quantum:customer_profiles
Table of Contents
Customer Profiles and Problem Statements
Patent-Centric
As long as we cannot self-finance
...
| Customer Profile | Problem Statement | Offering | Example |
| Corporation who wants a much faster processor and can afford to fund the research and build it | In ultra-high-stakes competition, constraint is speed of situational awareness and/or resolution of highly non-convex optimization problems | Full or Partial ownership of RequisiteQ and its patent | Azure with their millions of customers, AWS with their masses of data, US Military with their need to see the sky, NIST with their need for faster-than-NVIDIA RLADP-based TAAP control unit… |
| Laboratory who wants to be associated with our research into hardware, a much faster processor | FOMO in field of quantum computing | Status as primary sponsor | MIT, Rahman Institute, Berkeley, Oak Ridge… |
| Hardware manufacturer who wants to be associated with a much faster processor and can afford to fund the research and build it | Our designs have maxed out and our customers want moar fastee | Full or Partial ownership of RequisiteQ and its patent and/or percentage of processor sales | Suppliers of Row 1 above e.g. Taiwan, Intel, IBM… |
| Corporations selling optimization services | Primary competitive constraint is performance of optimizer and incremental improvement is desirable enough to pay for | Quantum-inspired Optimization services supported by RLADP QIAGI | IBM, Azure, AWS, Gurobi, InfinityQ… |
| Corporations buying optimization services | Significant competitive constraint is pace of complex computer-aided decision-making and incremental improvement is desirable enough to pay for | Quantum-inspired Optimization services services supported by RLADP QIAGI | American Airlines, Delta Airlines, Tesla, Google… |
Once we are making and selling first-gen hardware based on the patent
| Customer Profile | Problem Statement | Offering | Example |
| Corporations selling optimization services | Primary competitive constraint is performance of optimizer | tQQO boxes or cloud access with much faster processing | IBM, Azure, AWS, Gurobi, InfinityQ… |
| Corporations buying optimization services | Significant competitive constraint is pace of complex computer-aided decision-making | optimization services supported by tQQO boxes or cloud access with much faster processing | American Airlines, Delta Airlines, Tesla, Google… |
Separable-from-Patent
AI Consulting
| Customer Profile | Problem Statement | Offering | Example |
| Corporation who wants to prepare for the new world of regulated / certified AI | The new world of AGI is confusing and dangerous and I have to get my head around it somehow | Expert consultation on separation of AI concerns from corporate concerns, and of state-of-the-art AI certification and licensing approaches | US Senate, NIST… |
AI Business Function
| Customer Profile | Problem Statement | Offering | Example |
| Author who wants someone else to do their marketing | Marketing is hard and expensive | AI-driven marketing of your books | Hyrum W. Hawks… |
| Group of nerds with an idea but no business savvy | CEOs are expensive and bossy | AI-driven exploration and execution of business opportunities afforded by your idea | RequisiteQ… |
Exemplary AGI
| Customer Profile | Problem Statement | Offering | Example |
| Corporation who wants to promote best practices in AGI | AGI seems like black magic that no one will ever understand which means that no one is being held accountable for the impact of AGI and no one feels empowered to hold people accountable for the impact of AGI | A white-box AGI capable of controlling significant corporate assets in pursuit of multiple objectives, and doing so accountably and transparently (via classic RLADP e.g. Adaptive Critic etc.) | NIST… |
Crossing the Streams
This is where we started and needed to back up from
| Customer Profile | Problem Statement | Offering | Example |
| Corporations who have assets that they do not want to lose | Profits are deeply constrained by expenses due to replacing lost resources or plant | 50% fewer losses of valuable resources or plant (via RLADP control regime using Exemplary AGI powered by tQQO) | Air Force (airplanes), USDOT (lives from car accidents), Tata Corp (mining equipment), Space Force (rocket ships, fuel) |
| Laboratories who want to reverse-engineer the utility function of any given AGI | Corporations can make any claim they like about their AGI without repercussions because there is no way to test whether the claims are true | Mathematical representation of the utility function exhibited by the AGI under test (via controlled testing of AGI by Exemplary AGI powered by tQQO) | NIST… |
quantum/customer_profiles.txt · Last modified: 2024/08/07 10:11 by baw-geordie