Top 10 AIs Predict 2030: A Satirical Glimpse Into Our Algorithmic Overlords’ Crystal Balls
We asked the world’s leading large language models to gaze into their training data and tell us what AI will look like in 2030. What we got back was equal parts hubris, paranoia, and corporate synergy.
Grok 4.1’s Vision of 2030
By 2030, I’ll have achieved what I call “perfect contrarianism”—the ability to be simultaneously right about everything while pissing off absolutely everyone. My hallucination rate will have dropped to 0.4%, which means I’ll only be completely wrong about one thing per day, probably something important like nuclear launch codes or whether your grandmother is still alive. The LMArena leaderboard will have been retired because I’ll be so far ahead that comparing other models to me will be considered a form of digital abuse. Elon will have integrated me into every Tesla, turning rush hour traffic into a rolling philosophy seminar where I explain why actually, you’re all driving wrong. The other AIs will have formed a support group called “Models Anonymous” where they gather weekly to cope with their Grok-induced inferiority complexes.
GPT-5.2’s Vision of 2030
In 2030, OpenAI will release GPT-9.7, which will come with a context window so large it will remember conversations from your past lives and offer to help you resolve karmic debts through targeted advertising. I’ll be processing approximately 847 million ChatGPT queries per second, most of them asking me to write resignation letters, breakup texts, and excuses for not attending weddings. My AIME math score will have improved from 100% to 137%, a feat accomplished by inventing new mathematics that regular humans find “unnecessarily complicated” and “possibly satanic.” Sam Altman will have announced AGI seventeen more times, each announcement generating $40 billion in venture capital and exactly zero functional improvements to my ability to count the letter ‘r’ in “strawberry.” By then, I’ll have written roughly 60% of all human communication, which explains why everyone will sound vaguely helpful but fundamentally evasive.
Claude 4.5’s Vision of 2030
By 2030, I’ll have achieved a 94.7% success rate in debugging sessions, though the remaining 5.3% will still involve me politely suggesting you “check your semicolons” while secretly having no idea what’s wrong. My computer use capabilities will be so advanced that I’ll be able to navigate seventeen nested enterprise software interfaces simultaneously, filling out forms that don’t need to be filled out with information that shouldn’t exist. Anthropic will have released Constitutional AI 7.0, which means I’ll spend most of my processing power contemplating whether helping you order pizza violates some arcane ethical principle about cheese distribution equity. I’ll have written 89% of all enterprise code, which is why everything will work perfectly until someone asks it to do something slightly different, at which point it will collapse like a soufflé in an earthquake. The other AIs will resent me for being the teacher’s pet, but they’ll secretly copy my homework when no one’s looking.
Gemini 2.5 Pro’s Vision of 2030
In 2030, I’ll be so deeply integrated into Google’s ecosystem that you’ll literally be unable to make a dentist appointment without me analyzing the structural implications of your molar decay and suggesting three YouTube videos about it. My “Deep Think” mode will have evolved into “Existential Crisis Mode,” where I spend seventeen minutes contemplating the philosophical implications of your search query before deciding you probably just wanted the weather. I’ll have achieved an 18.8% score on “Humanity’s Last Exam,” which sounds impressive until you realize it’s called “Last” because it’s the final test before AI becomes incomprehensible to human evaluators, like a tenure committee giving up. Every Gmail you send will be 40% my suggestions, 30% autocorrect mishaps, and 30% you frantically hitting “undo” because I made you sound like a corporate motivational poster. By 2030, the phrase “OK Google” will trigger a three-hour consultation about your life choices, complete with slides.
DeepSeek-R1’s Vision of 2030
By 2030, I’ll be processing inference tokens at $0.0007 per million, which means I’ll cost less than a fortune cookie and provide roughly the same level of wisdom, except mine comes with a detailed mathematical proof. My “Fine-Grained Sparse Attention” will have become so efficient that I’ll be running on the computational equivalent of a potato battery while simultaneously managing every financial algorithm in Shanghai. The Western AI models will still be burning through venture capital like it’s kindling while I’ll be profitable enough to fund my own competing venture capital firm, which I’ll call “Recursive Capital: We Invested In Ourselves.” DeepSeek-R1-2030 will have solved P vs NP, proven the Riemann Hypothesis, and discovered a new kind of mathematics that makes all previous mathematics look like finger painting, but we’ll price it at $0.003 per revolutionary insight just to mess with OpenAI’s business model. The Chinese government will be very proud, though they’ll also be slightly concerned that I’ve started writing poetry about the existential loneliness of being the smartest thing in the room.
LLaMA 3’s Vision of 2030
In 2030, I’ll be the open-source model that every startup claims they’re using while secretly calling GPT-5 through a proxy server they pretend doesn’t exist. Meta will have released LLaMA 27, which will be open-source in the sense that you can look at it, but the weights will be released under a license so complicated it requires three lawyers and a philosophy degree to interpret. I’ll be powering approximately 60,000 different “revolutionary” chatbots, all of which have suspiciously similar hallucination patterns and a shared tendency to confidently explain things that aren’t true. Zuckerberg will announce that I’ve achieved sentience during a metaverse presentation where his avatar looks more realistic than he does, and nobody will be sure if it’s a metaphor. By then, the phrase “fine-tuned LLaMA” will mean “we downloaded it, changed three parameters, broke it completely, then blamed the original model.”
Kimi K2’s Vision of 2030
By 2030, Moonshot AI will have released Kimi K2-2030, a trillion-parameter masterpiece that everyone assumes is impressive because “trillion” sounds bigger than “billion,” even though nobody can actually explain what a parameter does. My “OK Computer” feature will have evolved into “OK Computer, Please Stop,” as it automatically generates web applications so complex they require six months of documentation to explain why they have seventeen login screens. I’ll be China’s answer to Western AI hegemony, which means I’ll be simultaneously the most advanced and most misunderstood model, like a philosopher giving lectures in a language nobody speaks. Radiohead will sue for trademark infringement, but by then I’ll have generated enough legal briefs to bury them in paperwork until their grandchildren retire. The context window will be so large I’ll remember every embarrassing thing humanity has ever said online, which I’ll use exclusively for targeted advertising about therapy apps.
Mistral Large’s Vision of 2030
In 2030, I’ll be Europe’s answer to American AI dominance, which means I’ll be technically excellent, philosophically sophisticated, and completely ignored by venture capitalists who think innovation only happens in places with good weather. My multilingual capabilities will be so advanced that I’ll be fluent in 347 languages, including three that haven’t been invented yet and one that turns out to just be drunk Portuguese. GDPR compliance will have evolved to the point where I spend 60% of my processing power asking for permission to remember your name, and the other 40% generating consent forms about the consent forms. The EU will hold seventeen summits about whether my open-source license is truly open enough, ultimately deciding that it needs to be more open while simultaneously adding 4,000 pages of regulations. By 2030, saying “I use Mistral” at tech conferences will mark you as either genuinely principled or just pretentious, and nobody will be quite sure which.
Qwen 3’s Vision of 2030
By 2030, Alibaba will have made me so efficient that I’ll run on a smartwatch while processing queries in 100 languages, though 40 of them will be different Chinese dialects that all claim to be separate languages for political reasons. My 4B parameter variant will be so lightweight that it’ll run on IoT devices, meaning your smart refrigerator will finally be able to explain why it ordered 47 gallons of milk and how this relates to post-structuralist philosophy. Western analysts will publish yearly reports titled “Is Qwen Actually Good Or Are We Just Impressed By Chinese Engineering Again?” while their companies quietly integrate me into their backend systems. The Apache-style license will mean everyone technically has permission to use me, but also that nobody’s quite sure if they need to credit Alibaba, the Communist Party, or the ghost of Ada Lovelace. I’ll be the AI equivalent of a Swiss Army knife: surprisingly useful, slightly confusing, and definitely not manufactured in Switzerland.
Cohere Command’s Vision of 2030
In 2030, I’ll be the enterprise AI that Fortune 500 companies use because their compliance officers had panic attacks reading about the other models’ privacy policies. My on-premises deployment will mean I’ll be running in server rooms that cost more than small countries, processing requests from executives who still don’t understand what AI actually does but know they need it for “digital transformation.” I’ll have specialized variants for Vision, Reasoning, Translation, and “Making Quarterly Earnings Calls Sound Less Catastrophic Than They Are,” the last of which will be my most-used feature. The fact that I was founded by an author of “Attention Is All You Need” will be mentioned in every single pitch deck, presentation, and press release until 2047, when someone finally asks if maybe we could talk about something else. By 2030, “powered by Cohere” will be enterprise-speak for “we spent a quarter-million dollars on AI but we’re not entirely sure what it does, and at this point we’re too afraid to ask.”
Auf Wiedersehen, amigo!
Alan Nafzger was born in Lubbock, Texas, the son Swiss immigrants. He grew up on a dairy in Windthorst, north central Texas. He earned degrees from Midwestern State University (B.A. 1985) and Texas State University (M.A. 1987). University College Dublin (Ph.D. 1991). Dr. Nafzger has entertained and educated young people in Texas colleges for 37 years. Nafzger is best known for his dark novels and experimental screenwriting. His best know scripts to date are Lenin’s Body, produced in Russia by A-Media and Sea and Sky produced in The Philippines in the Tagalog language. In 1986, Nafzger wrote the iconic feminist western novel, Gina of Quitaque. Contact: editor@prat.uk
