Browsed by
Category: Future Forecasts

Good Read on Modeling Social Emergent Phenomena – But Still Not There Yet!

Good Read on Modeling Social Emergent Phenomena – But Still Not There Yet!

Philip Ball – Critical Mass The most important thing we can do right now – given the huge changes ahead of us – both in society, the world, and technology – is to get some sort of “handle” on what’s coming up. By that, I mean a good set of models. And as a result, I’m on a search for good models. Those that I know, those that are new. Those that make sense, and those that don’t. (We need…

Read More Read More

Modeling Trends in Long-Term IT as a Phase Transition

Modeling Trends in Long-Term IT as a Phase Transition

The most reasonable model for our faster-than-exponential growth in long-term IT trends is that of a phase transition. At a second-order phase transition, the heat capacity becomes discontinuous. The heat capacity image is provided courtesy of a wikipedia site on heat capacity transition(s). L. Witthauer and M. Diertele present a number of excellent computations in graphical form in their paper The Phase Transition of the 2D-Ising Model. There is another interesting article by B. Derrida & D. Stauffer in Europhysics…

Read More Read More

Going Beyond Moore’s Law

Going Beyond Moore’s Law

Super-Exponential Long-Term Trends in Information Technology Interesting read for the day: Super-exponential long-term trends in Information Technology by B. Nagy, J.D. Farmer, J.E. Trancik, & J.P. Gonzales, shows that which Kurzeil suggested in his earlier work on “technology singularities” is true: We are experiencing faster-than-exponential growth within the information technology area. Nagy et al. are careful to point out that their work indicates a “mathematical singularity,” not to be confused with the more broadly-sweeping notion of a “technological singularity” discussed…

Read More Read More

Gibbs Free Energy, Belief Propagation, and Markov Random Fields

Gibbs Free Energy, Belief Propagation, and Markov Random Fields

Correspondence Between Free Energy, Belief Propagation, and Markov Random Field Models As a slight digression from previous posts – re-reading the paper by Yedidia et al. on this morning on Understanding Belief Propagation and its Generalizations – which explains the close connection between Belief Propagation (BP) methods and the Bethe approximation (a more generalized version of the simple bistate Ising model that I’ve been using) in statistical thermodynamics. The important point that Yedidia et al. make is that their work…

Read More Read More

What Makes a Metastable State Happen?

What Makes a Metastable State Happen?

Metastable States – the Meltdown Precursors I’ve just read a recent column by JL, one of the editors from Taipan Daily. He states, in his column “There Will Be Blood in Europe”: Stepping back a bit: What is so frightening right now, not just in Europe but China and America and Japan too, is the presence of fraud-fueled “Lehman 2.0” catalysts threatening to explode. One could say that the 2008 financial crisis was the mother of all wake-up calls. But…

Read More Read More

"What is X?" – Modeling the Meltdown

"What is X?" – Modeling the Meltdown

“What is X?” – Modeling the 2008-2009 Financial Systems Meltdown We’re about to start a detailed walkthrough of applying a “simple” statistical thermodynamic model to the Wall Street players in the 2007-2009 timeframe. The two kinds of information that I’ll be joining together for this will be a description of Wall Street dynamics, based largely on Chasing Goldman Sachs (see previous blogposts for link), and the two-state Ising thermodynamic model that I’ve been presenting over the past several posts. The…

Read More Read More

Modeling Nonlinear Phenomena

Modeling Nonlinear Phenomena

Modeling Nonlinear Phenomena – What is “X”? Many of us grew up hating word problems in algebra. (Some of us found them interesting, sometimes easy, and sometimes fun. We were the minority.) For most of us, even if we understood the mathematical formulas, there was a big “gap” in our understanding and intuition when it came to applying the formulas to some real-world situation. In the problem, we’d be given a set of statements, and then told to find “something.”…

Read More Read More

"The Origin of Wealth" – Revisited

"The Origin of Wealth" – Revisited

The Origin of Wealth – and Phase Transitions in Complex, Nonlinear Systems Once again, after a nearly two-year hiatus (off by only a week from my first posting on this in May of 2010), I’m getting back to one of my great passions in life – emergent behavior in complex, adaptive systems. And I’m once again starting a discussion/blog-theme referencing Eric Beinhocker’s work, The Origin of Wealth. Since this book was originally published (in 2006), we’ve seen an ongoing series…

Read More Read More

Accelerating Change – A Good Read

Accelerating Change – A Good Read

Writing to you within hours of summer solstice, 2010 – we now have 2 1/2 years (approximately) to the time that has been targeted by multiple cultures as a “pivot point” in human experience. The idea that we are accelerating in our experience on this planet is not new. Right now, this idea is receiving a great deal of attention – too much of which is “acceleration” of emotional content, and not an objective assessment. In this sense, John Smart’s…

Read More Read More

Equilibrium and Utility: Two Different Realms

Equilibrium and Utility: Two Different Realms

Continuing with Beinhocker’s Origin of Wealth, it is important to distinguish carefully between some of the ideas that Beinhocker is expounding. While overall, he is doing a good job of bringing in many related thoughts and ideas, there is a slight tendency towards “mushing.” In that note, I’d like to suggest that we discern carefully between ideas involving utility (Origins, hardcover; pp. 34 & 37), and equilibrium. On pg. 34, Beinhocker begins a discussion of how utility is an underlying…

Read More Read More