I worked for Jeremy. I still think his idea is really beautiful, and when it applies the math is airtight, but it hasn't matured into sharp predictions for real systems.
There were some simulations, but even then it was messy. For example, there were setups where energy was supplied by a driving force, and you could evolve "resonators". A naive application of Jeremy's ideas would predict a lot of structures in resonance with the drive, but in practice you often got less, because too good resonance actually made the structures break apart. So you couldn't get a sharp prediction about the final state even for a really simple system.
The issue is that thermodynamic notions are inherently "coarse", they only give you a high-level view of what's going on. Sometimes it's not powerful enough to say much useful unless you also know the detailed dynamics. This is also why, even if sharp and correct predictions were made for simulated systems, it's quite likely that biologists wouldn't view this as a true explanation for life. They would, perfectly legitimately, want to know about the detailed dynamics, the specific chains of chemical reactions that actually happened.
Now I'm in particle physics, so I'm not up to date, but the same dynamic happens here too. There are lots of beautiful ideas that come up, generate a flurry of excitement, and then get stuck for lack of sharp predictions, or feasible tests of those predictions. We file them away in the hopes that their time will come, possibly generations later. Science is hard!
There were some simulations, but even then it was messy. For example, there were setups where energy was supplied by a driving force, and you could evolve "resonators". A naive application of Jeremy's ideas would predict a lot of structures in resonance with the drive, but in practice you often got less, because too good resonance actually made the structures break apart. So you couldn't get a sharp prediction about the final state even for a really simple system.
The issue is that thermodynamic notions are inherently "coarse", they only give you a high-level view of what's going on. Sometimes it's not powerful enough to say much useful unless you also know the detailed dynamics. This is also why, even if sharp and correct predictions were made for simulated systems, it's quite likely that biologists wouldn't view this as a true explanation for life. They would, perfectly legitimately, want to know about the detailed dynamics, the specific chains of chemical reactions that actually happened.
Now I'm in particle physics, so I'm not up to date, but the same dynamic happens here too. There are lots of beautiful ideas that come up, generate a flurry of excitement, and then get stuck for lack of sharp predictions, or feasible tests of those predictions. We file them away in the hopes that their time will come, possibly generations later. Science is hard!