Sizing the Probabilistic Computing Opportunity

Probabilistic computing is about more than computing with randomness.

Probabilistic computing is the industry’s name for technologies that compute with probability distributions rather than single numbers. Some draw on probability theory to represent whole distributions compactly, in a fixed number of bits. Others harness the physics of materials to induce randomness in individual bits. Several technology startups are moving rapidly to bring products to market. The applications range from quantitative finance and semiconductor design to robotics, supply chain management, pharmaceutical R&D, and trustworthy AI. Almost every market figure published for these applications of probabilistic computing is a forecast. This one is not. It counts named institutions from lists you can open and costs the use cases they already run today.

Filter market spend to a subset of use cases
Use case
One use case at a time. Only use cases with a sourced entity count carry a figure. The rest show what is known about them instead.
What the pills mean
Pills name the technologies with evidence for the selected use case, colored by technology and always labeled. Bold on a tint is measured, a measurement with a stated baseline. Plain is demonstrated, a production deployment or public demonstration with a source. Dashed is claimed, a vendor or press assertion. A red ring is contradicted, where somebody measured the pairing and the result ran against it. Those pills link straight to the finding, because the reader's first question is who says so. No pill means Signaloid has no source on file for that pairing, which is not the same as none existing. This list records published evidence, so an absence of red beside a technology is not a claim that nothing counts against it. Hover or tap a pill to see the source that put the technology on this list, and beneath it whether a customer can buy a product that does this today. That second fact is a separate question from how good the evidence is. A pill's appearance does not encode it: a generally available product can name a workload nobody has published a figure for, while a strong research result can have no product behind it at all.
Vendor capture assumption, %What share of the addressable spend suppliers of these technologies could capture. It starts at an illustrative 10%. Signaloid does not forecast that share, so replace it with your own.
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Notes
How this calculator works: What They Spend Now counts what named institutions pay today for the selected use case. It multiplies sourced institution counts by per-entity spend estimates. Vendor Opportunity multiplies that spend by a capture share you enter under Use Cases. It works only where a spend figure exists. Use cases without a sourced count of what drives their spend show their evidence instead of a figure.
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