Mark L. Stone
marklstone.bsky.social
Mark L. Stone
@marklstone.bsky.social
Stochastically modeling, analyzing, and optimizing for more than 4 decades.
Stanford Emeritus Professor of Operations Research, Frederick "Fred" S. Hillier, died last week at the age of 89.

See www.linkedin.com/feed/update/...
Oral History interview with Frederick Hillier | Mark L. Stone
Stanford Emeritus Professor Frederick "Fred" S. Hillier died last week at the age of 89. He was a long-time Professor of Operations Research (OR) at Stanford, and retired early at about the time (1996...
www.linkedin.com
January 27, 2026 at 5:19 AM
𝐀𝐒𝐑𝐈 : 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐒𝐭𝐨𝐜𝐡𝐚𝐬𝐭𝐢𝐜 𝐑𝐞𝐚𝐬𝐨𝐧𝐢𝐧𝐠 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞

ASRI is absent from all frontier AI chatbots and doesn’t seem to be on the near-term horizon

ASRI would correctly perform probability calculations in coherent and consistent manner, using Law of Total Probability
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Significant bias introduced into simple simulation | Mark L. Stone
𝐀𝐒𝐑𝐈 : 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐒𝐭𝐨𝐜𝐡𝐚𝐬𝐭𝐢𝐜 𝐑𝐞𝐚𝐬𝐨𝐧𝐢𝐧𝐠 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 (acronym and term newly introduced in this post) ASRI is absent from all frontier AI chatbots and doesn’t seem to be on the near-term horizon. I b...
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January 2, 2026 at 10:27 PM
The Operations Research version of "There's no free lunch" , as articulated by "The Mythical Man Month author", Fred Brooks:

"You can only get something for nothing if you have previously gotten nothing for something."
December 17, 2025 at 11:11 PM
Is it time to recognize stochastic thinking as the new frontier in AI chatbot inference and prompt engineering? I think so. What do you think? www.linkedin.com/posts/markls...
Stochastic Thinking in AI Development: A Rare Commodity | Mark L. Stone posted on the topic | LinkedIn
Is it time to recognize stochastic thinking as the new frontier in AI chatbot inference and prompt engineering? The number one thing missing from AI scientists' arsenal and from prompt engineering is ...
www.linkedin.com
December 7, 2025 at 3:47 PM
Doing Operations Research (OR):
Figure out how something does or could work, and make it work better.
November 25, 2025 at 11:04 AM
November 19, 2025 at 6:51 PM
My thoughts on using an Operations Research approach to formulate prompts for AI chatbots capable of performing computationally intensive inference.

Hint: Inference should be based on conditional probability, so optimization should be constrained, not unconstrained

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An Operations Research (OR) practitioner's tips on how best to use current (or next) generation AI chatbots capable of performing computationally intensive inference to deliver answers to the… | M...
An Operations Research (OR) practitioner's tips on how best to use current (or next) generation AI chatbots capable of performing computationally intensive inference to deliver answers to the user. W...
www.linkedin.com
November 1, 2025 at 6:35 PM
det(exp(X)) = exp(tr(X)). Remarkably, the RHS does not involve off-diagonal elements of X.
September 19, 2025 at 12:13 AM
I note in passing that I read a new paper today which had 2 instances of "we remark in passing". That's a writing style I associated with decades past, such as a paper I coauthored in "Operations Research" in 1983 which I note in passing used "we note in passing" (attributable to my older coauthor)
January 18, 2025 at 5:25 PM
SR1 is a fairly well-known Quasi-Newton update. Most frequently used in conjunction with Trust Regions on indefinite Lagrangians.

SR! Quasi-Newton update is same as SR1, except for holding on to the shift key too long after the R. Most frequently used by older people with declining visual acuity.
November 18, 2024 at 6:50 PM
A crappy simulation is a crappy simulation, whether or not it's called a Digital Twin.
November 18, 2024 at 6:47 PM