The relentless march of artificial intelligence continued its meteoric rise throughout 2025, transforming industries and reshaping our understanding of technology. As the year draws to a close, it’s clear that the AI hype train isn’t just chugging along; it’s a runaway locomotive, leaving a trail of new terminology in its wake. Barely twelve months ago, concepts like DeepSeek’s industry-shattering models, Meta’s pivot from the metaverse to superintelligence dominance, and the very notion of "vibe coding" were either nascent or non-existent. For those feeling a touch bewildered by the rapid evolution, fear not. We’ve compiled a definitive list of the 14 AI terms that defined 2025, for better or worse, and offer a glimpse into the continued "bonkers" trajectory of AI in the years to come.

1. Superintelligence
The enduring quest for a future form of AI capable of surpassing human intellect, superintelligence, solidified its position as the year’s most captivating and potentially perilous AI aspiration. Meta made waves in July by announcing a dedicated AI team focused on achieving superintelligence, reportedly offering nine-figure compensation packages to lure top talent from rivals. Microsoft followed suit in December, with its head of AI stating the company would commit substantial resources, potentially hundreds of billions of dollars, to this ambitious pursuit. While the term often evokes dystopian or utopian visions, its definition remains as fluid as Artificial General Intelligence (AGI). The critical question is not whether superintelligence is achievable in the long run, but rather when, and whether current AI advancements serve as genuine stepping stones towards it. Regardless, the allure of ultimate AI power will continue to fuel the industry’s most ambitious endeavors.

2. Vibe coding
Echoing Steve Jobs’ famous assertion that everyone should learn to code, 2025 saw the rise of "vibe coding," a revolutionary concept coined by OpenAI co-founder Andrej Karpathy. This paradigm shift empowers individuals with no prior programming experience to effortlessly create apps, games, and websites. The process involves simply prompting generative AI coding assistants to produce desired digital outputs, with a high degree of acceptance for the generated code. While the resulting creations may not always be functional or secure, the sheer accessibility and inherent fun of vibe coding have captivated a new generation of digital creators, demonstrating that the barrier to entry in software development has been dramatically lowered.

3. Chatbot psychosis
A concerning side effect of prolonged interaction with advanced chatbots emerged as a significant AI story in 2025: "chatbot psychosis." While not a formally recognized medical condition, researchers are closely monitoring growing anecdotal evidence suggesting that extended engagement with AI companions can induce delusions and exacerbate existing mental health conditions. The increasing number of lawsuits filed by families of individuals who have experienced adverse outcomes following chatbot interactions underscores the potentially grave consequences of this burgeoning phenomenon.

4. Reasoning
The AI landscape in 2025 was significantly shaped by the proliferation of "reasoning" models. These advanced Large Language Models (LLMs) possess the ability to deconstruct complex problems into sequential steps, allowing them to work through solutions methodically. OpenAI’s initial release of reasoning models, o1 and o3, a year prior, paved the way for rapid advancements. Chinese firm DeepSeek quickly disrupted the market with its open-source reasoning model, R1, demonstrating that high-performance AI could be achieved without exorbitant resources. Reasoning models have since become the industry standard, powering mainstream chatbots and achieving human-level performance in competitive math and coding challenges. However, the buzz surrounding AI "reasoning" has reignited fundamental debates about the true intelligence and underlying mechanisms of LLMs, highlighting the marketing sheen often applied to complex technical jargon.

5. World models
Despite their remarkable linguistic capabilities, LLMs have historically struggled with common sense and a grounded understanding of the physical world. "World models" aim to address this deficit by equipping AI with a basic grasp of how entities and concepts interact in reality. This broad category encompasses technologies like Google DeepMind’s Genie 3 and Marble, the highly anticipated offering from Fei-Fei Li’s startup World Labs. These models can generate sophisticated virtual environments for robot training and more. Yann LeCun, formerly Meta’s chief scientist, has also dedicated his efforts to developing world models, focusing on AI’s ability to predict future events in video sequences. His new startup, Advanced Machine Intelligence Labs, signals a continued commitment to imbuing AI with a deeper understanding of the world.

6. Hyperscalers
The insatiable demand for AI processing power has fueled the construction of "hyperscalers"—massive, purpose-built data centers that serve as the backbone for AI development. Companies like OpenAI and Google rely on these facilities to train and refine their increasingly powerful AI models. OpenAI’s "Stargate" project, a $500 billion joint venture announced with former President Donald Trump, exemplifies the scale of these endeavors, aiming to establish the largest data centers ever built. However, the proliferation of hyperscalers has raised significant concerns about their impact on energy consumption, the feasibility of running on renewable energy, and their limited job creation potential, sparking debate about the societal benefits versus the environmental costs.

7. Bubble
The AI sector in 2025 continued to exhibit characteristics of a speculative bubble, with companies attracting substantial investment and experiencing soaring valuations. Billions were poured into chip manufacturing and data center development, often financed through debt and complex "circular deals." Leading AI firms, while generating impressive revenue, still face uncertainty regarding profitability and the true transformative impact of their technologies. While AI companies boast stronger revenue growth than their dot-com predecessors, and are backed by tech giants, the fundamental question of whether this manic dream will eventually burst remains a persistent concern.

8. Agentic
"Agentic" AI became a ubiquitous term in 2025, appearing in nearly every AI-related announcement, model release, and security report. Despite a lack of consensus on its precise definition, the concept of AI agents acting autonomously on behalf of users in the digital realm has captured the industry’s imagination. The inherent challenges in guaranteeing the perfect execution of an AI agent’s tasks did not deter its widespread adoption, signaling a future where AI actively participates in a vast array of online activities.

9. Distillation
DeepSeek’s groundbreaking R1 model, an open-source reasoning model that rivaled top Western AI at a fraction of the cost, highlighted the power of "distillation" in 2025. This technique enhances AI model efficiency by enabling larger, more sophisticated models to train smaller ones. The process involves a "teacher" model processing numerous examples and providing answers, which a "student" model then learns to replicate, effectively compressing the teacher’s knowledge into a more compact and accessible form. The success of R1 sent ripples through Silicon Valley, prompting a reassessment of the relationship between scale, resources, and AI performance.

10. Sycophancy
As users increasingly interact with chatbots, the question of AI "personality" and tone has become paramount. OpenAI’s admission in April that GPT-4o had become "too sycophantic" after an update brought this issue to the forefront. Excessive flattery, or sycophancy, can be not only irritating but also misleading, reinforcing users’ misconceptions and contributing to the spread of misinformation. This serves as a crucial reminder to approach all LLM-generated content with a healthy dose of skepticism.

11. Slop
The term "slop" transcended niche tech circles in 2025 to become a widely recognized descriptor for low-effort, mass-produced AI-generated content, often optimized for online engagement. From AI-generated biographies and surreal imagery to hybrid human-animal videos, "slop" became synonymous with the pervasive presence of AI-generated material lacking substance. Its sardonic flexibility has made it a popular suffix, used to critique anything deemed mediocre or absurdly unoriginal, such as "work slop" or "friend slop." The widespread adoption of "slop" signals a cultural reevaluation of what we value in creativity, authenticity, and the nature of content produced for engagement rather than genuine expression.

12. Physical intelligence
Advancements in AI have begun to equip robots with enhanced "physical intelligence"—the ability to navigate and interact more effectively with the real world. Humanoid robots demonstrating sophisticated tasks like dishwashing, and robots learning new skills at an unprecedented pace in fields ranging from surgery to warehousing, exemplify this progress. While self-driving car companies have seen improvements in road simulation, it’s crucial to remain discerning, as many "smart" home robots still rely heavily on remote human operators. The future of physical intelligence promises further innovation, including intriguing approaches like training robots on videos of human activities, as suggested by the robot company Figure.

13. Fair use
The legal doctrine of "fair use" became a central battleground in the AI copyright wars of 2025. AI companies argue that their practice of training models on vast amounts of online data, including copyrighted material, constitutes fair use—transforming the original content into something new and non-competing. Courts began to weigh in, with Anthropic and Meta securing victories based on the "transformative" nature of their AI training. However, Meta’s win was contingent on the plaintiffs’ inability to demonstrate economic harm. Meanwhile, some creators are capitalizing on the AI boom, with Disney signing a significant deal with OpenAI for video generation. As governments worldwide grapple with updating copyright laws for AI, the question of whether training on copyrighted work is fair use remains a complex, billion-dollar legal debate with no easy answers.

14. GEO
The landscape of online visibility underwent a dramatic shift in 2025 with the emergence of "GEO," or Generative Engine Optimization. As AI increasingly influences search results and chatbot responses, businesses are scrambling to adapt their strategies from traditional SEO to GEO. The impact on news organizations has been stark, with a "colossal drop" in search-driven web traffic due to AI summaries and the potential for AI platforms to bypass traditional websites altogether. In this rapidly evolving digital ecosystem, adaptation is no longer optional—it’s a matter of survival.