We'll All Win with A.I.
This wave of innovation won't be like the previous waves of tech innovation.
Over the past 80 years we’ve gone through five major waves of tech innovation, which have cumulatively had an enormous positive impact on the way we do things now. During each wave of innovation there were clear winners that emerged, each of whom had a major impact on the world.
The first wave was the invention of silicon-based transistors over the 1940s and 50s. Transistors (semiconductors) are important components in electronics circuits. A company called Fairchild Semiconductor, started by a group of intelligent engineers, was notably the company that kicked things off. One of the founders of Fairchild was Gordon Moore (proponent of Moore’s law) and from Fairchild, Intel and AMD were born – two important tech companies for the world. The continuous development and improvement in transistors was the invention that allowed for subsequent waves of important tech innovation.
The second wave was the invention of the personal computer (PC) over the 1970s and 80s. The PC allowed productivity levels to improve significantly as more people were able to tackle difficult problems using machines which could analyse and process data faster. The development of the PC then enabled people to solve problems and build things using software. This era gave rise to companies such as Apple and Microsoft.
The third wave was creating the ability for these computers to share information over a vast network, which we call the internet. This wave took its form over the mid-1990s. This allowed the Internet economy to thrive. Internet businesses were created, and through internet expansion the addressable market for other companies became larger, spanning the whole of the internet (i.e., worldwide). This gave rise to powerhouses like Amazon and Google and laid the foundation for other great companies that came a little later, like Facebook (now Meta) and Palantir.
The fourth wave was the invention of the smart phone in the early 2000s. This put access to the internet in your pocket, again allowing companies to scale as they now had the capability to reach their customers at any time, and not just when they were behind a computer. This wave played itself out together with the next wave, which was mobile apps. Mobile apps made it even easier for companies to provide services to their customers, again improving engagement and profitability. The largest profiters from this era were/are Google with Android and Google Play, and Apple with iOS and the App Store.
We are currently in the next wave of important tech innovation, which is the artificial intelligence (AI) era. This era began in the early 2010s and we’ve yet to see the true impact of AI. We’ve also yet to see the definitive winner in this category as we have with the previous tech innovation waves, mainly because this era is only now starting to hit its stride.
The Development of AI
Since 2012, using proprietary data gathered over billions of driving miles, Tesla has introduced and redeveloped various vehicle AI based driving capabilities including Autopilot, Enhanced Autopilot, and Full Self Driving Capability (Beta mode).
In 2012, Alphabet bought a developing AI company called DeepMind. In 2016, one of DeepMind’s projects called AlphaGo beat the world champion of the board game Go. This was a huge breakthrough for AI, because neural network technology (a computer system modelled after the human brain) had reached a level where it was beating humans on a creative field - in a game with more possible moves than there are atoms in the universe.
In 2015, a group of investors including Elon Musk, Reid Hoffman, Amazon Web Services and Y-Combinator founded OpenAI, a company whose mission is to “create AI systems that will benefit humanity”. In 2022 OpenAI released the latest version of their project, called ChatGPT, which allows you to search for information (like entering a search in Google’s search bar), however ChatGPT returns results as a text chat, and allows you to interact back and forth to refine your search and get a better understanding.
Computing capabilities are now at their most powerful level.
What does this mean for the world?
AI will impact every single economic sector. Remember AI is an artificial neural network that works like a human brain. For example, if you read about or study a topic, research it, talk about it with other people and continue to refine your knowledge on the topic, you will end up knowing a decent amount. If you continue to refine your knowledge and practical application on the topic over years, you will become an expert. You have performed data analysis and interpretation to the highest level.
AI works in a similar manner, only orders of magnitude faster. The information that the AI has and is returning to you when you make requests comes from information it was fed from a collection of data stores over many data servers. Therefore, the most highly functional AIs are computer models that can search for/gather data, analyse, search/gather more data, then produce accurate results in the form of analysis reports and predictions, immediately.
The AI Era is Hitting its Stride.
On a smaller scale we interact with AI every day. Some examples are Siri and Alexa, auto spell corrects, grammar suggestions while you write in Microsoft Word, online one-player games like chess and poker, park assist in your car, when a website asks you to “accept cookies,” and really the entirety of Google’s business model is providing AI powered services.
However, these are not the game changing applications for AI. Here are some examples of game changers:
Manufacturing
DataProphet, a South African based company, is providing manufacturers with AI systems that help them recommend fixes and optimisations to avoid future malfunctions of equipment.
Healthcare
Predictive analytics is currently used by the Wyss Institute, where a wearable device was created to help detect early physiological signs of anaphylaxis, and automatically inject epinephrine if necessary.
Another example is DeepMind’s AlphaFold, which has figured out how to create 3D structures of protein molecules, aiding in biological research.
Finance
Kensho Technologies is empowering companies like JP Morgan with predictive analytics tools. These tools can consolidate internal and external data to determine the financial health of the business, and the business’s health vs competitors. Additionally, Kensho provides quantitative tools to predict credit risk and detect fraud.
Supply Chain
InstaDeep is providing AI powered decision making solutions for Logistics companies, empowering these companies with route optimisation, predictive maintenance, inventory management, and demand forecasting.
So, where is the next great company going from?
Because there is currently so much hype about AI, the space will get commoditized very quickly as more businesses fight to compete. Additionally, the broader business environment is giving many other companies, not just the Google’s and Microsoft’s of the world, the opportunity to be the next great.
A few important factors making the tech and broader business environment more friendly:
The cost of energy is going to zero. As the global appetite continues to favour renewable energy, we are seeing the cost of the most popular renewables go down globally. The means that the cost to generate compute power will fall in parallel, making it feasible for startups to run their own systems for AI, and for established companies to integrate more efficient computing systems.
Moore’s Law remains consistent. This is an exponential trend whereby the number of transistors that fit into an integrated circuit doubles every 2 years, meaning tech hardware is becoming more efficient every 2 years and therefore their costs are going down in parallel because demand increases as it becomes more feasible for people to use the technology.
Wright’s law remains consistent. This is a technology cost model that says for every cumulative doubling in production, the cost of production goes down consistently. This happens as production capabilities and know-how improve, the more of that thing is produced.
Moore’s Law and Wrights Law essentially tell us that as technology improves, the cost of adopting or implementing that technology goes down 1) because of improved know-how and 2) because of higher demand and therefore greater competition for supply, meaning suppliers must keep bringing prices down to compete.
Growing private investment interest in AI. A study by the OECD showed that as of 2020, more than 20% of VC investments went to AI focused companies. There is no doubt that this trend will continue, given the current news cycle globally around AI.
Because the factors mentioned above are global, the cost to participate in the AI revolution will come down over time, making it more feasible for economic sectors in developing regions to participate in the AI space. In parallel, the least costly way for developing regions to participate is to incorporate data analysis programs in school curriculums from as young as possible in a person’s life.
The influx of data analysts = an influx of people focused on finding ways to improve the way everything works. We’re all winners at that stage.
For companies, invest in AI… or die.
For investors, learn about AI, put resources to work behind interesting products. There will be more than one winner in AI, perhaps multiple winners for each industry. Google’s AI systems have outperformed peers thanks to the acquisition of DeepMind. Microsoft is allowing OpenAI to leverage Microsoft’s data to improve OpenAI’s product. There are more of these synergies to explore, and the winners in AI in each sector will likely be at the intersection between being able to leverage expertise to produce a dominant AI system, and the startup that can provide that for that company.