Where are the New Technologies? The 2010s was a terrible decade for new technologies
Which technologies were successfully commercialized in each decade, going back to the 1880s? Successful is an important yet vague word meaning that the technology should have added value in the relevant decade, it should have significantly diffused during the decade of introduction, and the suppliers should have become profitable. I made this list by looking at a variety of sources that describe the most important technologies commercialized in various decades, much of which is consistent with Robert Gordon’s book, The Rise and Fall of American Growth. Looking at the technologies commercialized in past decades (See table), this article, the 18th in this series on startups and technologies, argues that much fewer were successfully commercialized in the 2010s than in previous decades. This article first summarizes the technologies listed in the below tables, the trends they suggest, and then discuss the 2010s.
We begin with the 1880s because this was the decade in which two of the most important innovations, electricity and the telephone were first successfully commercialized. Electricity played a role in many of the technologies commercialized in this and subsequent decades including the elevator, light-rail systems, air conditioners, washing machines, refrigerators, commercial radio, and many others. A second group of technologies were mechanical in nature including cash registers, vending machines, bicycles, zippers, bulldozers. A third involved engines including the internal combustion, gas turbine, automobile, commercial aviation, and jet engine. A fourth were new materials such as polymers, nylon, Velcro, and Kevlar. A fifth involved imaging such as cameras, motion pictures, film, and television for consumers and X-rays, ultrasound, magnetic resonance imaging, and computer tomography for medical. Other medical technologies include penicillin, DNA sequencers, and biotech. A sixth were semiconductors and information technology which define the largest and most recent group of technologies, from semiconductors, magnetic storage, and lasers to computers, mobile phones, and the Internet.
Many of these have run their course and thus few new engines and materials are coming out anymore, and we take mechanical and electrical technologies for granted. This is a big reason why basic research had declined in automobile and other mechanical engineering companies by the mid- to late-20th century and more recently in aircraft and chemical companies. Similar things are beginning to occur with information technologies as the most recent startups such as Pinterest, Instagram, and even Facebook seem simplistic when compared to the development of transistors, lasers, and magnetic storage in decades past, even as we hope for driverless vehicles and artificial intelligence.
We now turn to the dismal 2010s, which follow the mediocre 2000s. I believe there are only three new technologies that can compare to the previous decades, organic-light emitting diode (OLED) displays, solar cells, and Big Data/AI. OLED’s market was valued at $32 billion in 2019[i], mostly for smart phone displays and televisions, the global solar energy market was $52.5 billion in 2018[ii], most of which was silicon solar cells, and Big Data and AI were $49 billion[iii] and $14.7 billion[iv] respectively. From the standpoint of American suppliers, the first two are of less interest than the others because the most successful suppliers are foreign ones, Korean ones for OLEDS and Chinese ones for solar cells.
Big Data and AI are even more controversial. Cathy O’Neil’s 2016 book Weapons of Math Destruction describes a dystopian world in which human resources try to hire the same people they already have and prevent hourly workers from achieving 30 hours to avoid paying benefits, while the judicial system sets high bail for suspects whose neighbors have police records, and companies target low-self-esteem people with marketing campaigns (Robert Gordon is also dismissive of Big Data in The Rise and Fall of American Growth). Outside of news, e-commerce, and advertising, AI has not done much better, as described in Chapter 8, and reported by news sites almost daily in 2020. I am still looking for an application for which productivity has been substantially enhanced by Big Data or AI.
I almost included electric vehicles in the table, but with a mere 1.44% market share in the U.S. 11 years after Tesla introduced its first EV in 2008, one cannot define EVs as successful. I am also doubtful that EVs will quickly diffuse and not just because of the coronavirus. Fitting the 1.44% figure to a logistics curve suggests they will not reach 50% until 2035, and this assumes no impact from the current economic contraction. This make their rate of diffusion much faster than that of solar cells, a technology that diffused very slowly until the 2010s. People forget that they were first used in satellites during the 1950s, and then diffused slowly in remote locations and finally in homes and businesses beginning in the 2000s.
Many will argue that smart phones, 4G, and the sharing economy should be included in the 2010s, but I don’t include them because Apple introduced the first smart phone in 2007, the app store in 2008 and some argue (including myself) Japanese and Korean companies did so in the early 2000s. Big improvements have not been made, except perhaps a complete move to OLEDs A successful folding phones would qualify as an important new technology once they succeed (likely in the 2020s). 4G isn’t included because neither are 2G and 3G services. And the sharing economy is still not profitable as is discussed in other articles.
I almost included electric vehicles in the table, but with a mere 1.44% market share in the U.S. 11 years after Tesla introduced its first EV in 2008, one cannot define EVs as successful. I am also doubtful that EVs will quickly diffuse and not just because of the coronavirus. Fitting the 1.44% figure to a logistics curve suggests they will not reach 50% until 2035, and this assumes no impact from the current contraction. This make their rate of diffusion much faster than that of solar cells, a technology that diffused very slowly until the 2010s. People forget that they were first used in satellites during the 1950s, and then diffused slowly in power locations and finally in homes and businesses beginning in the 2000s.
What about tablet computers, commercial drones, blockchain, wearables, virtual reality, and augmented reality, technologies that received a lot of attention throughout the 2010s. Their rates of diffusion have also been slow if non-existent. Tablet computers did achieve more than $10 billion in sales in the early 2010s but then their diffusion stopped, and they remain a niche product[v] along the lines of PDAs (personal digital assistants). Commercial drones and blockchain are also still niches with a $5.8 billion market in 2018[vi] and a $2.2 billion market in 2019[vii] respectively. Even Britain’s blockchain association claiming only 2% of projects show evidence of a positive outcome[viii]. Sales of Augmented reality devices are only expected to reach 200,000 in 2020[ix] while those of virtual reality reached $7.9 Billion in 2018 or more than 10 times the market for AR[x]. And a long list of Google’s projects have failed, none have yet to succeed[xi].
Although the Apple Watch is a widely used wearable, it merely monitors and analyses our heart rates, important, but more a status symbol than a functional breakthrough. And Apple accessories such as ear buds may be profitable[xii], but they are not wearables in the sense that watches or AR are. AR’s market in 2018 was less than $1 billion or about 1/10 that of VR[xiii], which was $7.9 billion in 2018.
Some will argue that smart phones, 4G and IoT should be included in the 2010s, but I don’t include them because Apple introduced the first smart phone in 2007, the app store in 2008 and some argue (including myself) Japanese and Korean companies did so in the early 2000s. Big improvements have not been made, except perhaps a complete move to OLEDs, and successful folding phones would qualify as an important new technology once they succeed (likely in the 2020s). 4G isn’t included because neither are 2G and 3G services.
For IoT, Ericsson and Cisco predicted there would be 50 billion connected devices by 2019, yet there were only 9 billion and most of these were smart phones, followed by manufacturing equipment. Other applications such as Amazon Kindle reporting on what you read or the much-hyped monitoring of vehicles for insurance purposes have not succeeded anywhere near the extent once predicted. For all these technologies, they are still in their infancy. Perhaps in five or ten years we will look back and say they first succeeded in the 2010s, but none of these technologies can be yet defined as a success.
These results are consistent with my analyses of startups that were presented in earlier Medium articles. One analysis done in March 2020 found that only 6 of 45 ex-Unicorns were profitable in 2019[xiv]. Subsequent analyses found that ex-Unicorns who did later IPOs were also not profitable in 2019, nor were foreign or Chinese ones that have released figures[xv]. These unprofitable startups dominate fintech (14 of 18), consumer Internet (20 of 21), business software (26 of 27), and deep tech (0 of 12)[xvi]. Many of these articles have argued that the reason for the lack of profitable and top 100 market capitalized startups is the lack of breakthrough technologies[xvii], which is also demonstrated in this article.
[xvii] https://medium.com/@jeffreyleefunk/why-are-todays-startup-unicorns-doing-worse-than-those-of-the-past-1c8ece718ab0 14 https://medium.com/@jeffreyleefunk/the-illogic-of-the-data-wheel-eb5b7cb7c259https://medium.com/@jeffreyleefunk/deep-tech-unicorn-startups-are-unprofitable-why-8f65dc7f2a8d