The Big Bang of AI
On November 30, 2022, OpenAI launched ChatGPT and thereby triggered an unprecedented technological revolution. Based on the Transformer architecture, this conversational model achieved what decades of research had not: bringing artificial intelligence to millions of people in an intuitive, useful, and surprisingly human way. In a few weeks, it surpassed 100 million users, becoming the fastest-growing application in digital history. ChatGPT demonstrated that generative AI could write, reason, learn, and collaborate, transforming everything from education to programming, creativity, and productivity.
The Technological Cold War and Capital Concentration
The success of ChatGPT unleashed a global race for leadership in artificial intelligence, described by analysts as a "technological cold war." The so-called "Magnificent Seven"—Apple, Microsoft, Google/Alphabet, Amazon, Meta, Broadcom, and Nvidia—concentrate not only the largest market value on the planet but also the most aggressive investments in AI. This concentration of capital has accelerated the development of increasingly powerful, sophisticated, and specialized models, making generative AI the most important growth engine of the digital era.
Market Capitalization: Microsoft and Nvidia, the New Titans of AI
By July 2025, the six major tech companies reached a combined market capitalization of over $13 trillion. Microsoft and Nvidia led this rise, each surpassing $4 trillion in valuation. Microsoft achieved this through its integration of Copilot into Windows, Office, and Teams, and the deployment of AI in its Azure cloud. Nvidia, for its part, established itself as the essential infrastructure provider for AI, with a growth of over 170% in one year. Even ChatGPT debuted in the ranking of most valuable brands, with an estimated value of $43.6 billion.
Microsoft's Strategic Bet: Copilot and Azure
Microsoft's vision dates back to 2019, when it invested $1 billion in OpenAI. In 2023, it doubled down on its bet with another $10 billion, securing exclusive access to the most advanced models. This alliance allowed for the integration of Copilot into its key products, redefining digital productivity. In addition, Azure became the preferred platform for deploying AI solutions, while Bing re-emerged as an intelligent search engine with conversational capabilities. Microsoft not only bet on AI but made it the core of its business strategy.
Google and the Gemini Challenge: Reinventing Search
Google, whose business model largely depends on advertising in its search engine, reacted with urgency to the advance of ChatGPT. Its response was Gemini (formerly Bard), a family of multimodal models that integrate text, image, and code. Gemini 2.5 Pro competes in academic and technical benchmarks and has been integrated into Google Cloud, Android, and Workspace. The challenge for Google is twofold: to maintain its dominance in search and to reinvent its advertising model in an environment where users prefer to interact with AI rather than browse links.
Open and Efficient Models: LLaMA and the Mistral Surprise
Meta opted for an open strategy, releasing its LLaMA models under open licenses. This decision aims to democratize access to AI and position Meta as a leader in distributed innovation. LLaMA 3.1 competes directly with GPT-4 and benefits from integration into platforms with billions of users. Mistral AI, on the other hand, has made a strong entrance thanks to models like Mistral-medium, which offer an exceptional cost-performance ratio. Its focus on efficiency and local deployment has captured the attention of developers and companies alike.
Peak Performance: GPT-5, Claude, and Specialization
Competition has driven the creation of increasingly specialized models. GPT-5, launched by OpenAI, is described as a model with capabilities similar to a PhD-level expert, ideal for complex tasks in programming, law, or finance. Anthropic, with Claude, has prioritized security and ethical alignment, gaining popularity in academic settings. Grok, developed by xAI (Elon Musk), claims to outperform GPT-5 in certain benchmarks. This diversification reflects a trend towards models adapted to specific contexts and professional needs.
Nvidia: The Silent Architect of AI Infrastructure
While the models grab headlines, Nvidia has established itself as the silent pillar of the revolution. Its GPUs are essential for training and running models like GPT-4, Gemini, or Claude. Jensen Huang, CEO of Nvidia, has defended his position firmly, challenging competitors to make their own chips if they are not happy with the prices. Nvidia not only dominates the hardware but also offers complete platforms for AI development, becoming a strategic player in the global digital infrastructure.
Technical and Multimodal Advances: From GPT-3.5 to Convergence
The technical evolution of LLMs has focused on improving coherence, depth, and reasoning ability. The increase in the number of tokens and the quality of training data has made it possible to generate up to 80% of an application's backend with a single instruction. Multimodality—the ability to process text, image, and audio—has become the new standard. ChatGPT 4.0 and Gemini offer visual analysis, creative generation, and real-time responses, getting ever closer to a truly human interaction.
The Battle for Talent and the Exchange of Accusations between CEOs
The race for AI is also being fought on the human front. Big tech companies are competing to attract the best researchers, offering compensation packages that can exceed $300 million. This competition has generated public tensions: Sam Altman accused Meta of "poaching talent," while Elon Musk criticized OpenAI for "betraying its original mission." These conflicts reflect not only the intensity of the competition but also the strategic importance of human capital in the development of AI.
Enterprise Adoption and the Data Security Dilemma
The adoption of generative AI tools in the business world has been rapid and widespread. Surveys reveal that 69% of engineers already use them, although 79% admit to having limited knowledge of how they work. The impact on productivity is positive, but concerns about the accuracy of responses and data security persist. Companies face the challenge of establishing clear policies for the responsible use of AI, balancing innovation with information protection.
The Regulatory Framework: The EU AI Act and Future Projections
In the face of the dizzying advance of AI, the European Union has led the creation of a regulatory framework with the AI Act. This legislation classifies systems according to their level of risk and establishes specific rules for general-purpose models like ChatGPT. As of August 2025, these rules came into effect, marking a milestone in algorithmic governance. Despite regulatory and energy challenges, the global AI market is projected to reach $4 trillion by 2034, solidifying its role as a driver of global transformation.