He was inspired into a life of programming by a programming professor he had in college named Ken Thompson while he was on sabbatical from Bell Labs. That’s where Thompason, with Dennis Ritchie and one of the most amazing teams of programmers ever assembled, gave the world Unix and the the C programming language at Bell Labs. Adventure game went on to sell over a million copies and the genre of fantasy action-adventure games moved from text to video.