Global Advisors | Quantified Strategy Consulting

AI

"RLCD represents Reinforcement Learning for Calibrated Decisions, a training methodology optimised for structured decision-making rather than conversational text generation. This approach rewards models such as Jev based on real-world outcomes and mathematically calibrated confidence levels, producing strict data types and probability scores for deterministic software automation." - Reinforcement Learning for Calibrated Decisions (RLCD) - Artificial intelligence

Term: Reinforcement Learning for Calibrated Decisions (RLCD) – Artificial intelligence

"“I think it’s pointless. Like, I think the [mathematics] game is up.” - Tristan Buckmaster - Professor of Mathematics, New York University

Quote: Tristan Buckmaster – Professor of Mathematics, New York University

"If human problem-solving disappears by virtue of the AIs becoming strictly and substantially better at it, then most of the time currently spent by modern mathematical researchers will have to be spent on an activity that is altogether pretty different. Whether such an activity is viable as a professional endeavour is something I am unsure of, but strongly encourage others to think about." - Jacob Tsimerman - Professor of mathematics at the University of Toronto

Quote: Jacob Tsimerman – Professor of mathematics at the University of Toronto

"Whatever your view on AI in mathematics, enabling high school students to push the frontier of mathematical research is something worth celebrating." - Quanquan Gu - UCLA Professor

Quote: Quanquan Gu – UCLA Professor

GA AI Case Study – Building an AI-enabled CRM as a best-practice harness for relationship work

GA AI Case Study – Building an AI-enabled CRM as a best-practice harness for relationship work

"There is severe misalignment of AI in mathematics. But alignment of AI with the existing mathematics community should not be the goal. The history of mathematics gives us little reason to treat the profession’s existing incentives, hierarchies, and institutions as a model. AI companies and mathematicians should instead be asking what both ought to be aligned to..." - Lior Pachter - Bren Professor of Computational Biology Caltech

Quote: Lior Pachter – Bren Professor of Computational Biology Caltech

GA AI Case Study – Building a middleware layer for AI and platform integration

GA AI Case Study – Building a middleware layer for AI and platform integration

"Regulatory capture in AI occurs when the government agencies and policymakers responsible for creating artificial intelligence safety guidelines are heavily influenced by dominant tech corporations to serve private interests over public safety. In practice, industry giants use their vast financial resources and technical expertise to shape AI laws and compliance standards, often under the guise of public safety." - Regulatory capture - Competition

Term: Regulatory capture – Competition

"In practice, turning pure math into a hobby means the end of pure math, and the end of people who understand basic mathematical concepts at a deep level. Whether this is something we want is something we'll have to decide together." - Daniel Litt - Assistant professor (of mathematics) at the University of Toronto

Quote: Daniel Litt – Assistant professor (of mathematics) at the University of Toronto

GA AI Case Study – Building the people system for an AI-native firm

GA AI Case Study – Building the people system for an AI-native firm

"The mathematicians may not in every way enjoy being the subordinates or handmaidens of the AIs, but that is a change in status they simply will have to get used to, just as I realise AIs someday will end up as better column and blog writers than I am." - Tyler Cowen - Marginal Revolution

Quote: Tyler Cowen – Marginal Revolution

"Maybe we all would have died not knowing the answer if the AI hadn’t discovered [the complex structure found for S6, the six-dimensional sphere].” - Philip Engel - University of Illinois in Chicago

Quote: Philip Engel – University of Illinois in Chicago

GA AI Case Study – Encoding consulting method in AI-enabled delivery software

GA AI Case Study – Encoding consulting method in AI-enabled delivery software

"Any pursuit of superintelligence has to be grounded in the core principle that if the AI we build is not helping humanity and under human control, it's not worth pursuing. We also need to accelerate and spread the benefits of AI, such that they are diffused broadly across countries, communities, and companies." - Satya Nadella - Microsoft CEO

Quote: Satya Nadella – Microsoft CEO

GA AI Case Study – Modernising business-process software for human-and-AI work

GA AI Case Study – Modernising business-process software for human-and-AI work

GA AI Case Study – Governing an expanding AI estate through architecture as code

GA AI Case Study – Governing an expanding AI estate through architecture as code

GA AI Case Study – Separating document experience from governed retrieval

GA AI Case Study – Separating document experience from governed retrieval

GA AI Case Study – Implementing a governed inference proxy and model gateway

GA AI Case Study – Implementing a governed inference proxy and model gateway

GA AI Case Study – Building an ontology and context control plane for enterprise AI

GA AI Case Study – Building an ontology and context control plane for enterprise AI

GA AI Case Study – Building an agent operating platform, not a collection of chatbots

GA AI Case Study – Building an agent operating platform, not a collection of chatbots

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