AGI and Superintelligence: A New Era for Humanity?

A few days ago, I watched an interview with Demis Hassabis, CEO of DeepMind, and I was completely struck by how fast things are evolving in the world of artificial intelligence. It felt like a wake-up call, a realization that we are witnessing a revolution unfolding before our eyes. More than 15 years ago, I studied artificial intelligence at Université Paris-Dauphine. Back then, AI was a different beast. We worked with autonomous agents, inference principles, and even neural networks, but the technology was limited. GPUs weren’t powerful enough to train deep learning models effectively. My work primarily focused on decision trees, which were the ancestors of modern machine learning algorithms. At the time, AI felt more like a set of theoretical ideas rather than something capable of truly transforming the world. But today, everything has changed.

Evolution of AI: 10 Years Ago vs. Today

AI 10 Years Ago (2014)

A decade ago, AI was primarily based on classical machine learning techniques such as Support Vector Machines (SVMs), Decision Trees, and early neural networks. Convolutional Neural Networks (CNNs) had started gaining attention, especially after the success of AlexNet in 2012, revolutionizing image recognition. Recurrent Neural Networks (RNNs) were also widely used for sequential tasks like speech and text processing, though they struggled with long-term dependencies.

Computational power was a major limitation, as GPUs were not yet powerful enough to train large-scale models efficiently. Additionally, AI lacked access to vast labeled datasets, making training less effective. AI applications were mostly narrow and task-specific, powering recommendation systems (Netflix, YouTube), speech recognition tools (Siri, Google Assistant), and image classification models. Chatbots existed but were rule-based, offering only limited conversational capabilities.

AI Today (2024-2025)

Fast forward to today, and AI has evolved dramatically with the rise of deep learning and Transformer-based architectures like GPT, BERT, and PaLM. These models enable AI to generate human-like text, images, code, and even videos with remarkable fluency and accuracy. The shift from RNNs to Transformers, introduced in 2017, has allowed AI to process and understand long-range dependencies more effectively.

One of the biggest changes has been the exponential increase in available data and computing power. AI models are now trained on enormous datasets sourced from the internet, and advancements in GPUs and TPUs have made it possible to train massive neural networks. Self-supervised learning techniques have also reduced the reliance on manually labeled data, further accelerating progress.

Generative AI has become mainstream, with tools like ChatGPT, DALL·E, and MidJourney creating high-quality text, images, and even music. Multimodal AI models, such as GPT-4V, can now process and understand text, images, and audio simultaneously, broadening AI’s capabilities across different domains. AI is now deeply integrated into industries such as healthcare (drug discovery, medical imaging), finance (algorithmic trading, fraud detection), and software development (GitHub Copilot). Autonomous AI agents like AutoGPT can even complete complex tasks with minimal human intervention.

AI, the Turing Machine, and Human Intelligence

Alan Turing’s Turing Machine showed that machines could compute anything given the right instructions, forming the basis of modern AI. But does this mean humans are just biological machines? Unlike AI, humans possess emotions, self-awareness, and intuition—qualities that go beyond pure computation. While AI processes data with speed and precision, it lacks true understanding and consciousness, raising the question: Is intelligence just computation, or is there something uniquely human that AI can never replicate?

Are Humans Just Turing Machines?

With the rise of Artificial General Intelligence (AGI) and the possibility of superintelligence, I can’t help but wonder: Is the human mind simply a more advanced version of a Turing machine? If intelligence can be reduced to computations, then perhaps consciousness itself is just an emergent property of complex processing. If that’s the case, what happens when machines surpass us in intelligence?

This isn’t just a technical question—it’s a philosophical and ethical one. If machines become more intelligent than us, how much trust should we place in them? Should we fear deception, theft, and espionage? Will AGI develop human-like motivations—seeking rewards, power, and dominance? Or will it be fundamentally different from us, driven purely by logic and optimization?

The Social Nature of AI: Solitary or Collaborative?

One of the most intriguing questions is whether AI will be solitary or collaborative. Human intelligence has evolved through social interactions—our survival and progress depend on our ability to communicate, share knowledge, and work together. Will an advanced AI system seek to collaborate with other AIs to achieve its goals, just as humans form alliances? Or will it function in isolation, optimizing for its objectives without concern for others?

This question has massive implications. If AGI systems learn to cooperate, they could form a kind of machine civilization, accelerating innovation at an unimaginable pace. But if they operate in isolation, we might end up with unpredictable and uncontrollable intelligence, each system pursuing its own agenda without human oversight.

Will AI Innovate or Just Learn?

Another fundamental question is whether AI will experiment with new concepts or simply rely on existing data. Human progress has been driven by curiosity—by stepping into the unknown and testing ideas that have never been tried before. If AGI is truly intelligent, will it have its own form of curiosity? Will it design and conduct experiments to uncover new scientific truths? Or will it always be bound by the information we provide?

The answer to this question could define the future of human civilization. If AGI can truly innovate, we might enter an age of exponential discovery, where scientific breakthroughs happen at an unprecedented rate. But if AI is limited to existing knowledge, its intelligence—while powerful—will always be an extension of human intelligence rather than something fundamentally new.

A Philosopher’s Role in the AI Revolution

We are at the dawn of a new era, one that will redefine what it means to be human. As AI evolves, philosophers, ethicists, and thinkers must step up to guide humanity through this transformation. This isn’t just about technology—it’s about the very essence of intelligence, ethics, and existence.

How do we ensure that AI serves humanity rather than controls it? How do we define what it means to be intelligent, conscious, or even alive? These are no longer abstract questions for academics—they are urgent, real-world problems that will shape the next century.

The choices we make today will determine whether AGI becomes humanity’s greatest ally or its most unpredictable challenge. The revolution is happening now. Are we ready?

What’s Next for AI?

Despite the intellectual war between nations over which AI will become more dominant and who will reach space first, the development of Artificial General Intelligence (AGI) remains a major focus. AGI aims to create AI systems capable of reasoning, planning, and learning like humans, marking a shift from narrow, task-specific AI to more autonomous, adaptable intelligence.

As AI grows more powerful, governments and organizations are working on regulations to address ethical concerns and mitigate potential risks. Meanwhile, AI is evolving to become more human-like in its interactions, with enhanced emotional intelligence, deeper reasoning abilities, and contextual awareness.

AI has transformed from a niche technology into a fundamental force shaping modern life, augmenting or even replacing human intelligence in various fields. The next decade promises even more groundbreaking changes, bringing AI closer to human-level understanding and problem-solving—a future where the boundaries between human and artificial intelligence may blur like never before. 🚀