To The Future
It’s 1999, the new, disruptive, and charged technological era of the internet, an era where you could easily raise money for the most bizarre technology scheme, --- someone told you that Apple, Amazon, Google, and Microsoft were going to dominate technology over the next 20 plus years. Politely --- you would have dismissed their musings.
In 1997 Apple was close to filing for bankruptcy, in 1998 Google was a small internet search engine, in 1996 Amazon began selling books online, and Microsoft was stuck in a rut for years largely due to increased competition and failure to adapt to change --- however, with a potential in the development of software that can be manipulated by the user to create eventually lifted their opportunities. Understandably, during this period, more attractive investment sources dominated the marketplace.
Our past is a lesson to the future. Yet, amidst the whirlwind of technological disruption, our ability to foresee outcomes beyond a year remains severely challenged. We are lousy at making long term predictions. It’s inevitable that we will experience a boom-and-bust scenario in AI --- as we have with any new technological innovation and disruption in the past.
The comparison between AI disruption and the internet disruption of the 1990s reveals both similarities and differences in terms of scale, impact, and the sectors affected. Here’s a breakdown:
Similarities
1. Transformational Impact: Both AI and the internet represent foundational technological shifts that have the potential to transform multiple sectors. Just as the internet revolutionized communication, information sharing, and commerce, AI is transforming decision-making processes, automation, and personalization across industries.
2. Economic Growth: Both technologies have contributed to significant economic growth and productivity gains. The internet spawned entirely new business models and companies (e.g., Amazon, Google), while AI is expected to create substantial economic value by enhancing productivity and fostering new innovations.
3. Global Reach: Both the internet and AI technologies have a global reach, affecting economies, societies, and cultures worldwide. They transcend geographical boundaries, enabling global collaboration and competition.
Differences
1. Scope and Speed of Adoption: The internet was about connectivity and information exchange, leading to a gradual transformation as infrastructure, access, and usage expanded. AI’s impact, on the other hand, is about enhancing human capabilities and automating processes, which can be applied rapidly across diverse sectors once the technology reaches a viable state. The speed of AI adoption in certain industries has been remarkably fast, partly because the internet has laid the groundwork for rapid dissemination of technological advancements.
2. Economic and Employment Displacement: While the internet did disrupt traditional industries (e.g., print media), AI’s potential for automation extends to a broader range of jobs, including those requiring cognitive skills. This presents both opportunities for new job creation in AI-driven sectors and challenges in terms of retraining and employment displacement.
3. Data Privacy and Ethical Considerations: While the internet raised concerns about data privacy and security, AI amplifies these concerns due to its ability to analyze and act upon vast amounts of data. The ethical implications of AI, including bias, decision-making transparency, and accountability, present new challenges that were not as prominent with the initial growth of the internet.
Regulatory and Societal Impact: The internet’s growth initially outpaced regulatory responses, leading to a “catch-up” phase in terms of governance and regulation. With AI, there’s a more proactive approach towards understanding and mitigating its societal impacts, including discussions on ethics, regulation, and the need for equitable access early in its development phase. Consider a recent sample:
“BRUSSELS (Reuters) - Alphabet unit Google enjoys a competitive edge in generative artificial intelligence due to its trove of data and AI-optimized chips, Microsoft has told EU antitrust regulators, underscoring the rivalry between the two tech giants. Today, only one company - Google - is vertically integrated in a manner that provides it with strength and independence at every AI layer from chips to a thriving mobile app store. Everyone else must rely on partnerships to innovate and compete," Microsoft said in its report to the Commission.”
In summary, while both AI and the internet have been transformational, the nature of their impacts, the speed of adoption, and the challenges they present differ. AI’s disruption is building upon the digital infrastructure and global connectivity established by the internet, accelerating its potential to transform industries and societies in unique and profound ways.
It is reasonable to assume that Apple, Amazon, Google, and Microsoft will continue to do well considering – financial resources, data access, talent acquisition, ecosystem, and infrastructure. Yet equally their sheer size can be their Achille heel.
However, the dominance of these giants does not preclude the emergence and success of newcomers. The tech industry has a history of disruptive innovation often driven by startups and new entrants. Factors that could favor newcomers include:
• Niche Specialization: Newcomers can focus on specific niches or emerging areas within AI, where larger players might not have focused their efforts.
• Innovation and Agility: Startups often have the agility to innovate and adapt quickly, unencumbered by the bureaucracy that can slow down larger organizations.
• Partnerships and Collaborations: By forming strategic partnerships, newcomers can leverage the strengths of established players while bringing fresh perspectives and innovations to the table.
Given these considerations, while the probability is high that companies like Apple, Amazon, Google, and Microsoft will continue to dominate the AI space due to their significant advantages, the dynamic and rapidly evolving nature of AI technology also provides substantial opportunities for newcomers to disrupt and carve out their own spaces. The tech landscape is characterized by constant and dynamic change, and history has shown that innovation can shift the balance of power unexpectedly. As I previously pointed out, except perhaps for Microsoft, companies like Apple, Amazon, and Google faced challenges in the 1990s and were not considered strong contenders to dominate the marketplace.
A sample of possible candidates that show, not only promise, but could also pose considerable disruptive threat that might not compete across all fronts but can impact significant areas of their specific niche dominance in their most profitable segments:
Healthcare AI
• DeepMind Technologies (a subsidiary of Alphabet yet operates with a degree of independence and has made significant advances in health-related AI research).
• Tempus Labs: Specializes in applying AI to precision medicine, particularly in oncology, by analyzing clinical and molecular data.
AI in Autonomous Vehicles
• Waymo: While a subsidiary of Alphabet, Waymo is noteworthy for its leading position in autonomous driving technology and could represent internal disruption.
• Cruise Automation: Backed by General Motors, working on self-driving technology with the potential to disrupt traditional vehicle and tech companies alike.
AI in Enterprise and Cloud Services
• Palantir Technologies: Focuses on big data analytics, offering platforms that could compete in the data analysis and AI-driven decision-making space.
• Databricks: Offers a unified analytics platform powered by AI and machine learning, targeting data science and machine learning operations at scale.
AI in Consumer Applications and Hardware
• OpenAI: Known for GPT (Generative Pre-trained Transformer) models, OpenAI has partnerships and products that directly compete with services offered by tech giants.
• NVIDIA: While traditionally a GPU manufacturer, NVIDIA has increasingly positioned itself as a key player in providing hardware and software for AI and deep learning applications.
AI in Robotics and Automation
• Boston Dynamics: Specializes in advanced robotics, developing machines that can navigate real-world environments with animal-like agility.
• UiPath: Focuses on Robotic Process Automation (RPA), automating routine tasks with AI, showing how automation can reshape industries.
AI in Finance and Insurance
• Lemonade: Uses AI and machine learning to disrupt traditional insurance models, offering automated insurance purchasing and claims processing.
• Stripe: While primarily a payment processing platform, Stripe uses AI extensively for fraud detection and risk management, showing how AI can be applied to financial services.
Niche AI Innovations
• Graphcore: Designs and manufactures processors specifically for AI and machine learning applications, potentially challenging the hardware dominance of companies like NVIDIA and Intel.
• Quantum Computing Companies (e.g., D-Wave Systems, Rigetti Computing): Working on quantum computing solutions that could eventually revolutionize AI computation power and efficiency
When the world moves from sailing ships to steamships? --- Quantum Computing.
Consider a company that lost to Microsoft in the 1980s, missing a huge opportunity, largely to management beliefs and hubris at the time, may perhaps be on another trajectory today? Last December IBM showed a new quantum computing chip and machine that it hopes will serve as the building blocks of much larger systems. Researchers around the world are trying to perfect quantum computing, which relies on quantum mechanics to reach computing speeds far faster than classical silicon-based computers. Besides IBM --- Microsoft, Google, and China’s Biadu, along with startups and nation states, are all racing to develop quantum machines. Another way of looking at quantum computing --- theoretically perform calculations in seconds that might take the most powerful classical supercomputers, we use today, thousands of years. Today’s early states of quantum computing are predominantly used for research and development. Will IBM dominate?
Microchip technology, known as integrated circuits or chips, has been a driving force behind modern technology’s rapid progress. There’s an ongoing race to increase the capacity and speed of microprocessors -- more specifically quantum computing. This next phase will better analyze complicated molecular interactions in drug discovery, leading to the invention of new medications and speeding up the discovery process, help with optimization difficulties like supply chain management and logistics, locate optimal solutions more quickly – resulting in significant cost savings and increased efficiency, etc. A disruptive process ushering in a new and more disruptive period when compared to the internet.
Often there is an implied assumption that pioneers, and pioneering companies, have --- one leg up on the competition. However, the relentless pace of technological advancement and intense competition means that early innovations, while historically significant, are no guarantee of perpetual dominance in a dynamic industry. Take Texas Instruments and Fairchild Semiconductor, pioneers in the inventions of the integrated circuit, laying the foundational stones of the digital age. While both companies initially reaped significant benefits from their groundbreaking innovations, including patent royalties and market leadership, their long-term advantages were tempered by the semiconductor industry’s highly competitive and rapidly evolving nature.
Monitoring the swift and ever-changing landscape of technology is like watching a river’s course, constantly shifting, and flowing, demanding vigilance to navigate its unpredictable waters.
John
March 2024