More ovens do not guarantee more dinners
Powerful hardware is only part of the AI story. Follow the work from capacity to paying customers — and then examine where the token fits.
Powerful hardware is only part of the AI story. Follow the work from capacity to paying customers — and then examine where the token fits.
🍳 Imagine a busy kitchen with an expensive new oven — and a queue of orders that still moves too slowly.
The oven may be excellent. But perhaps ingredients arrive late, preparation space is crowded, or finished dishes wait for someone to carry them out. Adding another oven would increase capacity at one station. It would not necessarily solve whatever is holding up dinner.
AI infrastructure presents a similar puzzle. Powerful processors matter — but so does how work reaches them, how it is divided, and how efficiently the surrounding system operates.
The organiser
🧑🍳 When NVIDIA introduced Dynamo on 18 March 2025, it described software for coordinating AI inference: the computation involved in producing responses from a trained model. The announcement covered separating stages of that work across GPUs, routing requests, and managing memory.
These were NVIDIA's descriptions of its technology — not an independent performance assessment. Read NVIDIA's announcement
The kitchen analogy helps explain why coordination matters. A capable organiser keeps one station from sitting idle while another is overwhelmed — more useful work from arranging existing resources better.
The analogy is deliberately simplified: GPUs are not interchangeable kitchen appliances, and performance depends on the actual workload and system.
Follow the orders to the till
🧾 For someone researching AI businesses, the next question is whether useful work becomes paid work.
We would want to see customers placing orders, returning for more, and paying enough to cover the cost of serving them. In practical terms: repeat usage, revenue, operating costs — and how much demand depends on promotional incentives.
These are FORTUNA's proposed research questions, not findings about a particular company.
Where does the token fit?
🪙 Crypto introduces another layer. If an AI project has a token, how does the token connect to the service?
- 🙋 Does the customer need it?
- 🔁 Does usage create a lasting reason to hold it?
- 📦 What supply enters the market while that demand develops?
Owning a restaurant's loyalty points would not automatically give you a share of its profits. Similarly, the precise rights and mechanics of a token matter. A successful service and a successful token investment are separate propositions — they need to be connected with evidence.
NVIDIA's announcement does not establish a partnership with, or an economic benefit for, any AI token. What it offers is an entry point into a better question: how does the machinery become a service people repeatedly choose to pay for?
Start with the ovens — but follow the orders all the way to the till. 💰
🔎 Reporting scope: a historical technology announcement and an original research framework. No current software review, independent benchmark, or token ranking is claimed.