Introduction to AI’s Growing Presence in Daily Life
Artificial Intelligence (AI) models, such as ChatGPT, Gemini, or Copilot, are increasingly present in the daily activities of many individuals. Today, they serve as alternatives to internet search engines, answering a wide range of questions, generating ideas, providing advice, enhancing writing skills, assisting with tasks and schoolwork, among other functions. For instance, in China, some judges can draft sentences within seconds thanks to DeepSeek.
Historical Perspective and the AI Power Formula
Twenty years ago, if one suggested this was possible, many would have disbelieved it. However, it was indeed feasible back then, albeit with processing times stretching into hundreds of years. Today, thanks to AI’s power, summarized by the formula: AI Power = Algorithm Power x Computing Power, such tasks are accomplished in milliseconds.
Achieving perfectly accurate results might require decades of computation, even for simple requests. Mathematicians and computer scientists discovered that algorithms could be designed to multiply computational power, yielding results in less time while sacrificing minimal precision. For example, each algorithmic improvement could double the power and reduce precision by just 0.1%. While this sounds fantastic, it’s not without its drawbacks.
For AI to be functional, it’s highly likely that algorithms have been amplified thousands of billions of times, leading to a significant reduction in precision, known as “AI hallucinations.” So, has AI reached its computational power limit? The answer is no. We must look at the second part of the formula: computing power.
The Role of Computing Power in AI Advancements
AI’s possibility is attributed to the growth in computing power, driven by Graphics Processing Units (GPUs) developed by Nvidia. These semiconductors are the brains of AI and have become so valuable that Nvidia’s stock value surged from $150 billion at the end of 2019 to $4.3 trillion by mid-2025, marking a 3,000% increase in just six years.
Economic Impact and Competition Among Tech Giants
AI’s economic value is immense, and tech giants are well aware of it. As of now, OpenAI, the creator of ChatGPT, is a privately-held company valued at $500 billion. Microsoft, with a market capitalization of $3.8 trillion, has reaped substantial benefits from its partnership with OpenAI, holding exclusivity to distribute ChatGPT through its cloud platform Azure until 2030. Moreover, Microsoft is developing its own AI called Copilot.
Google, valued at $2.4 trillion in the stock market, is also investing heavily in AI through Gemini. Meta, owner of Facebook and WhatsApp and valued at $1.9 trillion, doesn’t want to fall behind and is aggressively poaching talent from other companies with personal contracts worth hundreds of millions of dollars. This aggressive hiring strategy, reminiscent of sports superstar signings, has disrupted Silicon Valley’s labor structure.
The AI Power Formula: Predicting Future Leaders
The AI power formula is a simple equation that will help determine which competitor will emerge victorious in this race. The best algorithms, those with higher power and lower precision loss, have become today’s most valuable industrial secrets. Countries or companies with the greatest computational capabilities and advanced chips will be the ones to develop the most powerful AI.
Key Questions and Answers
- What is the AI power formula? It’s a simple equation: AI Power = Algorithm Power x Computing Power.
- How has computing power contributed to AI advancements? Computing power, driven by GPUs developed by Nvidia, has significantly increased AI capabilities.
- Why are tech giants investing heavily in AI? Due to its immense economic value, tech giants like Microsoft, Google, and Meta are investing in AI to gain a competitive edge.
- What are “AI hallucinations”? These are significant reductions in precision that occur when algorithms are amplified excessively for faster results.
- How does the AI power formula predict future leaders? It identifies the best algorithms with higher power and lower precision loss, indicating which entities will develop the most powerful AI.
