In 1950, Alan Turing proposed “The Imitation Game”, today known as the Turing test, as a hypothetical way of measuring whether a computer can think…
Lonnie Chrisman
Lonnie Chrisman, PhD, is Lumina's Chief Technical Officer, where he heads engineering and development of Analytica. He was awarded the Alton B. Zerby award "Most outstanding Electrical Engineering Student in the USA", 1987. He has a PhD in Artificial Intelligence and Computer Science from Carnegie Mellon University; and a BS in Electrical Engineering from University of California at Berkeley.
Author Posts
Does GPT-4 pass the Turing test?
Managing a portfolio of ESG projects
For Decision Strategies, Inc., the recommendation is clear: ‘Executives who are hesitant about using decision support systems should consider Analytica.’ Pointing executives…
AI weekly updates with Lonnie Chrisman
Join Lonnie Chrisman every Thursday at 8 a.m. PT to hear his latest updates on what is happening in the artificial intelligence (AI) world.
The value of knowing how little you know
Understand the Expected Value of Including Uncertainty (EVIU), compare with the Expected Value of Perfect Information (EVPI), and the insights it gives into a variety of problems.
Making jet fuel from the sun and wind: When will it be cost effective?
Learn more on how Evan Sherwin employed an optimization-based techno-economic analysis, implemented in Analytica, to assess the prospects for large cost reductions.
Applied real options analysis for the finance and decision professional (Aug 25, 2021)
Watch Dan Zoppo’s webinar on the powerful Least Squares Monte Carlo method for real options problems that can add value to a businesses.
Green accountability and incentives: reflecting the social and economic cost of CO2 in new capital projects using Analytica with Robert Brown
Join Robert Brown’s webinar as he reflects on the social and economic cost of CO2 in new capital projects using Analytica.
Decision making when there is little historic precedent
Learn how to make decisions and strategic plans in uncertain situations, where historical data is not available. See how to model this in Analytica with clarity and insight.