What Spaceflight and AI Show Us About the Tech Market
We are consumers of technological advancements, we are the users of scientific discovery-backed products, and we are the public that decides which things to invest our pocket money in. The public is witnessing more growth in the market than ever, with the ease of online purchasing, consumers are giving helping hands to certain big or small companies in competition. Walking at the front ends of research and development, big companies are leading the market and business models of many startups, often shaping their new waves and their directions as well. This huge phenomenon brings out the questions of, what is happening in the fields of technology? How are the products designed? How do private enterprises function?
Certain technological advancements are often broadcasted by news channels and radios and often tend to receive a wide audience. These include spaceflight, architecture, premium consumer items, medical innovation, etc. For example, written by big news companies was the launch of NASA/SpaceX spacecraft, a mission transporting American astronauts to the ISS that was carried out a month ago. Space and air-related innovation are often seen as the flagship of the performance of a country's research & development. In this case, having a collaboration between a private company, representing the private market that America has long endorsed, and a national agency that led the world in space discovery was truly worthy of the vast attention of the news.
Spaceflight and Privatization
Spaceflight came into the world’s spotlight half a century ago, and almost immediately the public was fascinated by this new piece of technology that allowed humans to break free of Earth’s barrier. Some of these theoretical and practical breakthroughs were led by Konstantin Tsiolkovsky and Robert H. Goddard, who were both from the Soviet Union. They were the first explorers of space, launching the first satellite and the first humans into orbit. Other countries were captivated by the idea of going to space, and nowadays the competition aspect of the 20th century’s spaceflight development is referred to as the “Space Race”.
Following the path of the Soviet Union, the United States also poured money and effort into spaceflight programs, with the most famous of which being named the “Apollo Program”, the third human spaceflight program carried out by NASA. The mission’s significance lies within the length of its journey: Apollo 8 was the first human spaceflight to leave earth orbit and orbit the Moon on December 21, 1968, and Apollo 10 was the first crewed mission carrying Neil Armstrong and Buzz Aldrin to set mankind’s first footprint on the Moon, on July 11, 1979.
What does SpaceX mean in the advancement timeline of spaceflight technology? SpaceX marks the beginning of privatizing space exploration. Maintaining a company that enables private and commercial spaceflight is very difficult, since existing space programs in the United States are almost all overseen by NASA, including the mission that took place a month ago, which was a collaboration between NASA and SpaceX. Finding the weak points in an existing system and improving upon it is exactly what SpaceX did. From shuttle design to recyclable rockets, the early actions of SpaceX to compete against NASA’s national monopoly were unintentional. Instead, they hoped to establish a private space company as a dominant role in the market, when the market didn’t really have any direct competition. SpaceX has sought to make improvements rather than competition. Because unlike other missions carried out by NASA, SpaceX’s direction has been moving towards a recyclable chain of rockets that could drastically reduce the price of each mission.
Carrying out missions that reflect national pride, NASA has received enough funding and support for the search of the unknown and the new. However, they are not putting as much attention into internal savings on cost. This is how SpaceX, without standing in the shadow of NASA, secured its position on the market that originally opened for governments, and commenced the move of privatization.
Artificial Intelligence and Startup Acquisitions
There are other fields of research that many companies have poured their assets into, in the hopes that they will ultimately be made into consumer items. For example, the use of artificial intelligence was first centered towards defense to recognize secret codes, but after demonstrating its capabilities, it was expanded into many aspects including voice recognition, image recognition, and other strategic algorithms. As time went on, these progressed into what is now modern smart-assistants, video editors, grammar tools, even board game players (DeepMind/Google’s AlphaGo made a big title when it defeated Lee Sedol in its five-game match of Go, demonstrating the amazing capabilities of artificial intelligence in strategic games).
The breadth of what AI could do was incomprehensible, and they were just scratching the surface. During the 1950s, computers were incapable of performing high-volume tasks, unable to store information, and lacked regulation of their components. At the time, AI was simply a fantasy, usually characterized by novels with phrases like “robots” and “intelligent metal humans that could walk”. A good example would be that of the tin man from the Wizard of Oz: he could walk and talk, he could perform tasks that humans could, but he “didn’t have a heart”. Personally, I assume that the “heart” in the novel, or the general consensus that robots lacked “heart”, represented the popular opinion at the time that robots would never be able to perceive or process human feelings and emotions, nor the idea of consciousness, which seemed to be only abstract ideas in their minds.
Throughout the flourishing of computer science, famous individuals such as Alan Turing, John McCarthy, Allen Newell, Paul Werbos, contributed their studies into the AI journey, establishing milestones in the form of algorithms, theories, and AI system design. The broad topic of AI gradually branched into machine learning, neural network, natural language processing, and many more fields. These were all powered by heavy computer science, mathematical research, and experiments. For example, it was discovered that especially in neural networks (learning frameworks for machines), many types of calculus would be heavily used to “back-propagate”, essentially to analyze errors from the input, bias, and outputs needed.
After a brief decline between the 1970s - 1980s along with some more breakthrough discoveries, more and more projects were carried out by companies and universities. However, they were facing two major problems: the lack of computational power, and the lack of connections between machine code and real-world logic structures. In the 21st century, these problems are still being solved, albeit at a relatively fast pace. Perhaps in the future with even better hardware like quantum computers, there will once again come a time of extraordinary and revolutionary breakthroughs.
It seems like the market of application-based AI is eerily similar to other tech markets, of course with less of a national-level monopoly through entities like NASA, but more industrial monopoly by huge enterprises like Google, Apple, Facebook, Microsoft, etc. This is because of the amount of data entry and the financial capabilities of these companies.
First, data has become one of the most valuable resources in the 21st century. Facebook has been involved in data-related scandals (Cambridge Analytica Data Access, 2018), Google has continually had access to a large majority of the public’s searching data, and Amazon has had access to billions of purchasing data and detailed receipts.
Data analysis is key to training AI algorithms. It is a part of the learning process that machines go through, which if not given, will not function. Unlike huge enterprises, smaller companies don’t have this level of data acquisition.
Second, smaller companies and startups are financially less powerful, often resulting in an acquisition of the company (big companies buying startups), therefore contributing to the size of these already-monopolistic humongous companies. For example, Google has, since 2009, spent almost four billion dollars on acquiring thirty companies in total. Apple has bought eighteen companies, and Microsoft and Facebook have bought twelve. In total, these four companies have spent six-and-a-half billion dollars on just buying startups and small-scale companies. This general trend of a monopolized field has created another barrier that decides whether startups succeed or fail.
In conclusion, whilst the nations of the world are led by governments, technological innovation is led by individual corporations. Although there are so many more intricate details to add about technology and its markets, these two factors are good examples of leading areas in innovation and business. Recognizing the pattern of these two leading industries, we can see the attempts made by huge enterprises to build a monopoly, through strategic investments in new technology, and the acquisition of smaller companies and startups. Although the future of technological markets is unknown, looking at the patterns of present enterprises, it is evident that it grows from both innovation and market strategies.