Frontier AI systems are a lot easier to get your hands on now. You can reach them through APIs, low-code tools, and open-weight downloads. Training a frontier model from scratch, though, is still out of reach for almost everyone.
The original Transformer model cost about $670 in 2017. GPT-4 is estimated at $78 million to $100 million, and Gemini Ultra at about $191 million. And that’s before you factor in the other requirements: elite researchers, massive datasets, chips, and repeated retraining. Those numbers go a long way toward explaining why the United States produced 61 notable models in 2023, compared with 21 in the European Union and 15 in China.
So if you want to put AI into a product or a workflow, today’s tools are worth using. But the limits are still there. Open-weight releases don’t change who controls the base model, real tuning takes compute, clean domain data, and specialized expertise, and most startups, hospitals, and mid-sized manufacturers are still integrating what already exists while incumbents keep benefiting from scarcity.
That concentration is getting tighter across the whole stack. Amazon Web Services held 30% of the cloud market in Q1 2026, Microsoft Azure 20%, and Google Cloud 13%. Nearly half of global 2025 funding went to those players. Qualcomm bought Modular. d-Matrix bought Wallaroo.ai. Research stayed concentrated in the Global North, women and racial minorities were still underrepresented, and underserved regions could end up with weaker systems while a small group keeps deciding what comes next, even if access to models now runs through the cloud, APIs, and downloads.
Author: Alijah Raechel Nuestro
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"de-DE": "Alijah Nuestro ist eine Autorin und Creative Practitioner, die von der De La Salle University in Manila graduiert hat. Sie spezialisiert sich auf kreatives Schreiben und konzentriert sich dabei besonders auf Prosa, die Charakter, Stimme und narrative Form erforscht. Neben ihrer Arbeit in der Prosa hat sie sich mit Drehbuchschreiben, Event-Writing und Copywriting befasst, was es ihr ermöglicht hat, ihre Erzählfähigkeiten über verschiedene Medien und Zielgruppen hinweg anzupassen.",
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