Drake Equation, Abiogenesis and Aliens

[SelfSim]

A major problem is that we don't know in what conditions life arose on the early Earth, and we don't know the precise chemistry involved. We do have a rough idea of the general conditions at the time, but the number of possible environments within those general conditions that might support chemical activity of the kind thought necessary is huge, as is the possible variety of available chemical resources, the variations in conditions over time, and so-on. The diversity includes volcanic pools, hydrothermal vents, various clays, tidal pools, etc. This makes the conditions to research a matter of informed guesswork - which has been surprisingly productive to date, given the vast environmental landscape to be searched. Some things just take time.

Just back-tracking a little here .. with a highly relevant update, (perhaps for future reference).
The project tackles, (head-on), the pre-biotic chemistry research problem.
(Article here), paper follows:
A robotic prebiotic chemist probes long term reactions of complexifying mixtures (my underlines):

Here we report a robotic prebiotic chemist equipped with an automatic sensor system designed for long-term chemical experiments exploring unconstrained multicomponent reactions, which can run autonomously over long periods. The system collects mass spectrometry data from over 10 experiments, with 60 to 150 algorithmically controlled cycles per experiment, running continuously for over 4 weeks. We show that the robot can discover the production of high complexity molecules from simple precursors, as well as deal with the vast amount of data produced by a recursive and unconstrained experiment. This approach represents what we believe to be a necessary step towards the design of new types of Origin of Life experiments that allow testable hypotheses for the emergence of life from prebiotic chemistry.

Background:

Currently the field lacks an experimental design framework that would allow researchers to test competing hypotheses on long timescales, and the number of candidate experiments is gigantic. This problem is made even bigger when the vastness of search space relevant for the investigation of the emergence of life is considered—such a chemical space cannot be adequately explored using experiments that run for a day or a few hours. Here we show a ‘robotic prebiotic chemist’, an automated closed-loop system that runs unconstrained multicomponent chemistry experiments on mineral surfaces in cycles, with fully automated analytical measurements and a decision-making metric.

The eye-catcher here is that it looks like they're using a data/results driven Artificial Learning technique, (looks very similar to reinforcement learning?), which has already shown to produce superior goal oriented performances over humans, in chess matches (see @sjastro's thread here for a quick snap-shot on different AI learning approaches):

Briefly, the molecular transformer is a machine-learning model that takes input reagents as arguments and suggests possible product species, the model has a built-in mechanism to assess (or score) the quality of its prediction on a scale of 0.0–1.0, with reactions scored as 1.0 being the most supported by observed reactions. For our purposes, any combination that gave a score greater than 0.8 was saved and the candidate product was recorded. This analysis yielded 2206 possible reactions, which means they can be predicted based on the structure of the reactants and previously reported reactions from the literature. To visualize this chemical space, these reactions were represented as a network, with reactants being connected to the products if they are part of the same reaction, see Fig. 1B2
...
The system can change experimental conditions and inputs based on the data acquired during the experiment.

This is great stuff!
A very exciting development in Abiogenesis research .. one that may overcome the, thus far, mostly inaccessible views created by vast 'experiments' in a natural environment, over eons of timescales(?)

 

[FrumiousBandersnatch]

This is great stuff!
A very exciting development in Abiogenesis research .. one that may overcome the, thus far, mostly inaccessible views created by vast 'experiments' in a natural environment, over eons of timescales(?)

Very cool! This looks like the way to go - and will probably find applications speeding up many kinds of chemistry research - particularly medical research.