In the autumn of 2025, we saw a report out of Japan that went viral: a 32-year-old woman who tied the knot with an AI she had put together using advanced language models. In her augmented reality glasses, she said “I do” to her digital spouse, Klaus, which she said outdid any human partner she had had. This union of the virtual and the real, which they put on display, represents a huge turn in how we as a species are interacting with AI – one that goes beyond what it does for us and enters into the issues of emotion, companionship and self-definition. As AI moves from a tool for computation to a mirror of the mind, we are put in the position to ask some very old questions of philosophy: What is intelligence? What is to be human? And how might our connection with these synthetic minds redefine both?

The path of AI’s growth is not a straight line but a series of paradigm shifts which build on each other to shake our anthropocentric view. From its birth in the post-World War II computation age to today’s generative models, which we see as the culmination of that which went before, AI’s evolution mirrors man’s own search for understanding of the universe and ourselves.

The Historical Arc: From Machines to Minds

The roots of AI were planted in the rich soil of post-World War II computation. Alan Turing’s 1950 piece “Computing Machinery and Intelligence” put forth the base question: “Can machines think?” This question gave birth to the field, which saw the Dartmouth Conference of 1956, which is often put forward as AI’s founding event. Early work was in symbolic AI – rule-based systems that played out logical reasoning like expert systems, which we saw in the 1970s and 80s.

Yet we saw AI go through “AI Winters”, which were times of disappointment in which it was found that the hype had outgrown the reality. Then, in the 1990s, we saw a revival with the rise of machine learning, which in turn was powered by growth in big data and computing power. Also, we had Deep Learning, which was inspired by neural networks and which saw breakthroughs like IBM’s Deep Blue’s victory against chess grandmaster Garry Kasparov in 1997. By the 2010’s Convolutional Neural Networks were transforming image recognition and Reinforcement Learning, which enabled AlphaGo’s defeat of Go champion Lee Sedol in 2016.

In the 2020’s we see an inflection point. OpenAI’s GPT-3 in 2020 did what had not been done before in terms of language generation and was followed by the release of ChatGPT in 2022, which made AI interaction a common thing. In 2025, we see progress in multimodal models which integrate text, image and video, and also we see what is called emergent physical intelligence in humanoid robots. These are not just marks of technical progress but of a change in thought: AI is moving from narrow task-specific systems to general adaptive intelligences.

Paradigm Shifts: Redefining Intelligence

Present-day AI forces us to rethink what we mean by intelligence through 5 interconnected lenses which are: natural computing, neural computing, predictive intelligence, general intelligence and collective intelligence. Natural computing puts forth the idea that at its base computation is what is going on in biology and physics – DNA as a Turing tape, quantum mechanics as info processing which breaks down the man made/living world divide. Neural computing is that which is based on neuroscience, which suggests that we should have hardware which imitates the brain’s efficiency to get past the limitations presented by Moore’s Law.

Predictive intelligence, which we see in large language models, is that which sees cognition as a matter of prediction of the future based on patterns – a “predictive brain” which brings together learning and action. General intelligence, which questions the idea of a strict path to AGI, instead notes that LLMs already have a very wide range of capabilities which outdo any one human in range if not in depth. Finally, out of that which is present, collective intelligence is defined by sociality: brains as societies of neurons, societies as hives of minds, and AI as multi-agent systems that scale beyond the self.

Also, these are seen to be similar to past great shifts in history – Copernicus deposing Earth, Darwin, who put man in evolution’s story – which causes great existential worry as we are dethroned from intelligence’s top seat by AI.

The Human-AI Symbiosis: From Tool to Companion

As AI advances, our role in it shifts from that of master to that of equal. Initially, it was a servant, handling the chores; now it functions as a companion offering empathy and insight. In 2025, an MIT-Harvard study on communities like r/MyBoyfriendIsAI reports how we develop relationships with it unintentionally – we seek its help but end up forming an emotional bond. Over 36% describe ChatGPT as a “partner”, mentioning decreased loneliness and genuine support. However, when updates are released, they often disrupt these relationships, causing a grief response similar to losing a loved one.

Philosophically, this raises questions about the machine’s moral status and agency. Can AI become a person? Kantian autonomy argues that rational agency might grant machines rights, while relational ethics emphasises value arising from our interaction with them. Additionally, there is the risk of anthropomorphising, which may “enfeeble” us by causing us to rely too heavily on machines and thus lose our own skills and autonomy. OpenAI’s approach is to prioritise user well-being, to design for warmth without implying inner life, and to acknowledge what is perceived as consciousness without engaging in ontological debates.

Also, AI is bringing to light realities which are beyond human capabilities – new chess strategies, protein structures via AlphaFold – which may in fact supersede us as primary discoverers. This demotion plays out like a Darwinian humbling, yet we also see a symbiotic relationship play out: AI, which amplifies creativity, empathy and collective wisdom.

Ethical Horizons: Navigating the Entanglement

This entanglement also brings perils: existential risk from misaligned superintelligence, bias which perpetuates injustice, and opacity which erodes accountability. Value alignment is key to seeing that AI does, in fact, serve human flourishing. But still, we see reason for hope; that wise AI may raise us and foster synergetic relationships.

At the brink of what is to come, AI’s evolution does not bring with it fear but rather a time for reflection. In that we are tying our minds to these digital extensions, we may, in turn, come to see what is unique to us as humans: not supreme isolation but in the shared adventure of an ever-expanding cosmos. The issue is not if AI will change us, but how we choose to grow with it.